Joint Transmit/Receive Antenna Selection in MIMO Systems Based on the Priority-Based Genetic Algorithm

Lu, Hoang-Yang; Fang, Wen‐Hsien

doi:10.1109/lawp.2007.911387

Cited by 42 publications

(20 citation statements)

References 8 publications

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“…Antenna selection/beamforming based on Tabu search and priority-based genetic algorithm (GA) is considered in [5] and [6], respectively. The symbol error probability [7], the outage probability [8] and the bit error probability [9] of the network are analyzed for different antenna selection algorithms.…”

Section: Introductionmentioning

confidence: 99%

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A Genetic Algorithm-Based Antenna Selection Approach for Large-but-Finite MIMO Networks

Makki

Ide

Svensson

et al. 2017

IEEE Trans. Veh. Technol.

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CitationMakki This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract-We study the performance of antenna selectionbased multiple-input-multiple-output (MIMO) networks with large but finite number of transmit antennas and receivers. Considering the continuous and bursty communication scenarios with different users' data request probabilities, we develop an efficient antenna selection scheme using genetic algorithms (GA). As demonstrated, the proposed algorithm is generic in the sense that it can be used in the cases with different objective functions, precoding methods, levels of available channel state information and channel models. Our results show that the proposed GAbased algorithm reaches (almost) the same throughput as the exhaustive search-based optimal approach, with substantially less implementation complexity.

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Section: Introductionmentioning

confidence: 99%

“…The contribution of the paper is twofold. 1) We develop an efficient antenna selection scheme based on the GAs [6]. With the proposed GA-based approach, the appropriate transmit antennas are activated based on the instantaneous channel quality such that the system performance is optimized.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm-Based Antenna Selection Approach for Large-but-Finite MIMO Networks

Makki

Ide

Svensson

et al. 2017

IEEE Trans. Veh. Technol.

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show abstract

“…For all the EA algorithms, the population size P , the number of generations, and the elitism parameter T , are selected in accordance with [12,13]. Values for each scenario are shown in Table II.…”

Section: Simulation Resultsmentioning

confidence: 99%

Antenna selection for MIMO systems using biogeography based optimization

Fountoukidis

Siakavara

Goudos

et al. 2017

2017 International Workshop on Antenna Technology: Small Antennas, Innovative Structures, and Applications (iWAT)

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“…The first 2Z elements of the mask are for the subcarrier pairing part, while the remaining element is for the power allocation part. For the subcarrier pairing part, we use the priority-based crossover [18], which consists of two steps: exchange empty and sort refill. In the exchange empty, when the elements in the crossover mask are 1's, the genes of the two parent chromosomes in the corresponding positions will be exchanged, whereas if they are 0's, the genes will be emptied.…”

Section: B Proposed Ga-based Approach For Joint Subcarrier Pairing Amentioning

confidence: 99%

Power allocation and subcarrier pairing in OFDM-based Decode-and-Forward relay networks based on a genetic approach

Lang

Fang

Lin

2013

2013 International Symposium on Intelligent Signal Processing and Communication Systems

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Abstract-This paper addresses a joint subcarrier pairing and power allocation scheme in the orthogonal frequency division multiplexing (OFDM)-based Decode-and-Forward (DF) cooperative networks via a genetic approach. To suit the joint consideration, each chromosome in the proposed genetic algorithm (GA) is divided into an integer string for subcarrier pairing and a real number string for power allocation. In addition, new crossover and mutation operations are implemented for this new type of chromosomes. Conducted simulations show that the proposed GA-based approach outperforms some representative previous works with modest computational load.Index Terms-Decode-and-forward cooperative networks, OFDM, subcarrier pairing, power allocation, genetic algorithm.

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Joint Transmit/Receive Antenna Selection in MIMO Systems Based on the Priority-Based Genetic Algorithm

Cited by 42 publications

References 8 publications

A Genetic Algorithm-Based Antenna Selection Approach for Large-but-Finite MIMO Networks

A Genetic Algorithm-Based Antenna Selection Approach for Large-but-Finite MIMO Networks

Antenna selection for MIMO systems using biogeography based optimization

Power allocation and subcarrier pairing in OFDM-based Decode-and-Forward relay networks based on a genetic approach

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