SIMO-NOMA系统分步多用户检测策略

上行免调度非正交多址接入（NOMA）系统中，针对低信噪比情况下通过压缩感知技术联合检测活跃用户和数据的误码率性能比较差的问题，提出了分步多用户检测策略。该策略考虑信号的稀疏度对系统检测性能的影响，理论分析得出了检测成功概率的下界，以降低稀疏度来提高重构概率；结合压缩感知硬融合算法（CS-HFA），对稀疏信号进行二次筛选，最终实现信号的精确检测。仿真结果表明，随着信噪比、活跃用户数或者过载率的改变，改进方案表现出较好的系统检测性能。

Substep multi-user detection strategy for SIMO-NOMA systems

To improve the performance of the compressive sensing technique-based active user detection under low signal-to-noise ratio(SNR) and the bite error rate(BER) in uplink grant-free Non-orthogonal Multiple Access(NOMA) systems,a substep multi-user detection strategy is proposed.Specifically,the impact of signal sparsity on the system detection performance is considered in the proposed strategy,and the lower bound of detection success probability is derived.Meanwhile,the probability of the reconstruction is improved by reducing the sparsity.After that,the spare signals are secondary screened by combining the Compressive Sensing-based Hard Fusion Algorithm(CS-HFA) so as to realize the accurate detection of the signals.Simulation results show that the proposed scheme can achieve a good performance with the change of SNR,the number of active users,or overload rate.