6G PHY: CSI Feedback and Channel Coding

The 3GPP has begun evaluating PHY options for waveforms, channel coding, artificial intelligence and machine learning (AI/ML), and energy efficiency for standards development, as shown in the Figure. Channel state information (CSI) feedback is a key aspect of the PHY, as this process allows the user equipment (UE) to report information on the quality of the downlink channel to the base station. Channel coding also is critical, enabling error correction by adding redundancy for reliable data transmission. Many determinations and tradeoffs remain around both CSI feedback and channel coding in 6G. Expect 6G to improve problems and inefficiencies in 5G instead of creating a revolutionary new approach. In the PHY, however, functions like CSI feedback and channel coding will vastly improve via AI/ML, increasingly large MIMO, and more power efficient approaches.

Figure. Shown is the early timeline for 3GPP 6G standardization.

CSI Feedback in 6G

To report from the UE to the network, for example, CSI feedback may involve the use of medium access control (MAC) control elements (CE) versus current 5G methods:

CSI feedback allows UEs to inform the network of the quality of the channel they are experiencing in downlink (DL), allowing for better link adaptation and beamforming at the network side. At the 6G PHY level, CSI is expected to enable advanced aspects like mMIMO, extra-large (XL-MIMO), gigantic MIMO (gMIMO), multi-user MIMO, beamforming, and overall improved spectral efficiency.

Additional 3GPP studies of CSI feedback will focus on enhancing it with AI/ML. The goal is to identify new use cases for CSI enhancements and potentially joint modulation and channel coding. This track will continue the CSI compression work done for 5G in 3GPP Release 19, which now will be part of Release 20 and continued in 6G.

How Will Channel Aging Impact Performance?

CSI feedback is subject to channel aging. In scenarios like fast-moving UEs, as CSI reports from the UE try to convey information on current channel conditions, CSI quickly becomes outdated. Such channel aging will severely reduce network performance and efficiency in mMIMO systems like 5G and 6G. CSI prediction with AI/ML tries to forecast future CSI reports based on historic reports, which allows the network to react more quickly to rapidly changing channel conditions. This work, which was introduced in 5G, will likely be continued and enhanced in 6G. Predicting how the channel will evolve enables the CSI to stay fresh even in dynamic conditions.

Expect a simplification of the CSI feedback reporting framework in 6G. One area under heavy discussion for the standards is moving all reporting schemes first to MAC control. This approach presents a simpler reporting mechanism than the one used in 5G to reduce complexity.

In investigations of MAC CE vs. 5G CSI feedback, another 5G problem arises that the industry would like to solve: the very complicated 5G CSI framework configuration. Continued specification evolutions to CSI report content in successive 5G releases created this complex configuration. If this CSI framework can be simplified, it will accelerate innovation and reduce development cycles. One proposed approach for 6G is to send control channel feedback via MAC CEs instead of PUCCH or UCI multiplexing of PUSCH schemes, as defined in 5G.

What Is the Role of Channel Coding in 6G?

Channel coding enables error correction by adding redundancy for reliable data transmission. Although channel coding will be modified for 6G, assume that it will use the same baseline used in 5G:

Since 5G’s deployment, minor tweaks have been proposed to make implementation of the decoders more efficient and enable support of higher throughputs. For 6G, expect to see those improvements adopted and reflected in the specification. The goal is to have an LDPC decoder and polar decoder that can be more easily implemented, which in turn provides more power efficiency, lower latency, and less computational complexity.

Goals for Channel Coding and Modulation

Engineers are evaluating several techniques involving waveform, channel coding, and modulation enhancements. In addition to improving reliability and uplink (UL) coverage, which are major 5G pain points, these improvements target power efficiency. The goal is to reduce the peak to average power of the generated waveform. In terms of energy efficiency, the 3GPP is considering a more end-to-end approach for both network and user equipment for 6G. This approach deviates from 5G, where network power efficiency was considered very late in the release cycle and not an integral part of the design from day 1.

Network power saving is a known weak area for 5G, so addressing it is not surprising. When power consumption is considered from the beginning and end to end, engineers can achieve a reduction even with more complexity in some parts of the system. Further reductions could be gained in other parts of the system via better coverage, enabling transmission with less power.

Do not expect the development of new channel coding schemes. 6G will most likely use current coding schemes with minor adaptations. However, new approaches to joint channel coding and modulation may provide measurable gains in power efficiency. Anticipate different options for power efficiency being evaluated for inclusion in the standard from 6G inception throughout the system.

With each new cellular generation, the industry can change channel coding algorithms. A new channel coding scheme could increase 6G spectral efficiency and data rates, reduce latency and energy consumption, and enable support for AI-native semantic communications. Research is underway to evaluate different channel coding algorithms using LDPC and polar coding as a baseline. New approaches, possibly using AI/ML, could give rise to improved performance across existing 5G use cases as well as new use cases supported in 6G. Research in this area will focus on evaluating different channel coding algorithms in a range of environments and assessing the benefits of AI/ML models.

You can use Keysight digital twins to support simulation of the PHY and MAC layers, integrate site-specific channel models, and simulate channel coding performance. Digital twins also have a role in CSI reporting, supporting ways to characterize latency’s impact versus the benefits of these new CSI reporting framework ideas.

To find out more about how the 6G PHY is evolving and the key use cases, tradeoffs, and technologies influencing it, download the eBook, 6G Research and Innovation: From 0 to PHY and Beyond. For more information on 6G trends and developments, check out the following resources.

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