关键词：传感器网络；通信资源重构；稀疏信号
摘 要：In this chapter, we consider the problem of reconstructing time-varying sparse signals in a sensor network with limited communication resources. In each time interval, the fusion center transmits the predicted signal estimate and its corresponding error covariance to a selected subset of sensors. The selected sensors compute quantized innovations and transmit them to the fusion center. We consider the situation where the signal is sparse, i.e., a large fraction of its components is zero-valued. We discuss algorithms for signal estimation in the described scenario, analyze their complexity, and demonstrate their near-optimal performance even in the case where sensors transmit a single bit (i.e., the sign of innovation) to the fusion center.