Multi-Processor Approximate Message Passing Using Lossy Compression

In this paper, a communication-efficient multi-processor compressed sensing framework based on the approximate message passing algorithm is proposed. We perform lossy compression on the data being communicated between processors, resulting in a reduction in communication costs with a minor degradation in recovery quality. In the proposed framework, a new state evolution formulation takes the quantization error into account, and analytically determines the coding rate required in each iteration. Two approaches for allocating the coding rate, an online back-tracking heuristic and an optimal allocation scheme based on dynamic programming, provide significant reductions in communication costs.

• Type: Journal
• Year: 2016
• Where: CORR
• Authors: Puxiao Han, Junan Zhu, Ruixin Niu, Dror Baron
• Keywords: CORR 2016, Education