A genetic-algorithm-based multiuser detector for multiple-access communications

Wang, X.F.; Lu, Wenkai; Antoniou, A.

doi:10.1109/iscas.1998.698973

Cited by 26 publications

(12 citation statements)

References 6 publications

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“…Two of the T number of L-symbol individuals in the mating pool are then selected as parents based on their corresponding diversity-based fitness values calculated with the aid of Equation 14 according to the so-called fitness-proportionate selection scheme [12]. The so-called windowing-mapping [14] technique is invoked in order to get the fitness value f (y) i associated with the i th individual, which is given by:…”

Section: Concatenated Mmse-ga Multi-user Detectionmentioning

confidence: 99%

Genetically enhanced TTCM assisted MMSE multi-user detection for SDMA-OFDM

Jiang

Hanzo

IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004

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Section: Concatenated Mmse-ga Multi-user Detectionmentioning

confidence: 99%

Genetically enhanced TTCM assisted MMSE multi-user detection for SDMA-OFDM

Jiang

Hanzo

IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004

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“…Specifically, in the context of wireless communications, GA-based multiuser detection has been proposed by Juntti et al [313] and Wang et al [314], where the analysis was based on the AWGN channel in the absence of diversity techniques. The proposal by Ergün and Hacioglu [315] utilized GAs as the first stage of a multistage MUD, in order to provide good initial guesses for the subsequent stages.…”

Section: Overview Of Ga-aided Mudsmentioning

confidence: 99%

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

2007

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“…Moreover, GA-based multiuser detection has been proposed by Juntti et al [27] and Wang et al [28], where the analysis was based on the additive white Gaussian noise (AWGN) channel in the absence of diversity techniques. The proposal by Ergün et al [29] utilized GAs as the first stage of a multistage multiuser detector, in order to provide good initial guesses for the subsequent stages.…”

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confidence: 99%

Hybrid Iterative Multiuser Detection for Channel Coded Space Division Multiple Access OFDM Systems

Jiang

Hanzo

2006

IEEE Trans. Veh. Technol.

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Abstract-Space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems assisted by efficient multiuser detection (MUD) techniques have recently attracted intensive research interests. The maximum likelihood detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher order modulation schemes. By contrast, the minimum mean-square error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward error correction (FEC) schemes such as, for example, turbo trellis coded modulation (TTCM), may be efficiently combined with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided code division multiple access (CDMA) systems. In this contribution, a GA-aided MMSE MUD is proposed for employment in a TTCMassisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum MLD-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed biased Q-function based mutation (BQM) assisted iterative GA (IGA) MUD is employed, the GA-aided system's performance can be further improved, for example, by reducing the bit error ratio (BER) measured at 3 dB by about five orders of magnitude in comparison to the TTCMassisted MMSE-SDMA-OFDM benchmarker system, while still maintaining modest complexity.Index Terms-Biased Q-function based mutation (BQM), genetic algorithm (GA), minimum mean-square error (MMSE), multiuser detection (MUD), orthogonal frequency division multiplexing (OFDM), space division multiple access (SDMA), turbo trellis coded modulation (TTCM).

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A genetic-algorithm-based multiuser detector for multiple-access communications

Cited by 26 publications

References 6 publications

Genetically enhanced TTCM assisted MMSE multi-user detection for SDMA-OFDM

Genetically enhanced TTCM assisted MMSE multi-user detection for SDMA-OFDM

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

Hybrid Iterative Multiuser Detection for Channel Coded Space Division Multiple Access OFDM Systems

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