Optimized semiblind sparse channel estimation algorithm for MU-MIMO OFDM system

Abstract

In Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the channel plays an imperative role as the multipath. The channel estimation frameworks specifically designed for the demanding channel conditions with faster time-varying characters are separately emphasized. The prevailing Channel Estimation (CE) methodologies are incredibly complex. To resolve such complexities, this paper proposed an Optimized Semi-Blind Sparse (OSBS) CE algorithm for MU-MIMO OFDM. On the transmitter block, initially, the QPSK modulation is implemented to modulate an input signal. Subsequently, the Pulse Shaping Algorithm (PSA) used for mitigating the ISI (Inter-Symbol Interferences). For symbol mapping, an IFFT (Inverse Fast Fourier Transforms) operation performed at each transmitter. Next, transmit the symbols over the Multipath channel via transmitter’s antennas towards the receiver’s antennas by adding AWGN (Additive White Gaussian Noise). The operations in the transmitter inversely done on the receiver block. Then CE is done by utilizing the OSBS algorithm, and the cost function is lessened by employing EDE (Enhanced Differential Evolution) algorithm. Lastly, the Channel Capacity (CC) is called gauge. Experiential result of the proposed system gives better results when contrasted with the other methods centered on Bit Error Rate (BER), PSNR, Symbol Error Rate (SER), LS, and MMSE.