Performance of Data-Rate Analysis of Massive MIMO System Using User Grouping

Sheikh, Tasher Ali; Bora, Joyatri; Hussain, Md. Anwar

doi:10.1007/s11277-020-07723-2

Cited by 10 publications

(8 citation statements)

References 16 publications

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“…We consider two linear precoding schemes that are used for the analysis of SE of the cell free Massive MIMO system. Precoding is a method in which by multiplying the precoding matrixes with user data capable to suppress the interference of the system that is produced due to the signals of other users [13]. From equation (10), the precoding scheme is shown in Fig.…”

Section: Linear Precodingmentioning

confidence: 99%

Performance Improvement of Cell Free Massive MIMO System Using User Clustering and Access Point Selection Technique

Sheikh¹

2022

Preprint

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A Cell Free massive MIMO, comprising a very large number of distributed access points (APs) is a promising technology to provide high data rate, spectral efficiency (SE), and energy efficiency (EE). The system performance of cell free M-MIMO is optimal when selecting access points (AP) from a large number of APs. In this work, zero-forcing (ZF) and minimum means square error (MMSE) linear precoding are used since it is free from self-interference hence, improving the system sum-rate. Here, the maximum channel gain-based Access Point Selection (APS) algorithm is introduced for access point (AP) selection in the Cell free M-MIMO network to enhance the system data-rate. APS algorithm used to select those APs whose channel gain is highest therefore it improves the rate of the system. The same number of users is scheduled using a simple semi-orthogonal user scheduling (SUS) algorithm. We also used a user clustering algorithm for grouping the users around the AP to schedule the best users. It is observed from the results that the APS and SUS algorithm jointly improve the system rate significantly in cell free massive MIMO systems.

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Section: Linear Precodingmentioning

confidence: 99%

Performance Improvement of Cell Free Massive MIMO System Using User Clustering and Access Point Selection Technique

Sheikh¹

2022

Preprint

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“…Genetic algorithms are a type of random search strategy that mimics evolution's laws. The biological world is a bionic algorithm with a powerful all-encompassing quest of perfection, including various people at a higher level [28]. According to the norms of superiority and inferiority, the condition is handed on to the next generation, with some individuals of lesser fitness eventually departing from the population and others of higher fitness increasing.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems

Mutlaq¹,

Saad

Aldabbagh³

et al. 2022

IJEECS

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Transmit antennas are chosen in multi-input-multi-output (MIMO) systems. Effective in improving system capacity while lowering RF connection costs and simplifying the system. Complete method with greatest accuracy for joint transmits and receive antenna selection (JTRAS), capable of scanning all subsets of both transmitting and receiving antennas for the optimal solution. However, when as the number of antennas but also computational complexity increase grows too great, limiting its application. Antennas are coded fractionally channel capacity maximizing coding is used as a basic criterion in this paper, and an intelligent algorithm Particle swarm algorithm, generic algorithm are used to pick antennas. The simulation results show that both algorithms are capable of performing antenna selection.

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“…1 In this work, we consider user grouping, which is a crucial component of massive MIMO systems to maintain the trade-off between performance gains and processing complexity [31], when the channel vectors of users are correlated and not asymptotically orthogonal. It is common for users' channels to be correlated in massive MIMO scenarios since the antennas are not sufficiently well separated, and the propagation environment is not richscattered.…”

Section: System Modelmentioning

confidence: 99%

Sum-Rate Analysis of a Multi-Cell Multi-User MISO System Under Double Scattering Channels

Jia

Nadeem

Kammoun

et al. 2022

IEEE Trans. Commun.

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This paper aims to derive expressions of the downlink ergodic user rates in a multi-cell large-scale multi-user multiple-input single-output (MISO) system under the assumption that each base station (BS) employs maximum ratio transmission (MRT) precoding and that single-antenna users in each cell are divided into groups, where channels of users in the same group share common covariance matrices and follow the double scattering channel model. Moreover, both channel estimation errors and pilot contamination effects caused by re-use of pilot sequences in neighboring cells are taken into consideration in this work. The analysis is carried out using statistical tools under the exact and asymptotic regimes in which the number of antennas at BS N , the number of users in each cell K, and the number of scatterers S grow large at the same pace. Furthermore, the obtained exact expressions and deterministic approximations of the ergodic rates are expressed in simplified closed-forms under the special case of multi-keyhole channels to yield useful insights. They reveal that signal-to-noise plus interference ratio (SINR) without user grouping in a multikeyhole channel is similar to that under standard Rayleigh channel in the asymptotic regime. However, under user grouping, we show that the massive multiple-input multiple-output (MIMO) gains promised by deploying large-scale antenna arrays in multicell settings are limited by the number of scatterers even if the number of antennas grows large. Simulation results illustrate the close match provided by the asymptotic analysis for moderate system dimensions and confirm the insights drawn from the theoretical findings.

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Performance of Data-Rate Analysis of Massive MIMO System Using User Grouping

Cited by 10 publications

References 16 publications

Performance Improvement of Cell Free Massive MIMO System Using User Clustering and Access Point Selection Technique

Performance Improvement of Cell Free Massive MIMO System Using User Clustering and Access Point Selection Technique

Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems

Sum-Rate Analysis of a Multi-Cell Multi-User MISO System Under Double Scattering Channels

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