ABSTRACT
Adaptive wireless channel identification is typically utilized when simpler techniques for received sequence detection cannot be used in telecommunication systems. This chapter presents a comparative performance study of computational complexity, mean square error, and convergence time for four adaptive blind identification methods of wireless channel. The adaptive wireless channel identification architecture is utilized for four adaptive algorithms: least mean square (LMS), normalized least mean square (NLMS), recursive least square (RLS), and affine projection (AFP). A wireless communication system transmits information through wireless channels. A mathematical model is constructed to reflect the most important characteristics of the transmission channel. This mathematical model is the prelude of the channel's simulation using MATLAB tool. Improving the current state of adaptive algorithmic aspect of wireless channel, for the next-generation 5G channel model, a novel breakthrough of emerging techniques is needed.
