Improved channel estimation using genetic operators for LTE downlink system

Long Term Evolution (LTE) is an emerging technology in the evolution of 3G and 4G cellular services. Orthogonal Frequency Division Multiplexing (OFDM) has become a promising technique for high data rate wireless communication systems. It has been widely employed for 4G systems like WiFi, DVB - T, WiMAX, LTE - A etc. Here LTE physical layer downlink is considered which conveys information from enhanced base station (eNodeB) to mobile user equipment (UE) using Orthogonal Frequency Division Multiple Access technique for LTE physical layer downlink channel estimation. To overcome the disadvantages of existing channel estimation methods, a new method is proposed by combining LS and MMSE methods using Genetic Operators like Mutation and Crossover. In this method, a four step algorithm is used. The best channel estimation matrix is selected with minimum error among the three estimated matrices with the help of fitness function. The simulation results show the performance of the new proposed method with BPSK is better and produces low NMSE ranging from 10^-15 to 10^-3 and zero BER. With more number of iterations, QPSK is better than BPSK in proposed method but has higher BER than BPSK. The selection of modulation schemes in adaptive modulation is essential. This technique can be used in medical field for transferring patient information immediately to doctor and can be used in situations where the ambulance cannot be arrived in time to the accident or wounded area.