FPGA Implementation of an LMS Algorithm-Based Adaptive Equalizer (Filter) for Digital Communication Systems

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Resource Overview

This paper addresses bit error issues in digital communication systems caused by inter-symbol interference (ISI) and channel additive noise. The project designs an adaptive equalizer/filter using the Least Mean Squares (LMS) algorithm and implements hardware realization through VHDL (VHSIC Hardware Description Language) and FPGA (Field-Programmable Gate Array) technology. The implementation includes key components like tap-weight adaptation, error calculation, and finite impulse response (FIR) filtering operations. This standard graduation thesis serves as a technical reference for implementing adaptive filtering systems with programmable logic devices.

Detailed Documentation

This paper focuses on resolving bit errors at the receiving end of digital communication systems, which are primarily caused by inter-symbol interference (ISI) and channel additive noise. To address this challenge, an adaptive equalizer/filter based on the Least Mean Squares (LMS) algorithm has been designed. The hardware implementation employs VHDL (VHSIC Hardware Description Language) for describing digital logic circuits and FPGA (Field-Programmable Gate Array) for physical realization. Key implementation aspects include: LMS weight adaptation using the formula w(n+1) = w(n) + μ·e(n)·x(n), where μ represents the step size, e(n) the error signal, and x(n) the input vector; FIR filter structure with programmable coefficients; and real-time error calculation circuitry. This standard graduation thesis provides a comprehensive reference for engineers and researchers working on hardware-based adaptive filtering solutions.

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