A Novel NOMA-Enhanced SDT Scheme for NR RedCap in 5G/B5G Systems

Zhenjiang Shi, Jiajia Liu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Recently, Reduced Capability (RedCap) New Radio (NR) User Equipment (UE), which has smaller cost, lower complexity, and longer battery life than normal NR UE, was introduced by 3GPP in R17. In particular, the UE energy consumption is an important metric of interest. Small Data Transmission (SDT) technology has been proposed by 3GPP to save UE power, which allows UEs to directly transmit small-sized uplink payloads in Inactive state without transitioning to Connected state. However, for a large number of RedCap UEs with bursty traffic, how to minimize UE energy consumption while ensuring the reliability of uplink payload transmission is still a challenge. Towards this end, we propose a novel Non-Orthogonal Multiple Access (NOMA)-enhanced SDT scheme to tackle this challenge. Considering that the power level pool is an important component of NOMA to achieve performance gains and the power level pool design problem in multi-cell scenarios is still rarely studied, we present a Multi-Agent Dueling Double Deep Q Network (MAD3QN)-based algorithm to further improve the performances of the proposed scheme by optimizing the power level pool for each gNB with practical imperfect Successive Interference Cancellation (SIC). Extensive numerical comparisons among the proposed scheme and multiple benchmarks show that the proposed scheme (with appropriate user pairing) can significantly improve the transmission reliability of large-scale RedCap UEs with a small cost of energy consumption.

Original languageEnglish
Pages (from-to)3190-3204
Number of pages15
JournalIEEE Transactions on Wireless Communications
Volume23
Issue number4
DOIs
StatePublished - 1 Apr 2024

Keywords

  • RedCap UE
  • imperfect successive interference cancellation
  • multi-agent reinforcement learning
  • non-orthogonal multiple access
  • small data transmission

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