Nonlinear Channel Estimation Issues in Cooperative Sensor MIMO

Abstract

Abstract-A cooperative MIMO system for range extension in sensor networks is considered. A local sensor group forms a consensus and seeks to transmit a common pool of data to a stand-off multi-element collector. Each sensor then transmits one column of an orthogonal space-time block code (OSTBC). The resulting increased effective power and diversity can yield substantial range increases for moderate numbers of sensors. The major problem is tracking the individual sensor frequency offsets, delays and sensor-to-collector channels under high mobility. The unscented Kalman filter (UKF) is presented as a state of the art solution to the cooperative MIMO channel estimation problem, and its performance is evaluated via a hybrid analysis/simulation of bit-error rate. A hardware implementation of the collector is also discussed based on simplified correlation and homodyne estimation strategies. The homodyne estimator performance is finally compared to that of previous generalized successive interference cancellation (GSIC) and correlation-based algorithms via simulation.