Performance analysis of MC-CDMA cellular systems employing MMSE multiuser detector in presence of own-cell and co-cell interference

Mora, Henry Ramiro Carvajal; Garzón, Nathaly Verónica Orozco; Almeida, Celso de

doi:10.1016/j.aeue.2017.06.020

Cited by 9 publications

(11 citation statements)

References 26 publications

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“…where (22) was substituted in (24). In ( 25) the first term is the kth user signal, MAI is the the multiple access interference, CEEI is the channel estimation error interference and the last term is the noise.…”

Section: A Maximal Ratio Combining Detectormentioning

confidence: 99%

“…The SNIR is also conditioned on the eigenvalues λ j and since the eigenvalues distribution is an elaborated expression [34], obtaining the mean SNIR is a quite complex task as shown in [25]. However, from the results of [24], for our scenario, it is possible to show that the mean SNIR per channel is γ c = γ s /(N −K +1) where γ s is the same obtained for the ZF detector in (33). For the PCSI scenario, it must be used = 1, µ = 1 and η = 0 on the SNIR expressions.…”

Section: Minimum-mean-square Errormentioning

confidence: 99%

“…For the MMSE detector, the solution of the integral expression given in ( 43) is quite complex. Nevertheless, it is solved in [24] using the channel reliability approach 8 , which is given by:…”

Section: Ber For Mmse Detectormentioning

confidence: 99%

“…The BER performance of MIMO with perfect channel estimation (or perfect channel state information -PCSI) for MRC and ZF detectors is analyzed in [22] and [23], respectively. For the MMSE detector, with PCSI, a closed-form BER expression is derived in [24] and a symbol error rate (SER) in [25].…”

Section: Introductionmentioning

confidence: 99%

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BER Evaluation of Linear Detectors in Massive MIMO Systems Under Imperfect Channel Estimation Effects

et al. 2019

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New perspectives for wireless communications have brought new techniques, such as a very large number of antennas at a base station (BS) serving multiple user terminals (UTs) with a single antenna each, known as massive MIMO (M-MIMO). M-MIMO linear detectors, such as maximal-ratio combining (MRC), zero-forcing (ZF) or minimum-mean-square error (MMSE) can achieve excellent performance with low complexity due to the channel hardening property. However, imperfect channel estimation produces a penalty in the performance. An average bit error rate (BER) performance analysis over time-invariant channel is presented for M-MIMO systems under imperfect channel estimation in contrast with most of M-MIMO literature that uses the ergodic capacity approach. Closed-form expressions and bounds to evaluate the average BER are derived for MRC, ZF and MMSE detectors in a unicellular environment considering M -QAM modulation. Furthermore, an expression to evaluate the normalized signal-to-noise ratio (E b /N 0 ) penalty due to the imperfect channel estimation is presented. Montecarlo numerical simulations are used to verify the tightness of the derived equations which are a function of the number of BS antennas, number of users, coherence time interval, number of pilot symbols and the E b /N 0 of pilot and data symbols used for channel estimation and data detection.INDEX TERMS BER, imperfect channel estimation, massive MIMO, maximal-ratio combining, minimummean-square error, zero-forcing.

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Section: A Maximal Ratio Combining Detectormentioning

confidence: 99%

Section: Minimum-mean-square Errormentioning

confidence: 99%

Section: Ber For Mmse Detectormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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BER Evaluation of Linear Detectors in Massive MIMO Systems Under Imperfect Channel Estimation Effects

et al. 2019

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“…Perfect CSI has been assumed in the evaluation of error rates for a Massive MIMO communication system employing MRC, ZF and MMSE detectors in [16,17]. With regards to the MMSE detector, it has been reported that the error probability analysis utilized a reliability function formulated by [18,19] thereby giving a closed-form expression which is tractable. In [20], the Bit Error Rate (BER) is computed for a Massive MIMO system assuming perfect CSI and a MRC detector in the uplink.…”

Section: Related Workmentioning

confidence: 99%

An approach to analyse the error performance of linear receivers for Multi-User Massive MIMO communication systems under Imperfect CSI

Hosany,

Rajkumarsingh,

FOWDUR

2023

Preprint

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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.

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On the Asymptotic BER of MMSE Detector in Massive MIMO Systems

Altamirano

Negrete

Almeida

et al. 2020

Communications in Computer and Information Science

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Performance analysis of MC-CDMA cellular systems employing MMSE multiuser detector in presence of own-cell and co-cell interference

Cited by 9 publications

References 26 publications

BER Evaluation of Linear Detectors in Massive MIMO Systems Under Imperfect Channel Estimation Effects

BER Evaluation of Linear Detectors in Massive MIMO Systems Under Imperfect Channel Estimation Effects

An approach to analyse the error performance of linear receivers for Multi-User Massive MIMO communication systems under Imperfect CSI

On the Asymptotic BER of MMSE Detector in Massive MIMO Systems

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