Grant-free Multi-User Communication in IoT Based on an Improved Greedy Reconstruction Algorithm
This article proposes a Compress Sensing based Multi-User Detection(CS-MUD)technology in grant-free Non-Orthogonal Multiple Access(NOMA)uplink transmission system to meet the needs of massive Machine Type Communications(mMTC)scenarios with large number of connections and information requirement in 5G.To meet the requirement of low overhead and low latency and to improve the reconstruction efficiency and reconstruction accuracy of the traditional Multi-User Detection(MUD)algorithm,this paper proposes a Dice-based Backtracking Orthogonal Matching Pursuit Multi-User Detection(DBOMP-MUD)algorithm.This proposed method first uses a Dice coefficient instead of atomic inner product for correlation calculation from matching criteria in atom pre-selec-tion stage.Secondly,backtracking is used to determine the atoms that minimizes the residual;finally,in each iteration.Regularization is adopted to find several atoms,which can balance reconstruction accuracy and efficiency.Simulation results show that the DBOMP-MUD algorithm proposed in this article takes into account both performance and efficiency during signal reconstruction.In the NOMA uplink transmission system reconstruction experiment,compared with the traditional CS-MUD algorithm,the signal-to-noise ratio gain can reach 1 dB,verifying the superiority of the proposed algorithm in NOMA uplink transmission system.Therefore,the proposed scheme can better meet the transmission delay and detection performance requirements in the practical mMTC.
国家科技期刊平台
NSTL
万方数据
