Multi-subspace pursuit algorithm based on body area network

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.