FPGA-Based Time-Domain Channel Estimation in Gaussian Mixture Model

Muhammad Khalid,Muhammad Rauf,Abid Muhammad Khan,Sheraz Afzal,Muhammad Taha Jilani,Dao B Wang

doi:10.1155/2021/5596301

Abstract

The performance of time-domain channel estimation deteriorates due to the presence of Gaussian mixture model (GMM) noise, which results in high mean squared error (MSE) as a challenging issue. The performance of the estimator further decreases when the complexity of the estimator is high due to the high convergence rate. In this paper, an optimized channel estimation method is proposed with low complexity and high accuracy in the GMM environment. In this channel estimation, an improved Gauss-Seidel iterative method is utilized with a minimum number of iterations. The convergence rate of the Gauss-Seidel method is improved by estimating an appropriate initial guess value when no guard bands are used in the orthogonal frequency-division multiplexing (OFDM) symbol. Simulation results provide an acceptable MSE for GMM environments, up to the probability of 5% impulsive noise component. This paper also presents the design and implementation of the proposed estimator in the NEXYS-2 FPGA platform that provides resources allocation, reconfigurability, schematic, and the timing diagram for detailed insight.

Highlights

In wireless communication, the performance of the system is often limited because it undergoes many unfavorable effects when the signal is transmitted to the receiver. e transmitted signals are normally scattered and reflected and arrived at the receiver through multiple paths [1]
This time-varying channel poses a serious challenge when it comes to estimating it in an efficient manner using the least complex method. us, the estimation of the channel is one of the most challenging and core issues in wireless communication. e additive white Gaussian noise (AWGN) has always been the dominant noise model in wireless communication systems, mainly because of two reasons: the first reason is that analytical manipulation is simple and the second one is due to central limit theorem
It is well known that this assumption is appropriate for many applications but some practical environments exist, which are incorrectly modelled by the AWGN noise model [5]

Summary

Introduction

The performance of the system is often limited because it undergoes many unfavorable effects when the signal is transmitted to the receiver. e transmitted signals are normally scattered and reflected and arrived at the receiver through multiple paths [1]. The iterative based techniques suffer from high complexity problem due to high convergence rate These methods need a large number of hardware resources. The proposed work focuses on time-domain channel estimation method, which is based on iterative technique that utilizes cyclic cross-correlation between received signal and no guard band subpilot sequence to estimate the channel impulse response. (1) e time-domain channel estimator is presented, which utilizes an appropriate initial guess and improves the convergence rate of iterative Gauss-Seidel method in the GMM environment (2) e FPGA implementation of the proposed channel estimation is investigated with its hardware resource requirements (3) Simulation results provide an acceptable MSE, up to the probability of 5% impulsive noise component in GMM environment e remainder of the manuscript is organized as follows: Section 2 discusses the system model.

System Model

Improved Gauss-Seidel Method

Results and Discussion