Sensor grouping for linear distributed estimation in a wireless sensor network

This paper is concerned with distributed estimation of a scalar parameter using a wireless sensor network (WSN) that employs a large number of sensors operating under limited bandwidth resource. A semi-orthogonal multiple-access channel (MAC), which provides transmission of observations from K sensors to a fusion center (FC) via N (N ≤ N) orthogonal channels, is studied. The K sensors are divided into N groups, where the sensors in each group simultaneously transmit on one orthogonal channel (and hence the transmitted signals are directly superimposed at the FC as opposed to being coherently combined). Two versions of the semi-orthogonal MAC are developed and analyzed in detail: fixed sensor grouping and adaptive sensor grouping. Both versions are shown to outperform the orthogonal MAC, especially the one with adaptive sensor grouping. In fact, the semi-orthogonal MAC with adaptive sensor grouping is shown to perform very close to that of the hybrid MAC, while requiring much smaller amount of feedback.