论文标题
用于通过外代码进行耦合的编码压缩传感的混合方法
A Hybrid Approach to Coded Compressed Sensing where Coupling Takes Place via the Outer Code
论文作者
论文摘要
本文旨在推进编码的压缩传感（CCS），作为未包含随机访问的实用方案。原始CCS算法具有串联结构，其中内部代码由支持恢复任务，外部树代码会进行消息歧义。最近，建立了CCS与稀疏回归代码之间的链接，从而将近似消息传递（AMP）应用于CCS。随后，通过通过动态的Denoiser整合放大器和信念在外代码上的信念传播来加强这种联系。沿着这些线路，这项工作表明了块对角线传感矩阵如何类似于传统CC中使用的矩阵，以及上述动态denoiser，是一种有效的手段，可以在低复杂性下获得良好的性能。这种新颖的结构可用于将此方案扩展到以前不切实际的维度。调查结果由数值模拟支持。
This article seeks to advance coded compressed sensing (CCS) as a practical scheme for unsourced random access. The original CCS algorithm features a concatenated structure where an inner code is tasked with support recovery, and an outer tree code conducts message disambiguation. Recently, a link between CCS and sparse regression codes was established, leading to the application of approximate message passing (AMP) to CCS. This connection was subsequently strengthened by integrating AMP and belief propagation on the outer code through a dynamic denoiser. Along these lines, this work shows how block diagonal sensing matrices akin to those used in traditional CCS, together with the aforementioned dynamic denoiser, form an effective means to get good performance at low-complexity. This novel architecture can be used to scale this scheme to dimensions that were previously impractical. Findings are supported by numerical simulations.
