Performance Comparison of LS and LMMSE Channel Estimation Algorithm for CO-OFDM System

Abstract

The CO-OFDM single-mode optical fiber system is constructed by the Matlab coupled with the Optisystem. And the influence of different channel algorithm on the receiver of system is researched. The simulation results show that the system performance is improved by using LS or LMMSE channel algorithm. And the LMMSE channel algorithm can provide better performance than the LS channel algorithm. Compared with LS algorithm, the required receiver OSNR is reduced by about 1 dB using improved LMMSE algorithm at bit-error-rate (BER) =10-4 in the CO-OFDM single-mode optical fiber system.

Channel Estimation Based on Statistical Frames and Confidence Level in OFDM Systems

“…The inverse operation is more complex as the number of subcarriers increases. The third method is linear MMSE (LMMSE) estimation [12,13]. The LMMSE method can exhibit good performance under multipath channels; however, the LMMSE estimator suffers a performance floor at a high signal-to-noise ratio (SNR).…”

Channel estimation and equalization in OFDM receiver for WiMAX with Rayleigh distribution

“…In this estimation, probabilistic assumptions are not required, signal model is only used. LSE channel estimation is [4],…”

“…In the presence of channel noise, LMMSE estimation of uncorrelated Gaussian channel vector g is [4] ,…”

“…To hold low bit error rates and high data rates and in OFDM systems, the estimator should have high accuracy and low complexity. The goal of the channel least square (LS) estimator [4] is to reduce the square distance between the received signal and the original signal. The LMMSE (Linear Minimum Mean Square Error) [4] channel estimator is designed to reduce the estimation MSE.…”

“…The goal of the channel least square (LS) estimator [4] is to reduce the square distance between the received signal and the original signal. The LMMSE (Linear Minimum Mean Square Error) [4] channel estimator is designed to reduce the estimation MSE. Fading [5] relates to the variation of the signal amplitude over time and frequency.…”