6G is expected to run at around 7 GHz on the same site grid that 5G already uses at around 3.5 GHz (i.e, 6G is expected to be collocated with 5G cell). Basically, this is the coverage problem. 6G is likely to work at  the frequency roughly twice as high as 5G frequency, and is expected the link quality still has to reach just as good as 5G frequency (i.e, 6G cell coverage is as far as 5G coverage).

Then how do you check whether the new system(6G) really reaches as far as 5G ? RAN1 set up a way to measure this: one formula, one reference channel, and a template that every company fills in. In this note, I will go through what the contributions settled, what they measured, and where they still disagree.

Everything here comes from the RAN1 contributions in the Reference section at the bottom of the page. When the documents disagree with each other, I put both numbers.

• Executive Summary
• Acronym
• What does "same coverage" mean when 6G moves to 7 GHz?
• Why does the wording "comparable to same" matter?
• How large is the coverage gap between mid-band and 7 GHz?
• What do field measurements say about the 7 GHz penalty?
• Which channels are evaluated, and why is Msg3 the reference?
• Which signals and channels are on the list?
• What do the first Msg3 results look like?
• Why do company link budgets disagree by more than the gap they measure?
• What is in the collection of results?
• What does the Msg3 MIL row show?
• What data rate should the study treat as the coverage target?
• Why are the IMT-2020 rates not the answer?
• Which lower and upper bounds are proposed?
• What UE assumptions does the evaluation rest on?
• How small can the smallest maximum UE bandwidth be?
• How should SRS be designed for 6G coverage and capacity?
• Which sequence families are the starting point?
• Why is SRS capacity the limit that matters?
• Where does the separate NR coverage enhancement work item sit?
• How does the work item extend PRACH and modulation?
• How are repetition and beam indication handled?
• How large is the agreed gap, channel by channel?
• How does each channel stand against Msg3 in the same band?
• What separates the O2I and O2O columns?
• How much does receiver combining of SSB and PBCH recover?
• How much does four-shot combining recover indoors?
• What does it change outdoors, and what does it cost?
• Why does base station beamforming not fix the uplink?
• What do the antenna counts actually say?
• Why does the asymmetry leave the uplink short?
• Can a low PAPR uplink waveform recover the link budget?
• What does the DFT-s-OFDM waveform contribute on its own?
• What is FDSS, and what separates the three options?
• How do CP-OFDM, DFT-s-OFDM and FDSS compare?
• Can a second carrier carry the uplink instead?
• Which use cases were agreed for study?
• Which carrier arrangements are under study?
• Can better coding of small uplink control payloads help?
• Why is the 5G Reed-Muller code not good enough at low code rates?
• What is the counter-argument, and how much gain is claimed?
• Can sparser SRS patterns improve uplink sounding coverage?
• Which comb values are under study?
• What limits and related agreements come with it?
• Can repetition close the gap, and what does it cost?
• What has the 6G study said about it so far?
• Where is repetition being specified, then?
• Reference

Executive Summary

Following is a table for looking up the main points, not a detailed explanation. Each row gives an area, what the contributions say about it, and what it means for the study.

Acronym

The list is short on purpose. I left out the standard NR vocabulary, because anyone reading a 3GPP note already knows it. The terms here are the ones used for the link budget, the deployment scenarios and the waveform proposals.

What does "same coverage" mean when 6G moves to 7 GHz?

Before comparing any numbers, we need to agree on what the target is. A coverage target is useful only if everyone interpret it in the same way. RAN set the aim as re-using the existing 5G mid-band site grid. Then RAN1 had to turn that phrase into something a link budget can test. There are several contributions dealing with how to turn that goal into a test.

RAN#110 set two aims, and they are quite different from each other.

• Re-use the existing 5G mid-band site grid at around 3.5 GHz, for 6G deployments in at least around 7 GHz. The target  is to achieve the same coverage as 5G mid-band for initial access, and  same coverage for data channels at the same data rate.
• Provide enhanced overall coverage compared to 5G in the same band. That aim is focused on cell-edge performance and on the uplink.

RAN1#123 propose a method to achieve the first goal. The starting point for the metric is link budget template candidates 1 and 2. During initial access, the coverage target refers to the bottleneck channel, which is Rel-15 NR Msg3 at 5G mid-band. Four deployment cases are considered: urban macro and sub-urban macro, each with an outdoor-to-indoor case and an outdoor case. The carrier frequency for the 6G deployment is 7 GHz. For the existing 5G mid-band, the agreement wrote [4 GHz] in brackets. Those brackets turned out to matter. I will come back to the final value in the section on the agreed tables.

Then what does "same" actually mean ? An operator group asked to make the meaning clear. Their proposal is that collocation is assumed. So same coverage for initial access means .. if a UE that can access the 5G network , it should be able to access the 6G network at the same location. For connected mode, it means the same data rate per MHz at the same location.

How can we achived this goal.  One of the trick is to use MIMO as the key technology, using a high number of antenna ports (256 as an example) and more than 1000 antenna elements. It also suggests repetitions turn out to be needed for initial access, the number of repetitions will be the study outcome.

Why does the wording "comparable to same" matter?

Why do people care about this here ? Because it can determine which one we can miss and which we cannot miss. The operators asks for the RAN1#123 agreement to be reworded so that it matches what RAN actually decided.

Following is the proposed change. It reads "targeting comparable to same coverage to 5G mid-band" in place of "targeting comparable coverage".

The same proposal asks to report three more things: spectrum efficiency, latency and energy efficiency. With these, an operator can see the trade-off rather than just a single yes or no on coverage.

• The target is relative, not absolute : coverage at 7 GHz is measured against an existing 3.5 GHz deployment, so the answer depends on what that deployment already achieves.
• Initial access and data channels have different targets : same coverage for the first, comparable to same coverage at the same data rate for the second.
• Collocation is the assumption that makes the test meaningful : the same UE at the same location is the comparison, not two separate network designs.
• Repetitions are considered as a cost, not a solution : the operator proposal asks for the required number to be stated explicitly if repetition is required to closes the gap.

How large is the coverage gap between mid-band and 7 GHz?

When we move from 3.5 GHz to 7 GHz, one thing is obvious. We lose some received power. Then the immediate question would be: how much do we lose?

RAN1 agreed on a formula to estimate this loss, and the formula gives us a certain number. However, when people actually went out and measured it in the field, the measured loss was noticeably larger than what the formula predicted.

Personally, I think this gap between the calculated value and the measured value is the most interesting part of this section. The formula itself is relatively simple. The real question is why the real-world result is worse than what the formula tells us.

The agreed calculation subtracts two maximum path losses and a frequency term. MPL1 is the maximum path loss of the evaluated signal or channel at around 7 GHz. MPL2 is the maximum path loss of the bottleneck channel at 5G mid-band, which is Rel-15 NR Msg3 for initial access. PL_diff is 20·log₁₀(f1 / f2), where f1 and f2 are the two carrier frequencies. The agreement also has an additional margin in brackets, and its value is still FFS.

Figure 1. The agreed coverage gap calculation. Three terms, one subtraction, and one value still marked FFS.

The frequency term is the only part you can compute without any assumption. At 7 GHz against 3.5 GHz the ratio is exactly two, so PL_diff is 6.02 dB. So every contribution that reports the gap against a 3.5 GHz reference includes the same 6.02 dB.

What do field measurements say about the 7 GHz penalty?

Then you may ask: how large is this penalty in a real deployment?

A formula can give us the free-space part of the answer. But the real propagation environment is not just free space. Diffraction, scattering, building penetration and many other effects also come into play, and those are not included in the simple formula.

So instead of relying only on calculation, an operator actually went out into the field and measured the difference..

Deutsche Telekom ran a propagation campaign at 3.6 and 6.8 GHz. The setup was deliberately simple.

• A continuous wave signal of very small bandwidth, with omni-directional antennas at both ends.
• Antenna patterns measured by an RF institute, with and without a ground plane.
• Sixteen transmit locations. A lift car gave several heights at some of them, so the analysis counts 29.
• The receive antenna 2 m above ground on a measurement van, which made most of the drive test non line of sight.

The campaign used two evaluation methods, and both gave almost the same answer.

• The first compares the 10th percentile of received power in 50 m distance intervals. Why a percentile ? Because coverage is a level exceeded with a given probability, not an average.
• The second compares average power per 10 m of travelled distance.

The measurement gives us two important numbers.

On average, the received power at 6.8 GHz is about 9 dB lower than at 3.6 GHz. In other words, if we want to close the coverage gap for about 50% of the locations, we need to recover roughly 9 dB.

But if we want to cover more difficult locations as well, the required compensation becomes larger. At the 10th percentile, the difference is around 14 dB. This means that we need roughly 14 dB of additional gain if we want to close the gap with about 90% probability.

So you can think of the numbers roughly like this: 9 dB for the typical case and 14 dB for the more demanding coverage target.

Figure 2. Three estimates of the same penalty. The formula term is the smallest of them, and it is the only one that assumes free space.

At first glance, you may think that 9 dB and 14 dB are just two measurements of the same thing, and the 5 dB difference comes from measurement error or some variation in the experiment.

But this is not the case.

These two numbers are actually describing two different points of the received-power distribution. One is based on the average value, while the other looks at the lower tail of the distribution. The measurement campaign used two different evaluation methods, and each method produced one of these numbers.

In one observation,  it calculates the average received power at each frequency. Then it subtracts the average at 6.8 GHz from the average at 3.6 GHz. This gives a difference of about 9 dB.

In another observation, they looks at the problem differently. Instead of using the average, it takes the 10th percentile of the received power within each 50 m distance bin for both frequencies. Then it compares those two percentile curves. This gives a difference of about 14 dB.

Now you may ask: which number is more meaningful for coverage?

For coverage, we are usually more interested in the weak locations than in the typical location. A user sitting in a good RF condition does not determine the coverage boundary. The difficult locations with low received power is important. In this sense, the second method is more closely related to the actual coverage question.

Figure 3 may help you see why the second number becomes larger.

In the left panel, the received-power distributions for the two frequencies are shown side by side. The mean of each distribution is marked, and the lowest 10% region is also highlighted. You can see that the separation around the weak-signal region is larger than the separation around the mean.

The right panel shows essentially the same information in cumulative-distribution form. Imagine drawing a horizontal line at a certain probability level. The line crosses the two curves at two different received-power values. The horizontal distance between those two crossing points tells you the frequency-dependent gap at that probability.

So the gap is not really one fixed number. It depends on which part of the received-power distribution you are looking at. Around the average, it is about 9 dB. Around the weak-signal region relevant to 90% coverage, it becomes about 14 dB.

Figure 3. What the two field numbers measure. The distributions are not simply shifted, so the distance between them at the 10 per cent line exceeds the distance between their means.

The important point here is that the two curves are not parallel. If the move to 6.8 GHz only shifted the distribution, every percentile would separate by the same 9 dB, and the two observations would agree. But they do not agree, so the spread must also be wider. Deeper diffraction and scattering losses at the higher frequency hurt the weak locations more than the typical one.

NOTE : the curves are an illustration rather than the measured histograms. The contribution publishes the two statistics and not the distributions behind them. The two normal curves drawn here are chosen to reproduce both numbers exactly, 9 dB between the means and 14 dB between the 10th percentiles, which needs the spread at 6.8 GHz to be about 3.9 dB wider. So the shape is just for illustration, but the two separations are the measured ones.

There are two things to keep in mind here, and they affect the result in opposite directions. First, higher building penetration loss at around 7 GHz is not included, so an indoor target would be even larger. Second, the receive antenna was outdoors and mostly non line of sight. So a use case with a high line of sight probability, such as fixed wireless access, would see less than the measured difference.

• The formula and the field disagree by roughly a factor of two : 6.02 dB from 20·log₁₀(f1/f2) against about 9 dB measured on average.
• The probability target changes the answer by 5 dB : 9 dB closes the gap half the time and about 14 dB closes it nine times out of ten.
• Two independent methods agreed : percentile-by-distance and average-per-travelled-interval gave 9 dB and 14 dB either way.
• Indoor is worse and fixed wireless is better : the measured numbers are for an outdoor receiver 2 m above ground, mostly without line of sight.

Which channels are evaluated, and why is Msg3 the reference?

Why do we need a reference channel in the first place?

The basic idea is simple. A cell cannot really be considered larger than the coverage of its weakest essential channel. Even if most channels work well at a certain location, the UE still cannot complete the procedure if one critical channel fails there.

So the study first picks one channel as the coverage reference, and then compares the other channels against it.

For initial access, the reference is Rel-15 NR Msg3.

Why Msg3? Because Msg3 is one of the critical uplink steps during random access, and uplink coverage is often the limiting side of the link. If the UE can receive the downlink but cannot get Msg3 back to the gNB, initial access still fails.

So you can think of Msg3 as the baseline coverage point.

The following RAN1 agreements then evaluate the other relevant channels and procedures relative to this Msg3 reference.

Which signals and channels are on the list?

Then what exactly should be evaluated around 7 GHz?

RAN1 asks companies to provide link-budget results for the main signals and channels involved in initial access. On the downlink, the evaluation includes NR PSS/SSS, SSB, common PDCCH, SIB1 PDSCH, Msg2 PDSCH and Msg4 PDSCH. On the uplink, it includes NR PRACH with formats C2, B4 and 0, Msg3 PUSCH, Msg5 PUSCH, and Msg4 PUCCH format 1. For Msg5 PUSCH, the assumed payload should also be reported.

There are also a couple of common assumptions so that everybody does not start from completely different conditions. The baseline simulation assumptions come from section A.1 of TR 38.830. For NR SIB1 PDSCH, the payload size is assumed to be 1200 bits.

For the remaining parameters, nothing is fixed yet. They are still FFS.

What do the first Msg3 results look like?

Now let's look at an early set of results and see how this comparison works in practice. The case is Msg3 PUSCH on 2 resource blocks, at code rate 120/1024, with a 56 bit transport block.

• Maximum coupling loss is 126.96 dB at both frequencies. So the channel itself has not become harder to decode.
• Maximum isotropic loss rises from 136.73 dB to 139.74 dB.
• Range for urban macro outdoor-to-indoor falls from 67.16 m to 36.85 m.
• Range for urban macro outdoor falls from 522.01 m to 437.17 m.

Then you may ask about the other channels. A later contribution applies the agreed gap formula to two of them. For urban macro outdoor-to-indoor, it reports −6.77 dB for PRACH format 0 and −7.37 dB for PUCCH format 1. For urban macro outdoor, it reports −2.32 dB and −3.02 dB. In each case, the 6.02 dB frequency term is subtracted from the difference of the two maximum path losses.

• Msg3 is the reference, not the only channel measured : nine other signals and channels are evaluated, and all of them are compared against the Msg3 reference.
• The comparison is a range, not a margin : the same coupling loss at both frequencies still produces a much shorter reach once the path loss model is applied.
• PRACH and PUCCH are evaluated too : the agreed formula is applied channel by channel rather than once for the cell.
• TR 38.830 supplies the starting assumptions : the 6G study did not start its link budget from scratch.

Why do company link budgets disagree by more than the gap they measure?

Companies submitted their link-budget results over three rounds of email discussion. But when all of those results were finally put together, something more interesting showed up.

Different companies were evaluating the same channel under the same scenario, but the reported link-budget numbers were still quite far apart. In fact, the difference between companies was sometimes larger than the frequency-related gap that the study itself was trying to measure.

That is a pretty important point.

If the spread between company results is larger than the effect we are trying to quantify, then we cannot simply look at one link-budget number and treat it as an absolute answer. Before comparing 3.5 GHz and 7 GHz, we first have to understand why the baseline link budgets themselves are different.

What is in the collection of results?

After RAN1#124bis, the collected results put the submissions from eighteen companies side by side with the reference template. About eighteen companies provided results for the urban macro outdoor-to-indoor scenario.

The important point here is not who submitted the numbers, but that a fairly large number of companies evaluated the same scenario independently. This gives us a good basis for looking at how much the reported link-budget results differ from one company to another

What does the Msg3 MIL row show?

You can see the problem very clearly if you look at the maximum isotropic loss for Msg3.

At 5G mid-band, the submitted values range from 140.04 dB to 157.70 dB. That is already a spread of about 17.7 dB. Around 7 GHz, the values range from 144.81 dB to 163.88 dB, giving an even larger spread of about 19.1 dB.

Now compare this with the actual frequency gap we are trying to measure. That gap is only a few dB. So the variation between company link-budget results is several times larger than the effect we are trying to quantify.

This is the real difficulty. Before we can confidently say how much coverage changes from mid-band to around 7 GHz, we first have to separate the frequency effect from the much larger differences coming from the link-budget assumptions themselves.

Then you may ask how RAN1 handled this. It did not average the results. It agreed to align how companies interpret the inputs instead. There are four things on that list.

• Antenna gain correction factors at components 3 and 4, and separately at component 2, for both transmitter and receiver.
• Receiver interference density.
• Penetration margin, and whether indoor distance is counted in the path loss for outdoor-to-indoor scenarios.
• Shadow fading margin, including how the function is defined and whether a handoff gain is counted.

• The method is agreed, but the inputs are not : one formula produced a 17 to 19 dB spread, so the disagreement is entirely in the parameters.
• Antenna gain accounting is the largest single ambiguity : four of the seven parameters on the alignment list are antenna gain correction factors.
• Shadow fading and penetration margin are the other two : both are margins rather than measurements, and companies were applying both of them differently.
• Three email rounds were needed before the meeting : the collection ran after RAN1#124 and again after RAN1#124bis.

What data rate should the study treat as the coverage target?

When we talk about the coverage of a data channel, just saying "coverage" is not enough. We also need to specify the data rate.

The same channel may work at the cell edge if the required data rate is very low, but it may fail much earlier if we ask for a higher throughput. So the coverage target does not really mean much unless the target data rate is defined together with it.

Then the next question is: what data rate should we use?

The contribution in this section does not try to pick one exact number. Instead, it proposes two bounds.

Why two bounds?

Because the most obvious source for choosing the target data rate gives values that are not very realistic for this particular coverage study. So rather than forcing one questionable number, the contribution defines a reasonable range and evaluates the problem within that range.

Why are the IMT-2020 rates not the answer?

The first numbers that may come to mind are the ITU IMT-2020 targets: 100 Mbps in downlink and 50 Mbps in uplink. But those numbers were not used even in the Rel-17 NR coverage-enhancement study.

Instead, TR 38.830 used much lower data rates.

For the urban scenario, the assumed rates were 10 Mbps in downlink and 1 Mbps in uplink. Compared with the IMT-2020 figures, this is 10 times lower in downlink and 50 times lower in uplink.

For the rural scenario, the assumed rates were even lower: 1 Mbps in downlink and 100 kbps in uplink. That is 100 times lower in downlink and 500 times lower in uplink.

So the lesson here is that a coverage study should not automatically use the headline IMT-2020 throughput numbers. When the real question is cell-edge coverage, much lower data-rate targets may be more meaningful.

Which lower and upper bounds are proposed?

An operator group proposes to use the TR 38.830 values as the lower bound.

For urban and rural scenarios, this is relatively straightforward because TR 38.830 already gives us target data rates. But for the suburban scenario, both downlink and uplink are left FFS.

Why?

The suburban case was added to the channel model only in Rel-19. So there is no older coverage-study target that can simply be reused.

Then what should we use for the upper bound?

Instead of taking another number from a specification, the contribution looks at actual field measurements.

The trials used an n78 carrier with 90 MHz bandwidth and 32-TRx and 64-TRx antenna systems from different vendors. Neighbouring n78 cells were turned off so that the test would be closer to a noise-limited condition even though the measurements were done in a dense urban environment.

Then what did they actually see?

Even when RSRP dropped below about -115 dBm, a single active UE could still achieve around 100 Mbps in downlink and around 10 Mbps in uplink. Based on these measurements, the contribution proposes roughly 100 Mbps DL and 10 Mbps UL as the upper-bound target for a 100 MHz carrier.

So the overall idea is to define a range rather than one magic number: reuse the conservative TR 38.830 values as the lower bound, and use field-measured performance as the upper bound.

• Two bounds, not one target : TR 38.830 supplies the lower bound and an operator trial supplies the upper bound.
• The ITU numbers were judged too high : the same figures were already passed over once, when NR studied coverage enhancement in Rel-17.
• The upper bound is a field observation : 100 Mbps down and 10 Mbps up came from a single UE in a cell with its neighbours switched off.
• Suburban has no target yet : the scenario entered the channel model in Rel-19 and both directions are still FFS.

What UE assumptions does the evaluation rest on?

A link budget does not depend only on the base station side. It also depends a lot on what kind of UE is sitting at the other end of the link.

So before comparing results from different companies, a few UE assumptions had to be fixed first.

The study focuses on three things: how many antennas the UE has, how much bandwidth the UE can support, and what kind of payload is carried in the initial-access messages.

If these assumptions are different, the resulting link budgets can easily move by several dB. So without fixing them first, comparing the numbers would not be very meaningful.

Let's start with the antennas. Three antenna sets are under evaluation for study up to 7 GHz. None of them constrains a later discussion of UE capability.

• Up to 4 transmit and receive antenna elements.
• Up to 8 transmit and receive antenna elements.
• Up to 16 receive antenna elements, intended only for fixed wireless access.

An operator group also proposes a lower limit for the UE antenna assumption.

In current 5G NR n78 operation, a UE already has at least four receive antenna ports. So the proposal is simple: use the same minimum of four receive antenna ports for the study around 7 GHz.

Then we come to the third assumption: what exactly is carried in the initial-access messages?

At this point, this part is not really defined yet. The format, payload and size of the 6G initial-access messages are still largely open.

So what should RAN1 do in the meantime?

The proposal is to reuse the corresponding 5G NR message assumptions until RAN2 or SA2 provides something more concrete.

This is basically a practical choice. Otherwise, the RAN1 coverage evaluation would have to wait for the higher-layer message definitions to become stable.

How small can the smallest maximum UE bandwidth be?

A UE with a narrow bandwidth is usually cheaper and simpler to build. But from the network point of view, a very narrow UE bandwidth can make scheduling more difficult. So this question has come up several times in RAN1 discussions: how much bandwidth should the UE actually support?

The answer proposed in this section is not one single number. It depends on the link direction and also on the type of device we are talking about.

At RAN1#123, three alternatives were agreed for further study.

• Alternative 1 is the simplest case: 20 MHz RF bandwidth and 20 MHz baseband bandwidth.
• Alternative 2 goes much narrower: 5 MHz RF and 5 MHz baseband. For the TDD combination, however, 10 MHz or 20 MHz is considered.
• Alternative 3 keeps the RF bandwidth at 20 MHz, but allows the baseband bandwidth to be smaller than 20 MHz.

So the basic tradeoff is clear. Narrower bandwidth can reduce UE complexity and cost, but the network has less frequency-domain flexibility when scheduling that UE.

The operator position is that downlink and uplink behave differently.

• Cutting downlink RF bandwidth from 20 MHz to 5 MHz in FDD bands would hurt eMBB UEs and overall cell efficiency. A UE narrower than the carrier can only be scheduled where the SSB is, unless extra common signals are added, and the device saves little in return.
• In the uplink the same cut still restricts scheduling. It raises no problem for RACH or control signals, and the cost saving is real for half duplex FDD with a SAW-less implementation.

Two more proposals come from the deployment side. One asks to study mechanisms that bar IoT devices from a particular carrier. The other asks to study mechanisms that move them onto a chosen carrier, during or before initial access. Why both ? Because operators run low bands as a coverage layer and wide high bands as a capacity layer.

• Four receive ports is the proposed floor : it matches what n78 already requires of every 5G UE.
• The message contents are borrowed until they are defined : 6G initial access is evaluated with NR formats, payloads and sizes as a placeholder.
• Downlink and uplink get different answers : 20 MHz both ways in general, and 20 MHz down with 5 MHz up only for half duplex FDD IoT devices.
• The saving only appears in one configuration : the contribution identifies half duplex FDD with a SAW-less design as the case with significant device cost reduction.

How should SRS be designed for 6G coverage and capacity?

Uplink sounding has two different problems that have to be solved at the same time.

The first one is coverage. The sounding signal transmitted by the UE has to be strong enough to reach the base station and be detected reliably.

The second one is separation. Many UEs may transmit sounding signals at the same time, so the base station has to figure out which sounding signal came from which UE.

You can think of the first problem as "Can I hear the signal?" and the second one as "Can I tell whose signal it is?"

Most of the contributions discussed in this section are focused on the second problem: how to separate and identify sounding signals when many UEs are transmitting them at the same time.

RAN1#124 listed eight aspects to study for SRS in uplink and downlink CSI acquisition.

• Efficient support of larger channel bandwidth.
• Capacity enhancements.
• Coverage enhancements.
• Efficient resource utilisation.
• Dynamic and flexible adaptation of SRS parameters.
• Multi-TRP transmission and reception, fixed wireless access, high speed train and other high mobility scenarios.
• Interference mitigation.
• Energy efficiency.

Which sequence families are the starting point?

RAN1#124bis narrowed down the starting point for the 6G SRS study.

For the sequence design, NR ZC and CGS sequences are used as the baseline.

For the frequency-domain pattern, the starting point is also taken from 5G NR: the per-resource SRS pattern with comb values 2, 4 and 8.

But this is only the starting point. Two additional areas are still left for further study.

One is how to multiplex multiple SRS ports.

The other is whether more sparse frequency-domain patterns should be supported. This may include larger comb values or even non-uniform patterns.

Of course, making the pattern more flexible is not free. The study also needs to look at what these choices do to implementation complexity, coverage, capacity and overall performance.s

Why is SRS capacity the limit that matters?

Why does SRS capacity become such an important issue?

The main limitation comes from the number of cyclic shifts that can be generated from one root sequence.

In NR SRS, a single root sequence typically supports only a limited number of cyclic shifts, such as 6, 8 or 12. This directly limits how many UEs can transmit SRS at the same time while still remaining orthogonal.

So if we want to support many more simultaneous sounding UEs, simply reusing the existing cyclic-shift structure may not be enough.

One proposal tries to solve this by using non-orthogonal pilots generated from multiple root indices. The contribution asks for support of more than 60 root indices, which would greatly increase the number of available sounding sequences.

A later proposal from the same source takes a slightly different approach, called adjustable phase-shift ZC.

In the conventional approach, cyclic shifts are usually spaced in a regular way. In this new approach, the shifts are selected based on the statistical characteristics of the channel.

Then you may ask: why would irregularly spaced shifts help?

The key idea is sparsity.

In a massive-MIMO OFDM channel, most of the angle-delay grid contains very little energy. The dominant channel components may occupy less than 5% of the total angle-delay elements.

This means the network does not necessarily need to keep every UE perfectly orthogonal everywhere. Instead, it can choose phase shifts so that the dominant components of different UEs overlap as little as possible in the angle-delay domain.

So the basic idea is to trade strict sequence orthogonality for channel-aware separation. If the channel is sparse enough, more UEs may be able to sound at the same time without causing too much interference.

The supporting simulation is run at 3.5 GHz with 15 kHz subcarrier spacing. It uses a 16 by 16 dual-polarised planar array, 2048 subcarriers with 1200 of them used for training, and a cyclic prefix length of 144.

• The cyclic shift count is the capacity ceiling : the limit of 6, 8 or 12 shifts of one root sequence decides how many UEs can sound together.
• Both proposals trade orthogonality for capacity : more root indices or unevenly spaced shifts, in each case accepting some correlation.
• NR sequences remain the baseline : ZC and CGS are the agreed starting point, so these are extensions rather than replacements.
• Sparsity is what makes overloading work : fewer than 5 per cent of angle-delay elements carry the channel, which leaves room to separate the users in that domain.

Where does the separate NR coverage enhancement work item sit?

One of the contributions discussed here is actually not part of the 6G study. It belongs to a separate NR coverage-enhancement work item under a different agenda item, so the agreements from that contribution apply to NR, not directly to 6G.

Then you may ask: why include it here?

The reason is simple. The techniques being studied there are exactly the kinds of techniques that the 6G coverage study will also need to think about. That NR work item runs under agenda item 10.4.1 and deals with NR coverage enhancements phase 3.

At RAN1#122bis, the agreements mainly covered two areas: multiple PRACH transmissions and modulation. So even though this is formally an NR discussion, it still gives us a useful preview of the mechanisms that may later become relevant to 6G coverage enhancement as well.

How does the work item extend PRACH and modulation?

For multiple PRACH transmissions, the basic question is how the gNB can distinguish one transmission from another.

If the UE uses the same transmit beam for multiple PRACH transmissions, the transmissions can be separated using different ROs or different preambles within the same RO. The same basic mechanisms can also be used when different transmit beams are applied.

The working assumption is to have one common solution rather than designing a separate mechanism for every procedure.

That common solution is expected to cover three cases: contention-based random access, contention-free random access during reconfiguration with sync, and system information request.

Another part of the agreement deals with modulation.

The idea is to extend pi/2-BPSK to additional MCS entries. The extension applies only to entries whose spectral efficiency is no larger than a threshold N. N will not be greater than 0.8770, but the exact value is still FFS.

There is one detail that may look a little strange at first. When pi/2-BPSK is used for these additional entries, the code rate is doubled.

Why?

Because BPSK carries only one modulation bit per symbol, while QPSK carries two. Doubling the code rate compensates for this difference so that the overall spectral efficiency of the MCS entry remains the same.

RRC signalling is also introduced so that the network can enable this extended pi/2-BPSK operation.

Then the remaining question is: which MCS entries should actually support it?

That is determined by link-level simulation. The evaluation considers two possible sources of gain. One is the direct link-level gain from using pi/2-BPSK. The other is the additional transmit-power gain that may be possible because pi/2-BPSK has a lower peak-to-average power ratio.

So the final benefit is not just a modulation gain. Part of the coverage improvement can also come from allowing the UE power amplifier to operate closer to its maximum output power.

Another agreement reuses what NR already has, instead of inventing something new. Five things from the same-beam case are reused for the different-beam case.

• The definition and determination of the RO group.
• The definition of the time period.
• The SSB-to-RO mapping rule.
• The time offset between RO groups.
• The PRACH power control rule, with power ramping left FFS.

How are repetition and beam indication handled?

For repetition, the proposal is not to invent a completely new rule. Instead, the existing Msg3 repetition behavior is reused. The same rules for determining the redundancy version and for finding the available transmission slots are applied to PUSCH repetition scheduled by DCI 0_0 with C-RNTI.

There is one limitation, though. This reuse applies only to repetition type A. So the basic idea is simple: wherever possible, keep the new PUSCH repetition behavior aligned with the already defined Msg3 repetition procedure rather than introducing another separate mechanism.

Then how does the network tell the UE which uplink beam to use ? This is the open question in that contribution, and five options were proposed.

• Implicit indication by RA-RNTI.
• Explicit indication in DCI format 1_0 scrambled by RA-RNTI.
• Repurposing fields in the UL grant in the RAR.
• A new field in the MAC RAR.
• Repurposing bits in the MAC RAR.

The contribution prefers the third one. Why not the others ? The first option adds UE complexity, and the second and fourth reduce the network’s freedom to pack several RARs into one MAC PDU.

The same work item is covered in full elsewhere on this site. Coverage Enhancement - NR Phase 3 follows all three of its objectives through the RAN1 agreements from RAN1#122bis to RAN1#125. This section summarises only the one contribution that reached the 6G study.

• This work item is NR, not 6G : it runs at agenda item 10.4.1 and its agreements do not carry into the 6G study automatically.
• The techniques overlap with the 6G coverage problem : PRACH repetition across beams and a lower peak to average waveform both address uplink reach.
• pi/2-BPSK is extended by doubling the code rate : spectral efficiency is held constant, so the gain comes from the waveform rather than from the coding.
• Reuse is the default : RO groups, time periods, SSB-to-RO mapping and power control all carry over from the same-beam case.

How large is the agreed gap, channel by channel?

So far, we have mainly been looking at how the coverage gap should be measured.

At RAN1#126, that part of the study was finally completed. The result was summarized into four tables, one for each deployment scenario.

These tables are important because they become the baseline for everything that comes next. Any coverage-enhancement technique discussed in the rest of this page has to be evaluated against the gaps shown in these tables.

All four tables use the same definition: the coverage gap between 7.0 GHz and 5G mid-band at 3.5 GHz.

There is one detail here that is easy to miss. The reference frequency is 3.5 GHz, not 4 GHz. Earlier, the RAN1#123 agreement still showed 4 GHz in brackets, but the final evaluation uses 3.5 GHz.

Why does this matter?

Because the frequency itself already introduces a different free-space loss depending on which reference you use. Going from 3.5 GHz to 7 GHz gives about 6.02 dB of frequency-dependent loss, while going from 4 GHz to 7 GHz gives only about 4.86 dB.

So if you mistakenly interpret these tables as a 4 GHz-to-7 GHz comparison, you would make the frequency penalty look larger than it really is for that reference.

Each table entry is based on a trimmed mean of the submitted company results. The table also shows the number of samples and the standard deviation, so you can get some feeling for how consistent the submissions were.

The sign of the number is also important. A negative value means that the 7 GHz case falls short of the 3.5 GHz reference by that amount. A positive value means that the channel already has some margin relative to the reference.

The tables also give us a way to move the reference from 3.5 GHz to another mid-band frequency.

For example, when the reference is changed from 3.5 GHz to 2.6 GHz, the Msg3 difference is 4.5 dB for the urban macro outdoor-to-indoor case and 2.58 dB for urban macro outdoor.

One important assumption is made here: this difference is applied equally to all signals and channels.

So you should not think of it as changing only the Msg3 value. It shifts the entire set of results for that scenario by the same amount.

The agreed coverage gap in dB for each signal and channel, across the four scenarios. Negative is a shortfall.

Now let's read the urban macro outdoor-to-indoor column from top to bottom, because it shows where the difficulty is. Figure 4 plots that column.

Figure 4. The urban macro outdoor-to-indoor column drawn to scale. The uplink data channels sit at the bottom, and they are the ones that decide the cell.

There are two points I want you to notice in that chart. The first is that the uplink channels dominate the deficit. Msg5 PUSCH at −13.00 dB and Msg3 PUSCH at −8.68 dB are the two worst entries in the whole table. The second is that the outdoor scenarios are much easier than the indoor ones. The reason is building penetration loss at 7 GHz, which is what makes outdoor-to-indoor hard.

How does each channel stand against Msg3 in the same band?

Figure 4 answers a question that spans two frequencies. But the study also needs to answer a question about a single frequency. Which channel actually limits the cell ? Msg3 is named as the reference channel everywhere, and you can compare the collected results to see how far the other channels are from it.

Then how do we get that number ? We subtract within each company column. Every company that submitted a full channel set at around 7 GHz also submitted its own Msg3 PUSCH. So if you subtract that company’s Msg3 maximum isotropic loss from each of its other channels, you get a relative figure, and the company’s own assumptions cancel out. Results from thirteen companies can be compared this way. The chart shows the median of those differences.

Maximum isotropic loss is the right row for this comparison. It stops before the shadow fading and penetration margins, so the ranking in Figure 5 does not change between the outdoor-to-indoor and outdoor scenarios. Only the range that each figure gives you changes.

Figure 5. Every channel measured against Msg3 in its own band, not against itself at another frequency. Positive means the channel reaches further than Msg3.

The first thing you would notice is that the downlink sits well above the uplink. Msg4 PDSCH, PBCH, Msg2 PDSCH and the two SIB1 channels all land between 7 and 9 dB above Msg3. This margin comes from the antenna asymmetry explained in the beamforming section. Here we see its effect on the channel comparison. The base station uses 768 or more elements on the downlink, and the UE transmits with one.

The uplink channels spread out much more than the downlink ones. PUCCH format 1 has a margin of 6.80 dB, because two bits over one resource block is the smallest payload on the list. The three PRACH formats fall in the order of how much energy they carry, from 6.02 dB for format 0 down to 0.10 dB for format C2.

Now pay attention to the two rows that give the answer. PRACH format C2 lands on the line, so it is the only non-data channel that matches Msg3 rather than beating it. Msg5 PUSCH sits 6.04 dB below, so it is the weakest channel in the set, not Msg3.

Then you may ask whether this contradicts the study. It doesn't. Msg3 is the reference for initial access, not the weakest channel overall. Msg5 carries a larger payload and arrives after the connection is up. So the study measures it, but it does not size the cell with it.

• The downlink has 7 to 9 dB of margin : every broadcast and downlink data channel reaches further than Msg3 in the same band.
• Msg3 is second from the bottom : only Msg5 PUSCH is worse, and it is worse by 6.04 dB.
• PRACH format C2 is the borderline case : at +0.10 dB it neither helps nor hurts, while format 0 has 6.02 dB of margin.
• The ranking stays the same across scenarios : maximum isotropic loss excludes the penetration margin, so indoors and outdoors give the same order.

NOTE : these medians are computed from the collection, not agreed by RAN1. Each median uses between six and thirteen company submissions, because companies filled in different channel sets. The per-company spread is wide too, because they assume different bandwidths and beam counts. PBCH runs from −4.61 to +16.92 dB across the thirteen entries. So what matters here is the order of the channels, not any single figure.

What separates the O2I and O2O columns?

In every agreed table, the O2I and O2O scenarios are shown side by side, and O2I always comes out worse.

Then you may ask: where does that difference actually come from? he answer is probably not where most people would first expect.

First of all, neither number comes directly from a field measurement. Both are calculated from the same link-budget template. Basically, the same template is filled in once for O2O and once for O2I.

If you put the two sheets side by side, you would notice that most of the parameters are actually identical. Only a small number of assumptions change between the two cases.

So the O2I penalty is not coming from a completely different model. It comes from a few specific terms in the same link budget.

The same Msg3 link budget under the two scenarios. The last column counts the 96 columns that carry the same company, carrier frequency and channel in both sheets.

The radio is the same equipment in both sheets, and most rows show that. Transmit power, antenna counts and noise figure never change. A quarter of the columns do re-run the noise and sensitivity chain, so the MIL differs in 27 of the 96. But row 27 differs in all 96.

The O2I cells are not just values typed into the spreadsheet. Thirty-three of them still contain the formula used to calculate them. Following is that formula.

PL_tw = 5 − 10 log₁₀ ( 0.7 · 10^{−(25.4 + 0.11 f )/10} + 0.3 · 10^{−(5 + 4 f )/10} )

This is the high-loss model of TR 38.901 Table 7.4.3-2, where f is the carrier frequency in GHz. The first term is infrared reflecting glass at 70 per cent weight, using the Release 19 value of 25.4 + 0.11 f. The second term is concrete at 30 per cent weight, at 5 + 4 f. If you evaluate it, you get 27.50 dB at 3.5 GHz and 32.35 dB at 7 GHz.

The penetration margin, split into the two terms TR 38.901 defines for it.

If you subtract the wall formula from every entry, a value remains. That value is constant for each company and does not change with frequency, so it is the indoor depth term. Six companies add nothing at all. Five add 6.25 dB, two add 4.17 dB, one adds 5.6 dB and one adds 10.18 dB. If you halve those figures, you get the depth each company assumed, from 0 m to 20.4 m inside the building.

So the wall is not in dispute. Every company uses the same formula for it. The apparent 18 dB spread is actually two separate effects mixed together. One part is carrier frequency, since the collection covers 2.5 GHz to 8.4 GHz. The rest is how far inside the building the user is assumed to stand. At a single frequency the spread is 10.18 dB, and all of it comes from depth.

The outdoor value is not zero either. RAN1 agreed 9 dB of car penetration loss for the outdoor scenarios, from TR 38.901 clause 7.4.3.2. So O2O actually models a user inside a vehicle, not a user standing in the open.

Then how does this affect the coverage gap ? The wall costs 4.85 dB more at 7 GHz than at 3.5 GHz, and nothing in the outdoor column changes with frequency. So the indoor gap is larger than the outdoor gap by roughly that amount. IIT Madras and CEWiT show this in their own tables: PRACH format 0 sits at −6.77 dB indoors against −2.32 dB outdoors, and PUCCH format 1 at −7.37 dB against −3.02 dB.

• O2I and O2O are computed, not measured : both come from the same link budget template, filled in twice.
• One row carries the difference : the penetration margin, and it differs in all 96 matched columns.
• The wall is agreed, the depth is not : every company uses the same wall formula, and differs only on how far inside the user stands.
• It shows up as range : a median of 196 m for Msg3 indoors against 642 m outdoors, from the same hardware.
• Outdoor is not open air : the 9 dB is car penetration loss, so the outdoor user sits in a vehicle.

NOTE : the Deutsche Telekom propagation campaign quoted earlier is a real measurement rather than a template, and its receiver sat outdoors 2 m above ground. So its 9 dB and 14 dB figures describe the outdoor case. The contribution itself says clearly that the difference becomes larger once the higher building penetration loss at around 7 GHz is counted.

Two supporting assumptions were fixed at the same meeting. The receiver noise figure is 9 dB for downlink and 5 dB for uplink. RAN1 sent a liaison statement to RAN4 to tell them this, without implying that RAN4 should adopt it. Cell area reliability stays at 95 per cent for control channels, SSB and SIB1, and 90 per cent for channels capable of HARQ retransmission, with retransmission not assumed.

• The uplink data channels set the cell size : Msg5 PUSCH and Msg3 PUSCH carry the two largest deficits in every scenario.
• Outdoor-to-indoor is the hard case : the same channel can sit at −8.68 dB indoors and −3.75 dB outdoors in the same urban macro scenario.
• Some channels already have margin : PRACH format 0 reaches +2.54 dB in urban macro outdoor, so it is not the channel to spend effort on.
• The spread across companies is now small : standard deviations mostly sit between 0.3 and 2.6 dB, against the 17 to 19 dB spread that the raw submissions had before alignment.

How much does receiver combining of SSB and PBCH recover?

The agreed tables already include the result for the first coverage-enhancement technique.

If you look carefully at the tables, you would notice that two entries appear twice: PSS/SSS and PBCH. Each one is evaluated once without receiver combining and once with receiver combining. So the combining gain does not have to be estimated separately. You can get it directly from the table by subtracting the result without combining from the result with combining.

In other words, the gain is already embedded in the agreed link-budget results. It is not an additional assumption or a separate claim.

How much does four-shot combining recover indoors?

For the urban macro outdoor-to-indoor case, combining across four SSB transmissions gives a pretty noticeable improvement.

For PSS/SSS, the coverage gap improves from -7.24 dB to -4.08 dB. That means the combining recovers about 3.16 dB.

For PBCH, the improvement is even larger. The gap changes from -8.32 dB to -3.09 dB, which corresponds to a gain of about 5.23 dB.

So four-shot combining helps both channels, but the amount of gain is not the same. In this case, PBCH benefits more than PSS/SSS.

What does it change outdoors, and what does it cost?

In the outdoor case, combining does something more important than just reducing the size of the gap. For urban macro outdoor, PSS/SSS improves from -2.81 dB to +1.13 dB, and PBCH improves from -1.51 dB to +1.69 dB. So both channels cross zero.

That means that, with combining, these two channels no longer have a coverage shortfall relative to the 3.5 GHz reference.

Then you may ask: what is the price for this gain?

The cost is mainly time.

The UE has to receive multiple SSB transmissions and combine them before decoding. In this case, it combines four SSB transmissions, so the initial-access procedure takes longer. There is no extra spectrum being consumed just for the combining, and there is no additional transmit-power requirement. The trade-off is latency. This is why the study keeps both cases in the table instead of simply assuming combining everywhere. You gain coverage, but you pay for it with a longer initial-access time.

• The gain is measured, not projected : both rows come from the same agreed table, so the difference between them is the technique.
• Three to five dB from four combinations : 3.16 dB for PSS/SSS and 5.23 dB for PBCH in urban macro outdoor-to-indoor.
• It closes the outdoor gap entirely : both channels move from negative to positive in urban macro outdoor.
• It does nothing for the uplink : combining applies to downlink broadcast, and the worst entries in the table are uplink data channels.

Why does base station beamforming not fix the uplink?

When we see a coverage gap, the first thing that may come to mind is antenna gain. And in fact, the agreed link-budget assumptions already include a pretty large amount of base-station antenna gain.

Then you may ask: if the base station is already using strong beamforming, why do we still have an uplink coverage gap?

The answer becomes clear if you look at one particular row in the link-budget spreadsheet.

The problem is not simply whether the base station can form a narrow beam. The important question is how much of that beamforming gain can actually be used on the uplink under the assumed antenna configuration.

So even though the antenna array itself provides a large gain, that does not automatically mean that the remaining uplink deficit disappears.

What do the antenna counts actually say?

The antenna-count assumption makes the asymmetry very clear.

If you look across the company submissions, the downlink base-station side uses either 768 or 1024 transmit antenna elements. But on the uplink, the UE side uses only one transmit antenna element in every submission. So the two directions start from very different antenna assumptions.

On the downlink, the base station can make use of a very large antenna array. On the uplink, the UE is still transmitting from a single antenna element.

This is why simply saying that the base station has massive beamforming does not solve the uplink problem. The uplink transmit side is still limited by the UE.

Why does the asymmetry leave the uplink short?

This antenna asymmetry explains why the uplink still remains the difficult side. On the downlink, the base station can keep increasing array gain by using a larger antenna array. But on the uplink, the transmitter is the UE. If the UE still transmits from a single antenna element, the network cannot create the same kind of transmit-array gain there.

Of course, the base station array still helps on uplink reception. The gNB can combine the received signal across many antenna elements and get receive-array gain. But that gain is already included in the agreed link-budget templates. So simply increasing the base-station array does not create a completely new uplink gain on top if the numbers we already have.

Interestingly, an operator contribution still points to large-scale MIMO as the main technology for matching the 3.5 GHz site grid at 7 GHz. The proposal mentions a very large number of antenna ports, for example 256 ports, implemented with more than 1000 antenna elements. So the message is not that massive MIMO is useless for uplink. It is still one of the key technologies. The point is that much of its receive-side gain is already counted, while the UE transmit side remains fundamentally more constrained.

• The templates already assume 768 to 1024 elements on the downlink : the deficit in the agreed tables is what is left after that gain is counted.
• The UE transmits from one element : every uplink column in the collection uses 1, and this caps what beamforming can do for the uplink.
• Base station arrays help the uplink only on receive : the gain is real, but the numbers already include it.
• So the remedies in the following sections are uplink remedies : waveform, coding, carrier choice and sounding all work where array gain cannot help.

Can a low PAPR uplink waveform recover the link budget?

Why does the uplink waveform matter for coverage?

A UE cannot always transmit at its nominal maximum power. The actual transmit power is limited by how much power its amplifier can generate while keeping the waveform sufficiently linear.

This is where PAPR becomes important.

A waveform with large peaks needs more power backoff. A waveform with lower peak-to-average power ratio can operate closer to the UE's maximum power.

So reducing PAPR directly translates into uplink link-budget gain. And unlike some other coverage-enhancement techniques, this gain does not require additional spectrum.

Then you may ask: how much gain are we talking about?

The evaluation results give us a useful example.

In one submitted result, the maximum power reduction is about 5 dB for DFT-s-OFDM and about 8 dB for CP-OFDM under the same configuration. That is a 3 dB difference.

The evaluation used 4 GHz, a 64-TxRU base station and a two-transmit UE with a nominal transmit power of 31 dBm. So just by moving from CP-OFDM to the lower-PAPR DFT-s-OFDM waveform, roughly 3 dB can become available to the uplink link budget before changing anything else.

This is why waveform design itself can become a coverage-enhancement technique. The gain does not come from transmitting more nominal power. It comes from allowing the UE to use more of the power it already has.

What does the DFT-s-OFDM waveform contribute on its own?

The shaping techniques discussed later in this section are applied on top of a waveform that already has a lower PAPR than the alternative.

So I think it is important to separate these two effects.

One gain comes from choosing DFT-s-OFDM instead of CP-OFDM. The other comes from additional shaping or modulation techniques applied afterward. These are not the same thing, and only the first one is shown to remain essentially unchanged when the carrier moves to 7 GHz.

Why does DFT-s-OFDM have this advantage?

Before the symbols are mapped onto the OFDM subcarriers, DFT-s-OFDM first spreads them through a DFT. This is why the discussions can refer to a DFT size in the first place.

The contributions treat DFT-s-OFDM and CP-OFDM as two alternative uplink waveforms. They are evaluated side by side, not combined together.

One submitted result compares them at both 4 GHz and 7 GHz while keeping the UE assumptions as similar as possible.

• At 4 GHz, the evaluation uses 20 MHz bandwidth with 30 kHz subcarrier spacing, a 64-TxRU base station and a two-transmit UE operating at 31 dBm. The maximum rank is 2 with MU-MIMO.
• At 7 GHz, the bandwidth increases to 100 MHz, while the subcarrier spacing remains 30 kHz. The base station uses 256 TxRUs, and the UE still uses the same transmit power and maximum rank.

Then what happens to the maximum power reduction?

Interestingly, almost nothing changes with carrier frequency. For the compared configuration, DFT-s-OFDM requires about 5 dB of maximum power reduction, while CP-OFDM requires about 8 dB. At 256QAM, the corresponding values are about 4.5 dB and 6.5 dB, with the entry also reporting deltas of 0.5 dB and 1.5 dB. So the basic waveform advantage itself survives the move from 4 GHz to 7 GHz. The carrier frequency does not remove the lower-PAPR advantage of DFT-s-OFDM.

The same entry also reports throughput numbers, but here we have to be careful. Those numbers are not comparing DFT-s-OFDM directly against CP-OFDM. Instead, they show the throughput gain obtained by enabling UL 1024QAM relative to a 256QAM baseline, and that comparison is performed separately for each waveform. At 4 GHz, enabling 1024QAM gives a positive gain under both waveforms.

For DFT-s-OFDM, the gain ranges from about +5.38% to +11.92%. For CP-OFDM, it ranges from about +3.48% to +11.49%.

The contribution attributes part of this difference to the lower maximum power reduction of DFT-s-OFDM. So the waveform advantage appears here indirectly through the achievable transmit power.

At 7 GHz, however, the picture changes. The reported 1024QAM gain becomes negative or very small: about -3.1% to +1.75% for DFT-s-OFDM and about -5.08% to -1.14% for CP-OFDM.

Why?

The important point is that the UE transmit power remains 31 dBm, but the occupied bandwidth does not.

At 4 GHz, that power is spread over 20 MHz. At 7 GHz, it is spread over 100 MHz. So the available power per subcarrier becomes much lower.

This is the part I think matters most.

The DFT-s-OFDM PAPR advantage is still there in dB. But once the uplink becomes strongly power-limited because the same total UE power is spread over a much wider bandwidth, that backoff advantage becomes less effective in turning into higher-order modulation throughput.

So we should separate two statements very clearly: the waveform advantage survives at 7 GHz, but the throughput benefit that depends on having enough SNR may not.

• There are two gains, not one : the waveform gives 3 dB of backoff before any shaping is applied, and the shaping options later in this section come on top of it.
• The backoff advantage is carrier independent : 5 dB against 8 dB at both 4 GHz and 7 GHz, in the same entry.
• The 1024QAM gain is not carrier independent : positive at 4 GHz and negative to near zero at 7 GHz, under both waveforms.
• The gain is smallest where this page needs it most : 7 GHz is the carrier with the coverage gap, and it is also where the measured waveform benefit almost disappears.

Now let's look at the shaping itself. RAN1#126 agreed the list of uplink PAPR reduction techniques to carry forward for down-selection. All three are forms of frequency domain spectral shaping, and each one is to be studied in both a transparent and a non-transparent form.

• Option 1 is FDSS with no spectrum extension or truncation, for pi/2-BPSK and QPSK. The applicable spectral efficiency range is FFS.
• Option 2 is FDSS with spectrum extension, for pi/2-BPSK, QPSK and 16QAM. The applicable range is FFS.
• Option 3 is FDSS with spectrum truncation, for pi/2-BPSK only. The applicable range is FFS.

What is FDSS, and what separates the three options?

You may notice that all three remaining options mentioned above use the same term: FDSS.

So the difference between them is not really about choosing three different techniques. The main difference is what happens to the occupied bandwidth.

Before going into the three options, there is one distinction that is very important. FDSS is not a waveform. DFT-s-OFDM is the waveform. In the evaluation, DFT-s-OFDM is compared directly with CP-OFDM as the alternative waveform. FDSS is something added on top of DFT-s-OFDM.

How do we know this?

There are several clues in the agreement.

First, the DFT size is defined before spectrum extension or truncation is applied. This means the DFT processing has already happened before FDSS comes in.

Second, the evaluation tables compare CP-OFDM and DFT-s-OFDM as the two waveform choices.

Third, the contribution itself is about PAPR reduction for DFT-s-OFDM.

So you can think of the processing flow roughly as this: DFT-s-OFDM transform → FDSS → subcarrier mapping.

Then what exactly does FDSS do?

FDSS stands for frequency domain spectral shaping. It modifies the frequency-domain signal after the transform and before the final mapping onto subcarriers.

The basic idea is that changing the spectral shape also changes the resulting time-domain waveform. If the shaping makes the time-domain envelope flatter, the PAPR can be reduced.

Now we can look at the three options.

• Option 1 keeps the occupied bandwidth unchanged. The shaping is done inside the existing allocation. Energy is redistributed within that bandwidth, but the transmitted signal does not become wider or narrower.
• Option 2 uses spectrum extension. In this case, the shaped signal occupies more subcarriers than the original data allocation would require. The extra frequency-domain width gives more freedom for shaping and PAPR reduction.
• Option 3 uses spectrum truncation. Here, the shaped spectrum is made narrower before transmission. Some part of the spectrum generated by the shaping process is removed, so the final transmitted signal occupies fewer subcarriers.

This bandwidth difference is also reflected in the modulation ranges being considered.

Spectrum truncation is listed only for pi/2-BPSK. That makes some intuitive sense. If part of the shaped spectrum is being removed, the most robust modulation is the safest place to start.

Spectrum extension is considered up to 16QAM, while the no-bandwidth-change option covers pi/2-BPSK and QPSK. One point is easy to misunderstand here. These modulation limits are not limits of DFT-s-OFDM itself.

DFT-s-OFDM is already evaluated with much higher modulation orders. The same evaluation set includes 256QAM and even studies the gain from enabling 1024QAM. So when the FDSS options stop at 16QAM, that limitation comes from the shaping scheme under study, not from the underlying DFT-s-OFDM waveform. And even that upper limit is not final yet.

The agreement targets a down-selection of the applicable modulation at RAN1#126bis, with 16QAM specifically called out as one of the cases to decide.

There is another classification that appears together with these options: transparent and non-transparent FDSS. This distinction is mainly about the receiver side rather than the transmitter waveform itself.

All three FDSS options are listed in both transparent and non-transparent forms, and RAN1#126bis is expected to down-select between them together with the modulation choice.

There is also one terminology trap worth mentioning. The letters "SE" are used with two different meanings in the same discussion.

In phrases like "FDSS with spectrum extension" or "DFT size before SE/ST", SE means spectrum extension. But in "Applicable SE range: FFS", SE means spectral efficiency. So you have to look at the surrounding context to know which one is intended.

A few other parameters are still open as well. The condition for applying the finally selected FDSS scheme is still FFS.

For the DFT size before spectrum extension or truncation, a size of 12 × 2^x × 3^y × 5^z subcarriers is supported.

There is also another DFT-size option under consideration, with a decision targeted for RAN1#127. So at this stage, the basic structure is already clear: DFT-s-OFDM is the waveform, FDSS is an additional shaping step, and the three FDSS options mainly differ in whether the occupied bandwidth stays the same, becomes wider, or becomes narrower. The exact modulation range and receiver handling are still being narrowed down.

How do CP-OFDM, DFT-s-OFDM and FDSS compare?

At this point, three different names appear in the discussion: CP-OFDM, DFT-s-OFDM and FDSS.

But be careful. They are not three alternatives at the same level. CP-OFDM and DFT-s-OFDM are waveforms. FDSS is not a third waveform. It is an additional shaping step that can be applied on top of DFT-s-OFDM. This distinction is important because otherwise it is very easy to read the table as if all three columns were directly comparable in the same way.

The following table puts them side by side.

It shows which items belong to the waveform itself, which ones belong to the shaping step, and why some cells are naturally left empty. An empty cell does not necessarily mean that something is unsupported. In many cases, it simply means that the parameter does not apply at that level.

The two waveforms against the shaping step applied to one of them. The first four rows are relationship and capability, the next four are measurements, and the last is status. The two 1024QAM rows are measured against a 256QAM baseline, not against each other.

Then why is the FDSS column empty in the middle?

The simple reason is that the numbers are not available yet. At RAN1#126, the evaluation template for uplink PAPR reduction was agreed, and companies were asked to fill in the results afterward. So when the meeting closed, the FDSS measurement results were still being collected.

There is another point that is easy to misunderstand in the two percentage rows. A percentage gain does not mean much unless you know what the baseline is. Those rows show the gain from enabling UL 1024QAM over a 256QAM baseline. They do not show the gain of DFT-s-OFDM over CP-OFDM. The waveform is only the condition under which the 1024QAM gain was measured.

This is also why the coverage discussion should focus mainly on the maximum power reduction rows. Backoff is a waveform property, so it can affect the link budget over a wide range of operating conditions. The 1024QAM gain is different. It is mainly a high-SNR throughput result. A UE near the coverage edge may never reach the condition where 1024QAM can be used in the first place.

NOTE : the four measurement rows come from a single company entry, so they are one evaluation, not an agreed value. The coverage gap tables earlier on this page are the opposite case, because they are trimmed means across as many as twenty submissions. So treat the waveform figures as indicative and the gap figures as settled.

• Three dB is available from the waveform alone : 5 dB maximum power reduction for DFT-s-OFDM against 8 dB for CP-OFDM in one reported configuration.
• All three surviving options are FDSS : the choice is between no shaping change, spectrum extension and spectrum truncation.
• The modulation order is the open question : pi/2-BPSK is in all three options, and 16QAM only in the extension option.
• Transparent and non-transparent are both still under study : a transparent scheme needs no receiver change, which matters for early deployment.

Can a second carrier carry the uplink instead?

What if the UE can receive the 7 GHz downlink, but its uplink cannot reach the base station reliably?

One possible solution is very simple: do not force the uplink to stay on 7 GHz. The UE can transmit on another, lower-frequency carrier with better propagation while still receiving on the 7 GHz carrier. In other words, the downlink and uplink do not have to use the same carrier.

This kind of arrangement can help because the lower-frequency uplink has a better link budget, while the network can still use the wider or higher-capacity 7 GHz carrier for downlink reception. RAN1 has opened this as a study item for idle mode.

Which use cases were agreed for study?

RAN1 agreed to study three main use cases for initial access with idle-mode multi-carrier operation.

• The first one is the most obvious: uplink coverage enhancement and downlink-to-uplink coverage imbalance.
• The second one is related to RACH operation. This includes RACH capacity, traffic offloading and load balancing between carriers.
• The third one is network efficiency, especially network energy saving and reduction of common signalling.

These are the agreed starting points, but the study is not limited only to these three. Other use cases can still be considered.

There is also an important condition attached to the study.

For each use case, RAN1 has to answer one basic question: does idle-mode multi-carrier operation provide any real benefit beyond what the existing mechanisms can already do?

And if the answer is yes, under what conditions?

So the study is not simply trying to define a new feature. It first has to justify why the feature is needed at all.

Which carrier arrangements are under study?

In this case, the UE may use radio resources on a carrier different from the one where it received the system information.

Then what kind of carrier combinations should be supported?

RAN1 is studying three basic arrangements.

• S1 has one downlink physical carrier and multiple uplink carriers.
• S2 is the opposite: multiple downlink carriers with only one uplink carrier.
• S3 allows multiple carriers in both directions.

So the difference between S1, S2 and S3 is simply how many downlink and uplink carriers are involved.

You can think of them as:

• S1: 1 DL + multiple UL
• S2: multiple DL + 1 UL
• S3: multiple DL + multiple UL

• The imbalance is named as a use case in its own right : UC-1 covers uplink coverage enhancement and downlink to uplink coverage imbalance together.
• The feature has to beat what already exists : each use case is studied for additional benefit over existing mechanisms, not in isolation.
• S1 is the arrangement that matches the coverage problem : one downlink carrier with several uplink carriers lets the uplink move down in frequency by itself.
• This is idle mode work : the agreement is about initial access, which is where the Msg3 bottleneck sits.

Can better coding of small uplink control payloads help?

Uplink control usually carries only a small number of bits.

Then you may ask: if the payload is so small, why does it still create a coverage problem?

The reason is in the coding.

For very small payloads, NR uses a block code. But that code cannot simply keep lowering the code rate as much as we want. So when more protection is needed, the system has to rely on repetition. And repetition is where the cost comes from.

The same control information has to be transmitted multiple times, which uses more time-frequency resources and increases the coverage burden.

So one possible way to improve uplink control coverage is not just to add more repetition, but to use a coding scheme that can work efficiently at much lower code rates for these very small payloads.

Why is the 5G Reed-Muller code not good enough at low code rates?

The main problem starts from the mother-code length.

For the Reed-Muller code used for small control payloads in 5G NR, the mother code is limited to 32 bits. Several contributions pointed to this same limitation.

Then what happens when we need a very low code rate?

The code itself cannot simply become much longer. So the system has to rely on repetition. And this is exactly where the coverage problem starts.

Several contributions observed that, once repetition is needed, coding performance becomes worse and more resources are required. Unfortunately, small uplink control payloads of around 3 to 11 bits are often operated in exactly this low-code-rate region. So this is not a rare corner case. It is the operating point where good coverage is especially important.

A few other weaknesses were also pointed out.

For PUCCH, several contributions observed a BLER loss caused by DMRS overhead. Since the payload itself is very small, the reference-signal overhead can become a significant part of the total transmission.

High PAPR was also identified as another source of loss, again at least for PUCCH. A higher PAPR means more PA backoff, which directly hurts the uplink link budget.

Another limitation is that the current code is not well suited for DMRS-less transmission.

The reason comes from the code structure itself. The first column contains an all-one vector, which makes it difficult to separate the coded signal from an unknown channel phase without a reference signal.

So the problem is not just one thing. The short mother code forces repetition at low code rates, DMRS adds overhead, PAPR costs transmit power, and the code structure itself makes DMRS-less operation difficult.

What is the counter-argument, and how much gain is claimed?

Of course, not everybody agrees that a new code is necessary.

Several contributions point out that the Reed-Muller code already worked well enough for small payloads in 5G NR, and that 6G has not introduced any fundamentally new requirement in this payload range that would automatically justify replacing it.

There is also a complexity argument.

The current Reed-Muller code has good minimum-distance properties, and it can be decoded efficiently using fast Hadamard transform based maximum-likelihood decoding. So the question is not whether a new code can perform better. The real question is whether the gain is large enough to justify changing something that is already simple and well understood.

Then how much gain is actually being claimed?

One contribution, R1-2605288, reports that an enhanced parity-check Polar code improves BLER by about 0.6 to 0.9 dB compared with the 5G Reed-Muller code at low code rates. The same contribution translates that into more than 10% coverage improvement.

Another contribution, R1-2605909, reports a similar result: about 0.7 dB gain for the same code family at K = 8 bits and E = 256 bits.

So the claimed gain is not huge, but it is also not negligible when the whole discussion is about recovering a few dB of coverage.

Polar coding is not the only alternative being considered.

Another family is enhanced Reed-Muller, where the basic code structure is kept but the basis-sequence selection and rate matching are optimized.

So the debate is really between two directions: replace the existing code with a better low-rate code, or keep Reed-Muller and improve the way it is constructed and rate-matched.

• The limit is the mother code length of 32 : below the rate that length supports, repetition is the only tool left.
• Repetition is what costs the coverage : four sources link the degradation directly to repetition, not to the code itself.
• Enhanced Polar is claimed to give more than 10 per cent coverage : this is from one source, at low code rates, together with a 0.6 to 0.9 dB BLER gain.
• Redesign is contested : four sources argue that 6G has no new requirement here to justify replacing a 5G code that already works.

Can sparser SRS patterns improve uplink sounding coverage?

SRS has the same basic power limitation as any other uplink transmission.

The UE has only a limited total transmit power. So if that power is spread over many subcarriers, the power on each subcarrier becomes smaller.

Then what happens if the SRS pattern becomes sparser?

The same total UE power is concentrated onto fewer subcarriers. That increases the power per occupied subcarrier and makes the sounding signal easier for the base station to detect. So a sparse SRS pattern is not only a way to increase multiplexing capacity or reduce resource usage.

It can also be a coverage-enhancement technique.

This is an important point because larger comb values are often discussed mainly from the capacity side. But from the link-budget point of view, they can also provide a direct uplink coverage benefit by concentrating the UE power into fewer tones.

Which comb values are under study?

RAN1#126 agreed to look at SRS patterns that are even sparser than the current comb-8 case. The two specific values under study are comb 12 and comb 16.

Why go that sparse?

The target is not just one thing. Larger comb values may help increase SRS capacity, reduce SRS overhead and improve coverage at the same time. But once the comb becomes this sparse, several other things also have to be checked.

The study lists six main points.

One is the SRS sequence itself.

• Another is the impact on MPR and on PAPR or cubic metric.
• The maximum number of cyclic shifts also has to be reconsidered for each comb value.
• The study also has to look at the minimum usable bandwidth and which sequence can be used there.
• Channel-estimation performance is another important point, because making the pattern sparser also means observing the channel at fewer frequency-domain locations.
• And finally, the applicable RB size has to be checked as well. One example mentioned in the agreement is an RB size of 8 or more.
• So comb 12 and comb 16 are not just simple extensions of comb 8. They may improve coverage and capacity, but only if the sequence design, power behavior and channel-estimation performance still remain acceptable.

What limits and related agreements come with it?

There are a couple of important conditions attached to this agreement.

• First, comb 12 and comb 16 are the only specific values agreed for study so far. Other comb values are still FFS.
• Second, RAN1 explicitly asks for input from RAN4 on maximum power boosting.

I think this second point is especially important for the coverage discussion. A sparser comb uses fewer subcarriers. In principle, that means the UE can concentrate more of its transmit power on the subcarriers that remain. But this coverage gain is available only if the UE is actually allowed to increase the power on those tones.

So the basic idea is simple: same total power + fewer occupied subcarriers → higher power per subcarrier → potentially better SRS coverage. But the word "potentially" matters here. The actual gain depends on the maximum power boosting that RAN4 allows.

There is also a related agreement on transmission time.

Cross-slot SRS transmission is supported at least across consecutive S and U slots. This allows one SRS transmission to extend over a longer time interval.

Whether the same idea should be extended to any pair of consecutive slots, for example U + U, is still open. So there are really two ways being explored to improve SRS reach.

• One is frequency-domain concentration using a sparser comb.
• The other is time-domain extension using cross-slot transmission.

Comb 12 and comb 16 are the current candidates for the first approach, but the actual coverage gain still depends on the power-boosting limits defined by RAN4.

Can repetition close the gap, and what does it cost?

Most of the techniques discussed above try to recover a few dB without spending extra time. Repetition takes a very different approach. It simply transmits the same information again and again, so the receiver can combine the copies and accumulate more energy. So the question is not really whether repetition can close the gap. The more important question is: how much time and capacity do we have to give up to get that gain?

Let's look at the size of the problem first.

In the urban macro outdoor-to-indoor case, Msg3 PUSCH has a coverage gap of about -8.68 dB. Msg5 PUSCH is even worse, at about -13.00 dB. These are the two largest deficits in the agreed tables, and both happen on uplink data channels.

Then you may ask: how many repetitions would be needed?

The contributions do not actually specify a repetition factor, so the following numbers are just simple link-budget arithmetic, not an agreed RAN1 result.

With ideal combining, N repetitions give a gain of about 10·log10(N) dB.

This means every doubling gives roughly 3 dB.

• To recover about 8.68 dB, you need around eight transmissions.
• To recover about 13 dB, you need around twenty transmissions.

And this is still the optimistic case.

Real combining is not perfectly ideal, so the actual number of repetitions would likely be larger.

This shows the real trade-off very clearly.

Repetition is reliable because it buys coverage directly with time. But once the required repetition factor becomes large, the price is paid in latency, resource usage and cell capacity.

Repetition counts set against the urban macro outdoor-to-indoor column of the agreed gap table. The gain column is 10·log₁₀(N) with ideal combining, so every count is a floor rather than a prediction.

So this is the cost, and an operator group has already asked for it to be stated clearly. Their proposal is simple. If repetitions turn out to be needed for initial access, the number of repetitions is written into the study outcome, not left implicit. A coverage target met by twenty transmissions is not the same target as one met by a single transmission.

What has the 6G study said about it so far?

So far, repetition itself is not one of the techniques that the 6G study has chosen to take forward.

I do not think this is just an omission.

Repetition appears in the contributions behind this page more than once, but each time it appears as something whose cost has to be understood, not as the preferred solution.

One example is the operator proposal discussed above.

Another appears in the channel-coding discussion.

For small uplink control payloads, the 5G Reed-Muller mother code is limited to length 32. Once the required code rate goes lower than what that code can support directly, repetition becomes the fallback. And several contributions point out that the resulting performance and coverage loss comes from this repetition step.

So repetition is already known to work. The problem is that it works by consuming more resources. But there is one place where the study has already accepted essentially the same idea: SSB combining.

In urban macro outdoor-to-indoor, combining four SSB transmissions recovers about 3.16 dB for PSS/SSS and about 5.23 dB for PBCH.

That also uses time.

Then you may ask: why is that acceptable while uplink repetition is treated much more cautiously?

The difference is mainly in who pays the resource cost.

SSB is broadcast periodically anyway. Those transmissions happen whether one particular UE combines them or not. The UE simply waits and accumulates energy from copies that already exist.

Uplink repetition is different.

Every extra PUSCH or PUCCH transmission occupies uplink resources that the scheduler could otherwise assign to another UE. So the principle is actually the same in both cases: accumulate energy over time.

What changes is the network cost.

• For SSB combining, the main price is longer access time.
• For uplink repetition, the price is longer transmission time plus a direct loss of uplink capacity.

Where is repetition being specified, then?

The repetition mechanisms themselves are not waiting for 6G.

They are already being worked out in NR coverage enhancement, or NR CE. This is a separate NR phase 3 work item under agenda item 10.4.1, running in parallel with the 6G study. This is where the actual repetition rules are being specified.

Two RAN1#122bis agreements are especially relevant here.

The first one is about Msg3 repetition.

For PUSCH repetition scheduled by DCI 0_0 with C-RNTI, the existing Msg3 repetition rules are reused, but only for repetition type A.

This includes things like redundancy version determination and available slot determination.

The second one is about PRACH repetition.

Multiple PRACH transmissions can be distinguished either by using separate ROs or by using separate preambles within the same RO. This applies whether the repeated transmissions use the same transmit beam or different transmit beams.

Then there is one important caution.

These are NR agreements.

They are useful as a precedent, but they should not be read as something that 6G automatically inherits.

What they do show is that repetition is not just "send the same thing again." Once repetition is introduced, a number of detailed design questions immediately appear. For example, how should the uplink beam be indicated for a repeated Msg3?

So the situation is roughly this.

Repetition itself is technically straightforward because energy accumulates with every copy. The real issue is how much time and capacity the network is willing to spend.

For the agreed coverage gaps, Msg3 PUSCH is about -8.68 dB in urban macro outdoor-to-indoor, and Msg5 PUSCH is even worse at about -13.00 dB. But no agreed repetition count exists yet.

In fact, one operator proposal explicitly asks for that number to be included in the study outcome, which tells you that the count is still missing today.

Meanwhile, the 6G study is mainly looking for coverage gain somewhere else: waveform shaping, an additional uplink carrier, better coding for short control payloads, and sparser SRS patterns.

Those techniques try to improve the link itself. Repetition improves the link by spending more schedule. And the detailed repetition specification work, at least for now, is happening on the NR side under agenda item 10.4.1.

Reference

I downloaded and read thirteen of the twenty-one documents listed below: ten of the thirteen supplied for this page, both sets of draft minutes, and TR 38.901. Every RAN1#126 agreement quoted on this page, including the coverage gap tables, comes from the RAN1#126 minutes.

Three documents are listed, but I could not get them, because they are not on the 3GPP server: R1-2604037, R1-2604041 and R1-2606727. The titles of the first two come from the RAN1#125 minutes, and no title is recorded anywhere for the third. Five further documents are named inside the RAN1#126 minutes and were not opened separately: R1-2606693, R1-2606804, R1-2606880, R1-2605288 and R1-2605909.

References are listed in meeting order, earliest first, with moderator documents first within each meeting, and the specification last. The agenda item number changed during the study. RAN1#123 to RAN1#125 used 10.5.0 for general aspects and 10.5.3.2 for uplink-based CSI acquisition. RAN1#126 renumbered the study, so 10.5 is now Multi-antenna system and no separate coverage item exists. R1-2509379 sits outside the study altogether, at 10.4.1, which is the NR coverage enhancement work item.

• R1-2509379 (RAN1#123) : Discussion on coverage enhancement (DENSO CORPORATION)
• R1-2601360 (RAN1#124) : On 6GR coverage target (Vodafone, Deutsche Telekom, Orange, Bouygues Telecom, Telecom Italia, British Telecom)
• R1-2603197 (RAN1#124-bis) : Summary of [Post-124-R20-General Aspects-Coverage] (Moderator, Huawei)
• R1-2603242 (RAN1#124-bis) : Summary of [Post-124-R20-General Aspects-Coverage] (Moderator, Huawei)
• R1-2601979 (RAN1#124-bis) : Discussion on 6G SRS coverage, capacity and overhead aspect (PML)
• R1-2603085 (RAN1#124-bis) : Initial Evaluation Results on 6G Coverage (IITM, CEWiT)
• R1-2605061 (RAN1#125) : FL summary of [Post-124b-R20-General Aspects-Coverage] (Moderator, Huawei)
• R1-2604037 (RAN1#125) : Discussion on 6G SRS coverage, capacity and overhead aspect (PML)
• R1-2604041 (RAN1#125) : Discussion on 6G SRS coverage, capacity and overhead aspect (PML)
• R1-2604053 (RAN1#125) : Discussion on 6G SRS coverage, capacity and overhead aspects (PML)
• R1-2604783 (RAN1#125) : 6GR Coverage Gap Evaluations (IITM, CEWiT, Tejas Networks)
• R1-2604799 (RAN1#125) : u6GHz coverage gap and smallest max. UE bandwidth (Deutsche Telekom, Vodafone)
• Draft minutes report RAN1#125 v0.8.0 (RAN1#125) : Chairman’s notes for the meeting (3GPP RAN WG1). Source of the agreed simulation assumptions, including car penetration loss and building penetration loss
• R1-2606693 (RAN1#126) : On PAPR reduction for DFT-s-OFDM (Sony)
• R1-2606804 (RAN1#126) : Feature Lead summary #3 on 6G waveform (Moderator, Nokia)
• R1-2606880 (RAN1#126) : Moderator summary on improvement of SRS capacity and coverage: Round3 (Moderator, CATT)
• R1-2605288 (RAN1#126) : Channel coding for 6GR air interface (Huawei, HiSilicon)
• R1-2605909 (RAN1#126) : Discussion on 6G channel coding (OPPO)
• R1-2606727 (RAN1#126) : Title not recorded
• Draft minutes report RAN1#126 v0.1.0 (RAN1#126) : Chairman’s notes for the meeting (3GPP RAN WG1)
• TR 38.901 v19.4.0 (Release 19) : Study on channel model for frequencies from 0.5 to 100 GHz (3GPP). Clause 7.4.3 defines both penetration loss models the link budget uses