Coded Demixing for Unsourced Random Access
Coded Demixing for Unsourced Random Access
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DOI：
10.1109/tsp.2022.3182224
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发表时间：
2022-01-01
影响因子：
5.4
通讯作者：
Narayanan, Krishna R.
中科院分区：
文献类型：
--
作者：
Ebert, Jamison R.;Amalladinne, Vamsi K.;Narayanan, Krishna R.
无源随机接入（URA）是最近提出的一种多址接入模式，适用于机器类型通信网络的上行链路信道。通过利用URA和压缩感知之间的强连接，大规模多址接入问题可以被转换为压缩感知（CS）问题，尽管是一个非常大的维度。为了有效地处理问题的维度，编码压缩感知（CCS）已经成为一种实用的信号处理工具，当应用于URA时，以低复杂度提供良好的性能。虽然CCS在恢复相对于单个基稀疏的信号方面是有效的，但是它不能联合地恢复相对于单独的基稀疏的信号。在本文中，CCS框架被扩展到混音设置，产生了一种称为编码混音的新技术。提出了一种通用的编码解混框架，并提出了一种基于近似消息传递（AMP）的低复杂度恢复算法。编码解混被应用于异构多类URA网络和传统的单类网络。它的性能进行了分析，并提出了数值模拟，以突出编码解混的好处。
Unsourced random access (URA) is a recently proposed multiple access paradigm tailored to the uplink channel of machine-type communication networks. By exploiting a strong connection between URA and compressed sensing, the massive multiple access problem may be cast as a compressed sensing (CS) problem, albeit one in exceedingly large dimensions. To efficiently handle the dimensionality of the problem, coded compressed sensing (CCS) has emerged as a pragmatic signal processing tool that, when applied to URA, offers good performance at low complexity. While CCS is effective at recovering a signal that is sparse with respect to a single basis, it is unable to jointly recover signals that are sparse with respect to separate bases. In this article, the CCS framework is extended to the demixing setting, yielding a novel technique called coded demixing. A generalized framework for coded demixing is presented and a low-complexity recovery algorithm based on approximate message passing (AMP) is developed. Coded demixing is applied to heterogeneous multi-class URA networks and traditional single-class networks. Its performance is analyzed and numerical simulations are presented to highlight the benefits of coded demixing.