Channel Estimation in OFDM Mobile Wireless Channel Using ZF, ZF-SIC, ZF-SIC-OO, MMSE, MMSE-SIC, MMSE-SIC-OO, LS & ALSMME Method

Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have emerged as wide application technology in wireless communication systems for increasing data rate and the system performance. The effect of fading & interference can be reduced to increase the capacity of the link. MIMO systems uses multiple (input) Transmit and multiple (output) Receive antennas which exploit the multipath propagation in the rich scattering environment. The matrix channel plays very pivotal role in the throughput of a MIMO link since the modulation, data rate, power allocation & the antenna weights are the various dependent parameters on the channel gain. When data rate is been transmitted at high bit rate, the channel impulse response can be extended over many symbol periods which leads to Inter-Symbol Interference (ISI). ISI always causing an issue for signal recovery in wireless communication. In order to reduce complexity of MIMO system, various detection algorithm such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Maximum Likelihood (ML) and a Novel algorithm namely ALMMSE is proposed that reduce Bit Error Rate (BER) by using spatial multiplexing. BPSK modulation is taken here as basic for simulation. All the simulations has been done by using MATLAB that shows BER vs. Signal to Noise Ratio (SNR) curve of equalizer exceeds that of ZF, ZFSIC, ZF-SIC-OO, MMSE , MMSE-SIC, MMSE-SIC-OO, ML, LS and ALMMSE equalizer. In this paper antenna 2x2 configuration is used.

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