Multi-subspace pursuit algorithm based on body area network

Abstract

Wireless body area networks (WBANs) provide a tremendous opportunity for remote health monitoring. However, the design of WBAN health monitoring system encounters a number of challenges including the process of the biomedical information. In this paper, we give an overview of the results of a special joint sparse model (JSM), JSM-2, in body area networks. We present JSM-2 for the signal groups that each signal has a common K-sparse characteristic although the biomedical signal groups are not all sparse signals. The reconstruction algorithm, multi-subspace pursuit algorithm, is proposed based on JSM-2. The algorithm combines the advantages of the previous study of the one-step greedy algorithm (OSGA) and simultaneous orthogonal matching pursuit (SOMP). Furthermore, the proposed algorithm not only performs better in sparse reconstruction performance than OSGA, but also needs less calculation than SOMP. The performance is evaluated through numerical simulations.

Keywords:

• wireless body area network
• distributed compressed sensing
• joint sparse model
• multi-subspace pursuit algorithm
• one-step greedy algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61074165], [grant number 61273064].