Modulation and Coding for NOMA and RSMA
Not on the map. Why?
Abstract (arXiv)
Next-generation multiple access (NGMA) serves as an umbrella term for transmission schemes distinct from conventional orthogonal methods. A key candidate of NGMA, non-orthogonal multiple access (NOMA), emerges as a solution to enhance connectivity by allowing multiple users to share time, frequency, and space concurrently. However, NOMA faces challenges in implementation, particularly in canceling inter-user interference. In this paper, we discuss the principles behind NOMA and review conventional NOMA methods. Then, to address these challenges, we present asynchronous transmission and interference-aware modulation techniques, enabling decoding without successive interference cancellation. The goal is to design constellations that dynamically adapt to interference, minimizing bit error rates (BERs) and enhancing user throughput in the presence of inter-user, inter-carrier, and inter-cell interference. The traditional link between minimizing BER and increasing spectral efficiency is explored, with deep autoencoders for end-to-end communication emerging as a potential solution to improve BERs. Interference-aware modulation can revolutionize constellation design for non-orthogonal channels. Rate-splitting multiple access (RSMA) is another promising interference management technique in multi-user systems. In addition to addressing challenges in finite-alphabet NOMA, this paper offers new insights and provides an overview of code-domain NOMA, trellis-coded NOMA, and RSMA as key NGMA candidates. We also discuss the evolution of channel coding toward low-latency communication and examine modulation and coding schemes in 5G networks. Finally, we highlight future research directions, emphasizing their importance for realizing NOMA from concept to functional technology.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 49 of its 288 references that are in the map. First posted on arXiv 30 Sep 2024.
Builds on
49 of 288 references.
References · 49
- 2017An Introduction to Deep Learning for the Physical Layercited by 227
- 2017Over the Air Deep Learning Based Radio Signal Classificationcited by 121
- 2023On the Road to 6G: Visions, Requirements, Key Technologies and Testbedscited by 75
- 2019Machine Learning in IoT Security: Current Solutions and Future Challengescited by 25
- 2022Distributed Deep Joint Source-Channel Coding over a Multiple Access Channelcited by 16
- 2019Robust and Fast Automatic Modulation Classification with CNN under Multipath Fading Channelscited by 14
- 2022An Overview of 5G Advanced Evolution in 3GPP Release 18cited by 14
- 2021TeraHertz Band Communication: An Old Problem Revisited and Research Directions for the Next Decadecited by 13
- 2019Grant-free Non-orthogonal Multiple Access for IoT: A Surveycited by 12
- 2022Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trendscited by 11
- 2016Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challengescited by 10
- 2019Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel with Partial CSIT: A Rate-Splitting Approachcited by 5
37 more
- 2021Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6Gcited by 5
- 2021SVD-Embedded Deep Autoencoder for MIMO Communicationscited by 5
- 2023A Weighted Autoencoder-Based Approach to Downlink NOMA Constellation Designcited by 5
- 2016Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolutioncited by 4
- 2019Millimeter-Wave NOMA with User Grouping, Power Allocation and Hybrid Beamformingcited by 4
- 2020Benchmarking End-to-end Learning of MIMO Physical-Layer Communicationcited by 4
- 2022Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMOcited by 4
- 2020Rate-Splitting Multiple Access for Multi-antenna Downlink Communication Systems: Spectral and Energy Efficiency Tradeoffcited by 3
- 2020On the Downlink Performance of RSMA-based UAV Communicationscited by 3
- 2021Rate-Splitting Multiple Access for Multi-Antenna Joint Radar and Communicationscited by 3
- 2021Deep Learning-based Codebook Design for Code-domain Non-Orthogonal Multiple Access Approaching Single-User Bit Error Rate Performancecited by 3
- 2022Rate-Splitting Multiple Access for Uplink Massive MIMO With Electromagnetic Exposure Constraintscited by 3
- 2023Interference-Aware Constellation Design for Z-Interference Channels with Imperfect CSIcited by 3
- 2023Deep Reinforcement Learning for Interference Management in UAV-based 3D Networks: Potentials and Challengescited by 3
- 2019Power Allocation in Cache-Aided NOMA Systems: Optimization and Deep Reinforcement Learning Approachescited by 2
- 2020Rate Splitting for Multi-Antenna Downlink: Precoder Design and Practical Implementationcited by 2
- 2020Multi-Objective DNN-based Precoder for MIMO Communicationscited by 2
- 2023Deep Polar Codescited by 2
- 2023Deep Autoencoder-based Z-Interference Channels with Perfect and Imperfect CSIcited by 2
- 2019Energy Efficiency of RSMA and NOMA in Cellular-Connected mmWave UAV Networkscited by 1
- 2019Downlink Non-Orthogonal Multiple Access without SIC for Block Fading Channels: An Algebraic Rotation Approachcited by 1
- 2019Low-Resolution Limited-Feedback NOMA for mmWave Communicationscited by 1
- 2019MmWave Amplify-and-Forward MIMO Relay Networks with Hybrid Precoding/Combining Designcited by 1
- 2019Trellis-Coded Non-Orthogonal Multiple Accesscited by 1
- 2021Globally Optimal Beamforming for Rate Splitting Multiple Accesscited by 1
- 2021Rate-Splitting Multiple Access for Downlink Multiuser MIMO: Precoder Optimization and PHY-Layer Designcited by 1
- 2021Downlink MIMO-RSMA with Successive Null-Space Precodingcited by 1
- 2021QoS-aware User Grouping Strategy for Downlink Multi-Cell NOMA Systemscited by 1
- 2021Rate-Splitting Multiple Access for Downlink MIMO: A Generalized Power Iteration Approachcited by 1
- 2021Secure Precoding in MIMO-NOMA: A Deep Learning Approachcited by 1
- 2021Signaling Design for MIMO-NOMA with Different Security Requirementscited by 1
- 2022Transmission Scheme, Detection and Power Allocation for Uplink User Cooperation with NOMA and RSMAcited by 1
- 2022Precoding and Decoding Schemes for Downlink MIMO-RSMA with Simultaneous Diagonalization and User Exclusioncited by 1
- 2022Outage Performance of Uplink Rate Splitting Multiple Access with Randomly Deployed Userscited by 1
- 2022K-Receiver Wiretap Channel: Optimal Encoding Order and Signaling Designcited by 1
- 2023Multicarrier Rate-Splitting Multiple Access: Superiority of OFDM-RSMA over OFDMA and OFDM-NOMAcited by 1
- 2023Fairness Optimization of RSMA for Uplink Communication based on Intelligent Reflecting Surfacecited by 1
Built on by
Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025Interference-Aware Super-Constellation Design for NOMAcited by 1
- 2026End-to-End NOMA with Perfect and Quantized CSI Over Rayleigh Fading Channelscited by 0
- 2026Deep Learning-Based Multi-User Communication Design for Dense IoT Networks: Interference-Aware Finite-Blocklength Communication and Preliminary MIMO Extensionscited by 0
- 2026Quantum-Aided Active Device Detection in Energy-Harvesting Symbiotic Radio Networkscited by 0
- 2026Quantum-Aided Active Device Detection in Energy-Harvesting Symbiotic Radio Networks22 Sep 2026
- 2026Deep Learning-Based Multi-User Communication Design for Dense IoT Networks: Interference-Aware Finite-Blocklength Communication and Preliminary MIMO Extensions24 Aug 2026
- 2026End-to-End NOMA with Perfect and Quantized CSI Over Rayleigh Fading Channels13 Feb 2026
- 2025Interference-Aware Super-Constellation Design for NOMA10 Mar 2025