Certain investigations on channel estimation algorithms for different fading environments in mimo systems

Abstract

The primary factors in wireless communication are high data rate, spectral efficiency and reliable communication. The technical challenges in wireless communication are multipath propagation, spectrum limitations, limited energy, user mobility, channel models, fading and diversity. The transmission rate quality is a significant factor and it is achieved by utilizing MIMO-OFDM (Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing). OFDM is a flexible and efficient modulation technique and uses separate channel bandwidth into multiple narrowband subcarriers to carry the information. To prevent adjacent carrier interference, subcarriers as orthogonal to each other, hence they are bandwidth efficient. MIMO is the key technology that leads to a significant increase in data rate in wireless communication. The channel estimation is a challenging phenomenon in wireless communication to achieve efficient reception of the signal. newlineThis research mainly focuses on improved channel estimation algorithm proposed through Crossover Teaching Learning Based Optimization (CTLBO) and Convolutional Neural Network AutoEncoder (CNNAE) techniques. The algorithm is proposed to estimate the channel under different fading environments say, Rayleigh, Rician and Nakagami. The entire implementation of the proposed channel estimation method with 8x8 MIMO-OFDM has been carried out in MATLAB simulation and the performance has been measured based on the parameters such as Bit Error Rate (BER), Mean Square Error (MSE), Signal to Noise Ratio (SNR) and Symbol Error Rate. During the analysis, 16-QAM modulation is involved, newline