非协调多址接入的编码压缩感知方案
A Coded Compressed Sensing Scheme for Uncoordinated Multiple Access
摘要：
本文介绍了一种新的通信方案，称为编码压缩感知，无源多址通信。所提出的分而治之的方法利用压缩感知和前向纠错的最新进展，产生一种新的非协调访问范式，以及计算效率高的解码算法。在此框架内，每个活动设备将其数据划分为几个子块，随后使用系统线性块码添加冗余。然后采用压缩感知技术来恢复子块直到它们的顺序的置换，并且通过使用基于树的算法将片段拼接在一起来获得原始消息。这种访问模式的错误概率和计算复杂性的特点。一个优化框架，它利用性能和计算复杂度之间的权衡，开发分配奇偶校验位的每个子块。此外，两个象征性的奇偶校验比特分配策略进行了检查，并分析了其性能的限制，作为活动用户的数量和相应的有效载荷趋于无穷大。所需的信道使用的数量和与这些分配策略相关联的计算复杂性建立了各种缩放制度。数值结果表明，编码压缩感知优于其他现有的实际访问策略在一系列的操作场景。
英文摘要：
This article introduces a novel communication scheme, termed coded compressed sensing, for unsourced multiple-access communication. The proposed divide-and-conquer approach leverages recent advances in compressed sensing and forward error correction to produce a novel uncoordinated access paradigm, along with a computationally efficient decoding algorithm. Within this framework, every active device partitions its data into several sub-blocks and, subsequently, adds redundancy using a systematic linear block code. Compressed sensing techniques are then employed to recover sub-blocks up to a permutation of their order, and the original messages are obtained by stitching fragments together using a tree-based algorithm. The error probability and computational complexity of this access paradigm are characterized. An optimization framework, which exploits the tradeoff between performance and computational complexity, is developed to assign parity-check bits to each sub-block. In addition, two emblematic parity bit allocation strategies are examined and their performances are analyzed in the limit as the number of active users and their corresponding payloads tend to infinity. The number of channel uses needed and the computational complexity associated with these allocation strategies are established for various scaling regimes. Numerical results demonstrate that coded compressed sensing outperforms other existing practical access strategies over a range of operational scenarios.
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