Joint Transmit and Receive Antenna Selection in Mimo Systems Based on Swarm Intelligence Algorithm

Zhang, Yiwen; Su, Sunqing; Liao, Wenliang; Lei, Guowei; Yang, Guangsong

doi:10.1007/s11277-022-09760-5

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…The suggested optimum TAS design was implemented in “MATLAB,” and the outcomes were displayed. Accordingly, the supremacy of the presented HS‐WA model was evaluated over existing models, namely, the modified velocity vector‐based gravitational search algorithm (MV‐GSA), 36 the improved sea lion optimization (I‐SLnO), 37 the SLnO, 34 the WOA, 29 and the particle swarm optimization (PSO) 38 . Here, two sets were used for the analysis.…”

Section: Resultsmentioning

confidence: 99%

“…Accordingly, the supremacy of the presented HS-WA model was evaluated over existing models, namely, the modified velocity vector-based gravitational search algorithm (MV-GSA), 36 the improved sea lion optimization (I-SLnO), 37 the SLnO, 34 the WOA, 29 and the particle swarm optimization (PSO). 38 Here, two sets were used for the analysis. The 1st setup is "P tx ¼ 40W , sv U flop=R ð Þ¼5U flop=R, P RF front ¼ 975mW ," and the 2nd setup was "P tx ¼ 10W , P sum1 sv U flop=R ð Þ¼ 50U flop=R, P RF front ¼ 97:5mW ."…”

Section: Simulation Setupmentioning

confidence: 99%

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Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

Singh

Kishoreraja

2022

Int J Communication

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Massive Multiple Input Multiple Output (M-MIMO) systems specifically refers to a practical technique for sending and receiving more than one data signal simultaneously over the same radio channel by exploiting multipath propagation". It depends on several antennas for transferring varied data streams simultaneously. With the increase in count of antennas, the energy or power utilization also gets increased. Thus, it becomes necessary to select optimal transmit antennas that exist as the great challenge in M-MIMO systems. This work introduces a new "Hybrid Sea Lion-Whale Algorithm (HS-WA)" for selecting the optimal transmit antenna by considering the multi-objectives, which increases both capacity and efficiency. The adopted scheme is the combination of both "Whale Optimization Algorithm (WOA) and Sea Lion Optimization Algorithm (SLnO)" that optimizes the antenna's count and moreover, it finds out "which antenna to be selected". At last, the supremacy of presented model is confirmed over existing models in terms EE and capacity analysis.

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Section: Resultsmentioning

confidence: 99%

Section: Simulation Setupmentioning

confidence: 99%

Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

Singh

Kishoreraja

2022

Int J Communication

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DRL-Based Resource Management in RIS-Assisted Uplink Cell-Free Network

Cui

Cao

2022

2022 IEEE Globecom Workshops (GC Wkshps)

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Transmit antenna selection in M-MIMO system using metaheuristic aided model

Singh,

Singh

2024

JHS

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Massive MIMO (M-MIMO) devices are the key tool to meet the performance stards established for 5G-wireless communication. However, more Radio Frequency (RF) chains needed in base station (BS) with a huge count of transmitting antennas, involve expensive hardware and computing complexities. In order to decrease the RF chains needed in BS, this work intended to use the optimal transmit antenna selection (TAS) strategy. This strategy is gaining a lot of interest since the optimization algorithm aids in the ability to enhance the system performance considerably the efficiency and secrecy rate. This work proposes a novel Coati Adopted Pelican Optimization (CA-PO) for choosing the optimal TA by considering efficiency as well as secrecy rate. In addition, the CA-PO algorithm makes the decision on which antenna to be elected. At last, the supremacy of CA-PO-based TAS is proven from the analysis regarding secrecy rate and EE analysis. Accordingly, the proposed CA-PO method for MF for set up 2 has attained a higher EE of 0.976; whereas, the DMOA, COA, MRFO, POA and BEA techniques have got a relatively lower EE of 0.968.

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Joint Transmit and Receive Antenna Selection in Mimo Systems Based on Swarm Intelligence Algorithm

Cited by 3 publications

References 19 publications

Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

DRL-Based Resource Management in RIS-Assisted Uplink Cell-Free Network

Transmit antenna selection in M-MIMO system using metaheuristic aided model

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