Distributed Basis Pursuit

作者：Mota Joao F C^*; Xavier Joao M F; Aguiar Pedro M Q; Pueschel Markus

来源：IEEE Transactions on Signal Processing, 2012, 60(4): 1942-1956.

DOI：10.1109/TSP.2011.2182347

• Augmented Lagrangian
• basis pursuit (BP)
• distributed optimization
• sensor networks

We propose a distributed algorithm for solving the optimization problem Basis Pursuit (BP). BP finds the least l(1)-norm solution of the underdetermined linear system Ax = b and is used, for example, in compressed sensing for reconstruction. Our algorithm solves BP on a distributed platform such as a sensor network, and is designed to minimize the communication between nodes. The algorithm only requires the network to be connected, has no notion of a central processing node, and no node has access to the entire matrix A at any time. We consider two scenarios in which either the columns or the rows of A are distributed among the compute nodes. Our algorithm, named D-ADMM, is a decentralized implementation of the alternating direction method of multipliers. We show through numerical simulation that our algorithm requires considerably less communications between the nodes than the state-of-the-art algorithms.

• 出版日期2012-4