Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink

摘要

LTE-A downlink transfers data and control information from base station to mobile. To reduce the mean square error between original and estimated channel, pilot/training based channel estimation like Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE) are ubiquitous for most wireless standards. To optimize the channel, many intelligent optimized techniques were developed. GA has no guarantee in finding global optima and high convergence time. ANN suits only linear solutions and more training period. PSO fits high dimensional space but needs more iterations. ABC has limited search space by initial solution. CS requires large resources and high computational time. To overcome these effects, an effortless Trellis Coded Firefly Optimized LMMSE based algorithm is proposed to estimate the channel. TCM has high spectral efficiency, more data rate and reduced error. FA has low complexity, easy implementation, automatic subdivision of groups to find local/global optima and ability to deal with multimodality. At SNR = 10 dB, LSE has high MSE of 10(-2) , LMMSE has 15.85% reduced MSE than LSE. The previous optimized methods have MSE ranging from 10(-3) to 10(-2) but the proposed method with 64-QAM has MSE range of 10(-5) to 10(-4) , which is 100 times reduced.