Adaptive Signal Combining and Detection in Cooperative Wireless Networks

In this research adaptive algorithms were developed for multiuser detection and signal combining in cooperative wireless networks. Some of the key contributions and works of this research thesis are: 1. A computationally simple Adaptive Minimum Mean Square Error Multiuser Detection scheme was proposed to eliminate multiple access interference in uplink communication of an asynchronous cooperative CDMA wireless network, where users cooperate in a relaying mode while they exchange data and channel information with the destination node. The proposed scheme provides better interference resistance than optimum multiuser detection Maximum Likelihood Sequence Estimation in cooperative wireless networks. The performance was examined under Amplify-and-Forward and Decode-and-Forward cooperative protocols in flat fading Rayleigh wireless channels. 2. Adaptive signal combining was proposed for cooperative wireless networks and its performance was analysed by using Least Mean Square and Recursive Least Square algorithms. The other classical non-adaptive techniques Maximal Ratio Combining and Wiener were also examined. It was also shown that adaptive signal combining achieves Wiener’s solution in cooperative wireless networks with added benefit of computational simplicity over classical combining schemes. 3. Weighted Least Square Error Method of signal combining was proposed for wireless signal combining, where estimates of inverse of the channel noise variance was used as weight of the combiner. The proposed method was a receiver with noise estimation filters at each received branch for the