Digital Communications with Emphasis on Data Modems

12ADAPTIVE SYSTEMS

12.1 INTRODUCTION

The ever‐increasing demand for channel capacity and bandwidth has resulted in the widespread use of adaptive signal processing techniques that compensate for the inevitable signal interference and distortion that results from the competitive needs for capacity and bandwidth. The significant advantages in efficient spectrum utilization, gained by high‐order symbol modulation with spectral containment, have been facilitated by the use of adaptive processing algorithms that compensate for the interference and distortion under crowded channel conditions. The development of adaptive processing for improved communications was jump‐started when wireline telephone networks [1] were under pressure for more capacity and higher data rates, and was well understood and developed when wireless communications entered the marketplace.

In the following sections, 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. These three objectives are obtained using subtle alterations in the adaptive processing configurations. The adaptive processing generally uses finite impulse response¹ (FIR) filters with weights that are adaptively adjusted to minimize error between the sampled filter output and the received input signal with known or estimated data using the minimum mean‐square error [2] (MMSE) algorithm. ...