Abstract
Before moving towards the 5G systems, we have to improve the symbol estimation techniques in the present 4G network to intensify the system performance. There are many symbol estimation techniques for MIMO LTE-A systems; among these techniques and after many researches, it is found that zero-forcing, maximal ratio combining and the minimum mean square error are mostly used. We have focused on the analysis of these techniques. In the MU-MIMO system, we tried to double the data rate and minimize the bit error rate (BER) using MMSE estimation using channel interpolation in the frequency domain. Here, we compared the performance on an AWGN and Rayleigh channel of channel estimation techniques using “ZF”, “ML” and “MMSE” on a 2 × 2 MIMO LTE system with BPSK, QPSK and 16 QAM using the VITERBI hard decision method of analysis. Then we modified the system with a 4 × 4 MU-MIMO LTE system and calculated the BER and analysed. Simulation results showed that among these techniques, “ML” is a salient features in characterizing the performance of the data channel and the LS and MSME behaved very similar to each other on a 2 × 2 MIMO system. Further, simulating the results we have showed that the MMSE MIMO detector slightly outperforms as compared to least square (LS) on SINR.
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Jyoti, Nandal, V., Nandal, D. (2021). BER Performance Analysis of MMSE with ZF and ML Symbol Detection for Hard Decision MU-MIMO LTE on Rayleigh Fading Channel. In: Khanna, A., Gupta, D., Pólkowski, Z., Bhattacharyya, S., Castillo, O. (eds) Data Analytics and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 54. Springer, Singapore. https://doi.org/10.1007/978-981-15-8335-3_25
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DOI: https://doi.org/10.1007/978-981-15-8335-3_25
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