Chapter 13: Equalization

Learning Objectives

• Explain how frequency-selective channels cause intersymbol interference and interpret eye diagrams as a diagnostic tool
• Design zero-forcing and MMSE linear equalizers and analyse their trade-off between ISI suppression and noise enhancement
• Describe the structure and operation of the decision-feedback equalizer (DFE) and identify the error propagation problem
• Apply the Viterbi algorithm to perform maximum-likelihood sequence estimation (MLSE) on ISI channels and assess its complexity
• Derive the LMS and RLS adaptive equalization algorithms and distinguish training mode from decision-directed mode
• Compare equalizer architectures in terms of performance, complexity, and suitability for different channel conditions
• Connect equalization concepts to modern wireless systems including OFDM and MIMO receivers