ADAPTIVE SYSTEMS
Richard W. Middlestead · 2017
In this chapter, the mathematical background and algorithms are developed for adaptive systems as they apply to waveform equalization of intersymbol interference (ISI), cancellation of interfering signals, and waveform identification. It introduces the orthogonality principle and applies in the derivation of Weiner's optimum linear estimation filter. The chapter examines the optimum finite impulse response (FIR) filter, with the tap weights adaptively estimated using the lease mean-square (LMS) algorithm. The LMS algorithm results in lower implementation complexity than the minimum mean-square error (MMSE) algorithm. The chapter considers various forms of equalizers and discusses adaptive interference cancellation using the LMS algorithm. The recursive least-squares (RLS) algorithm converges to the steady-state condition in considerably less time than that of the MMSE or LMS algorithms. The chapter gives case studies involving the application of ISI equalization and narrowband interference cancellation and concludes with a case study of the RLS-adaptive equalizer.