A vast population of low-cost low-power transmitters sporadically sending small amounts of data over a common wireless medium is one of the main scenarios for Internet of things (IoT) data communications. At the medium access, the use of grant-free solutions may be preferred to reduce overhead even at the cost of multiple-access interference. Unsourced multiple access (UMA) has been recently established as relevant framework for energy efficient grant-free protocols. The use of a compressed sensing (CS) transmission phase is key in one of the two main classes of UMA protocols, yet little attention has been posed to sparse greedy algorithms as orthogonal matching pursuit (OMP) and its variants. We analyze their performance and provide relevant guidance on how to optimally setup the CS phase. Minimum average transmission power and minimum number of channel uses are investigated together with the performance in terms of receiver operating characteristic (ROC). Interestingly, we show how the basic OMP and generalized OMP (gOMP) are the most competitive algorithms in their class.

翻译：大量低成本、低功耗的发射器零星地通过公共无线媒介发送少量数据，是物联网数据通信的主要场景之一。在媒体接入中，即使以多址接入干扰为代价，也倾向于采用免授权方案以减少开销。无源多址接入（UMA）近期已被确立为节能免授权协议的相关框架。在UMA协议的两大类中，压缩感知（CS）传输阶段是关键组成部分，然而对稀疏贪婪算法（例如正交匹配追踪（OMP）及其变体）的关注仍显不足。我们分析了这些算法的性能，并就如何最优设置CS阶段提供了相关指导。研究了最小平均发射功率和最小信道使用次数，同时基于接收机工作特性（ROC）评估了性能。有趣的是，我们发现基础OMP和广义OMP（gOMP）是其类别中最具竞争力的算法。