Implementation of a least mean square (LMS)‎ algorithm for adaptive channel equalization using HDL coder

Abstract EN

The LMS algorithm is the most widely used in wireless applications such as equalization and adaptive filtering in imaging, communications, etc.

The initialization of the LMS equalizer results from a pilot based channel estimation.

This technique is achieved by using algorithms which adapt the coefficients of Finite Impulse Response(FIR) filter to minimize the noise and Intersymbol Interference(ISI) to give an accurate received signal.

This paper presents the implementation of the LMS algorithm on Field Programmable Gate Arrays(FPGA).

Architecture of adaptive filter that is based on multiplier and adder is to realize the Multiple Access Channel(MAC) operation of the Finite Impulse Response (FIR).

The coefficients of the adaptive filter are modified automatically by the LMS algorithm based on input information’s.

The proposed architecture of this algorithm has been design using Matlab-Simulink (R2015a) to deal with parallel structure.

The design has been converted to behavioral VHDL coding style, as will as a VHDL test bench using Simulink HDL Coder tool to realize hardware directly from Simulink design