Threshold-based Adaptive Detection for WSN

Abstract

Efficient receiver designs for wireless sensor networks (WSNs) are becoming increasingly important. Cooperative WSNs communicated with the use of L sensors. As the receiver is constrained, it can only process U out of L sensors. Channel shortening and reduced-rank techniques were employed to design the preprocessing matrix. In this work, a receiver structure is proposed which combines the joint iterative optimization (JIO) algorithm and our proposed threshold selection criteria. This receiver structure assists in determining the optimal Uopt. It also provides the freedom to choose U<Uopt for each frame depending upon the tolerable difference allowed for mean square error (MSE). It is possible to gain in terms of complexity savings without affecting the BER performance of the system.