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Bit error rate performance versus signal to noise ratio, for a 128X32 massive MIMO system using QPSK modulation.
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MIMO or Multiple- input- Multiple- output is one of the latest technologies, which has been developed to combat the major problems encountering wireless communications. MIMO was developed to improve communication's capacity, range, reliability, throughput, to overcome bandwidth limitations, and to combat fading. This paper investigates the performa...
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... addition, when MIMO channels are spatially correlated, AMP approach may not have the ability to converge, which results in an undesirable performance. Figures 3-6 show the bit error rate performance comparisons for 5 iterations of AMP algorithm as well as the classical LMMSE, through different numbers of antennas and users. As we can see from the figures, the performance of the AMP algorithm approaches that of the classic LMMSE when the T is increased. ...
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Citations
... Review on various detectors in massive MIMO technology: a performance analysis [41] Performance of Detection Algorithms for Massive MIMO Systems [42] Performance analysis of Massive-MIMO using MRC, ZF and MMSE under Rician Fading. ...
The massive MIMO communication system for cellular networks has shown excellent performance in terms of high spectral and energy efficiencies in recent years. This achievement has been due to the assiduous research undertaken in terms of formulating mathematical expressions to compute these efficiencies. The purpose of this work is to find a generalized approach to compute the error rates of a user terminal connected to a linear receiver of a Massive MIMO system. In line with the objectives set for present and future cellular networks to achieve ultra-reliable communication systems the issue of finding bit error rates required per user terminal is evaluated for a range of BS antennas is addressed in this paper. The approach employed to tackle this issue is to consider three practical linear receivers such as Maximum Ratio Combining (MRC), Zero-Forcing (ZF), Minimum Mean Square Error (MMSE) altogether with an uncorrelated Rayleigh fading environment in the case of imperfect Channel State Information (CSI). Based on solid mathematical foundations, the approach to find the Bit Error Rate (BER) closed-form expressions which are simple to evaluate and have not been reported in literatures yet, are derived for MPSK and MQAM modulation techniques. We verified the validity of our analysis by simulating all mathematical formulations using Matlab R2018 and we showed interesting results such as the number of BS antennas required to achieve the desired BER for a specific uplink receiver and modulation scheme. The mathematical analysis presented in this work can be applied to future cellular systems to compute the distribution of error rates for a user with a given number of BS antennas and modulation scheme. Moreover, Machine Learning algorithms could be applied to the analysis presented to predict the bit error rates for any user terminal in the cellular network.
