Abstract
In this paper, we derive the bit error rate and pairwise error probability (PEP) for massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems for different $M$ -ary modulations based upon the approximate noise distribution after channel equalization. The PEP is used to obtain the upper-bounds for convolutionally coded and turbo coded massive MIMO-OFDM systems for different code generators and receive antennas. In addition, complexity analysis of the log-likelihood ratio (LLR) values is performed using the approximate noise probability density function. The derived LLR computations can be time-consuming when the number of receive antennas is very large in massive MIMO-OFDM systems. Thus, a reduced complexity approximation is introduced using Newton’s interpolation with different polynomial orders and the results are compared with the exact simulations. The Neumann large matrix approximation is used to design the receiver for a zero-forcing equalizer by reducing the number of operations required in calculating the channel matrix inverse. Simulations are used to demonstrate that the results obtained using the derived equations match closely the Monte Carlo simulations.
Highlights
M ASSIVE multiple-input multiple-output (MIMO) systems have recently attracted immense interest in the field of wireless communications due to their ability to increase data throughput and improve link quality [1]–[4]
Improvement in the bit error rate (BER) performance can reduce the number of receive antennas required to design coded massive MIMO-Orthogonal frequency-division multiplexing (OFDM) systems compared to uncoded systems [9]–[15]
We focus on two significant technical differences between conventional MIMO-OFDM and massive MIMO-OFDM systems, which can be summarized in the following points:
Summary
M ASSIVE multiple-input multiple-output (MIMO) systems have recently attracted immense interest in the field of wireless communications due to their ability to increase data throughput and improve link quality [1]–[4]. Improvement in the bit error rate (BER) performance can reduce the number of receive antennas required to design coded massive MIMO-OFDM systems compared to uncoded systems [9]–[15]. The massive number of receiving antennas at the base station, i.e. when Nr 10N , has justified the exploitation of the diagonally dominant property of the Gram matrix This assumption has reduced the complexity of evaluating the ZFE, and the calculation of the noise probability density function (PDF). We derive the bit error rate (BER) for uncoded massive MIMO-OFDM systems with M -QAM modulation for frequency-selective, Rayleigh fading channels using the ZFE. The subscripts l and n are used as indices for the l-th uplink user and the n-th receive antennas
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