Grant-free Non-orthogonal Multiple Access for IoT: A Survey
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Abstract (arXiv)
Massive machine-type communications (mMTC) is one of the main three focus areas in the 5th generation (5G) of mobile standards to enable connectivity of a massive number of internet of things (IoT) devices with little or no human intervention. In conventional human-type communications (HTC), due to the limited number of available radio resources and orthogonal/non-overlapping nature of existing resource allocation techniques, users need to compete for connectivity through a random access (RA) process, which may turn into a performance bottleneck in mMTC. In this context, non-orthogonal multiple access (NOMA) has emerged as a potential technology that allows overlapping of multiple users over a radio resource, thereby creating an opportunity to enable more autonomous and grant-free communication, where devices can transmit data whenever they need. The existing literature on NOMA schemes majorly considers centralized scheduling based HTC, where users are already connected, and various system parameters like spreading sequences, interleaving patterns, power control, etc., are predefined. Contrary to HTC, mMTC traffic is different with mostly uplink communication, small data size per device, diverse quality of service, autonomous nature, and massive number of devices. Hence, the signaling overhead and latency of centralized scheduling becomes a potential performance bottleneck. To tackle this, grant-free access is needed, where mMTC devices can autonomously transmit their data over randomly chosen radio resources. This article, in contrast to existing surveys, comprehensively discusses the recent advances in NOMA from a grant-free connectivity perspective. Moreover, related practical challenges and future directions are discussed.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2019.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 3; 2025: 2.
12 papers.
- 2022Towards Semantic Communication Protocols: A Probabilistic Logic Perspectivecited by 10
- 2024Modulation and Coding for NOMA and RSMAcited by 4
- 2023Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communicationscited by 3
- 2021DeepMuD: Multi-user Detection for Uplink Grant-Free NOMA IoT Networks via Deep Learningcited by 1
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systemscited by 1
- 2022Joint User and Data Detection in Grant-Free NOMA with Attention-based BiLSTM Networkcited by 0
- 2022TinyQMIX: Distributed Access Control for mMTC via Multi-agent Reinforcement Learningcited by 0
- 2023Deep Reinforcement Learning for Uplink Scheduling in NOMA-URLLC Networkscited by 0
- 2024Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communicationcited by 0
- 2024Deep Learning-Based Approach for User Activity Detection with Grant-Free Random Access in Cell-Free Massive MIMOcited by 0
- 2025Robust Learning-Based Sparse Recovery for Device Activity Detection in Grant-Free Random Access Cell-Free Massive MIMO: Enhancing Resilience to Impairmentscited by 0
- 2025Lightweight Learning for Grant-Free Activity Detection in Cell-Free Massive MIMO Networkscited by 0
- 2025Lightweight Learning for Grant-Free Activity Detection in Cell-Free Massive MIMO Networks14 Mar 2025
- 2025Robust Learning-Based Sparse Recovery for Device Activity Detection in Grant-Free Random Access Cell-Free Massive MIMO: Enhancing Resilience to Impairments13 Mar 2025
- 2024Modulation and Coding for NOMA and RSMA30 Sep 2024
- 2024Deep Learning-Based Approach for User Activity Detection with Grant-Free Random Access in Cell-Free Massive MIMO11 Jun 2024
- 2024Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication12 Mar 2024
- 2023Deep Reinforcement Learning for Uplink Scheduling in NOMA-URLLC Networks28 Aug 2023
- 2023Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications2 Jan 2023
- 2022TinyQMIX: Distributed Access Control for mMTC via Multi-agent Reinforcement Learning21 Nov 2022
- 2022Joint User and Data Detection in Grant-Free NOMA with Attention-based BiLSTM Network14 Sep 2022
- 2022Towards Semantic Communication Protocols: A Probabilistic Logic Perspective8 Jul 2022
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systems21 Jun 2021
- 2021DeepMuD: Multi-user Detection for Uplink Grant-Free NOMA IoT Networks via Deep Learning18 Feb 2021