Grant-Free Non-Orthogonal Multiple Access for IoT: A Survey
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TL;DR: Various grant-free NOMA schemes are presented, their potential and related practical challenges are highlighted, and possible future directions are thoroughly discussed at the end.
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Abstract: Massive machine-type communications (mMTC) is one of the main three focus areas in the 5th generation (5G) of wireless communications technologies 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 channel resources and orthogonal resource allocation techniques, users get a transmission slot by making scheduling/connection requests. The involved control channel signaling, negligible with respect to the huge transmit data, is not a major issue. However, this may turn into a potential performance bottleneck in mMTC, where huge number of devices transmit short packet data in a sporadic way. To tackle the limited radio resources and massive connectivity challenges, non-orthogonal multiple access (NOMA) has emerged as a promising technology that allows multiple users to simultaneously transmit their data over the same channel resource. This is achieved by employing user-specific signature sequences at the transmitting devices, which are exploited by the receiver for multi-user data detection. Due to its massive connectivity potential, NOMA has also been considered to enable grant-free transmissions especially in mMTC, where devices can transmit their data whenever they need without the scheduling requests. The existing surveys majorly discuss different NOMA schemes, and exploit their potential, in typical grant-based HTC scenarios, where users are connected with the base station, and various system parameters are pre-defined in the scheduling phase. Different from these works, this survey provides a comprehensive review of the recent advances in NOMA from a grant-free connectivity perspective. Various grant-free NOMA schemes are presented, their potential and related practical challenges are highlighted, and possible future directions are thoroughly discussed at the end.
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References
•Posted Content
Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO
Zhen-Qing He,Xiaojun Yuan +1 more
TL;DR: In this article, the authors considered the problem of channel estimation for large intelligent metasurface (LIM) assisted massive MIMO systems and proposed a two-stage algorithm that includes a sparse matrix factorization stage and a matrix completion stage.
161
Hybrid Random Access and Data Transmission Protocol for Machine-to-Machine Communications in Cellular Networks
TL;DR: This work derives a closed-form analytic formula for the M2M traffic throughput and proposes a joint adaptive resource allocation and access barring scheme based on the analytic results and shows that the proposed scheme exhibits a near-optimal performance in terms of the capacity.
159
FASA: accelerated S-ALOHA using access history for event-driven M2M communications
TL;DR: Simulation results demonstrate that under highly bursty traffic, the proposed FASA scheme outperforms traditional additive schemes such as PB-ALOHA and achieves near-optimal performance in reducing access delays and compared to multiplicative schemes, FasA shows its robustness under heavy traffic load in addition to better delay performance.
158
DeepNOMA: A Unified Framework for NOMA Using Deep Multi-Task Learning
TL;DR: Deep multi-task learning is resorted for end-to-end optimization of NOMA, by regarding the overlapped transmissions as multiple distinctive but correlated learning tasks, which makes DeepNOMA a universal transceiver optimization approach.
157
V2X Meets NOMA: Non-Orthogonal Multiple Access for 5G-Enabled Vehicular Networks
TL;DR: In this article, the authors investigated the applicability of NOMA in supporting cellular V2X services to achieve low latency and high reliability in the conventional OFDM-based LTE network.
156