Study and Analysis of an Adaptive MIMO OFDM System for the Improvement of the Spectral Efficiency of Wireless Systems

Abstract

Materials and Methods: To study and evaluate the performance of two linear channel estimators, the Least Square Error(LS) and Linear Minimum Mean Square 4 V-BLAST MIMO-OFDM system with different modulation-BPSK, QPSK, 8QAM, and 16QAM as well as with MMSE equaliser at receiver. For performance analysis, Channel estimation technique LMMSE is used instead of Minimum Mean Square Error(MMSE) because of its simplicity as well as it retains MMSE criteria but the constraint is linear. In optimal power allocation initially, the subcarriers are allocated with the random amount of power owing to the total power constraint and then optimal power to be allocated to the carriers is determined by the Cuckoo Search algorithm depending on the condition of the carriers measured from the channel estimation. newlineResults and Discussion: In this research, the proposed optimal power allocation method for high-speed V-BLAST MIMO-OFDM system showed a better performance in terms of SNR and BER than the traditional methods. This thesis work has been evaluated based on a different channel estimation with different modulation techniques for V-BLAST MMSE MIMO-OFDM System. The test program has been implemented in the latest technology system in Matlab R2013a. The experimental results show that our proposed method achieves better performance in terms of BER and SNR compared with the existing methods used for improving the performance of the MIMO-OFDM. Linear MMSE proved efficient channel estimation technique over LS. MMSE -OSIC achieves very good performance with respect to other detectors in V-BLAST MIMOOFDM environment for 2 2 as well as 4 4 MIMO-OFDM systems. newlineConclusion: This result would be useful to make efficient Adaptive MIMO-OFDM system. It would be also useful in adaptive modulation and power allocation concept for making better wireless communication system. This performance analysis can perform for different channel models. newline