Genetic algorithm implementation of multi-user detection in SDMA-OFDM systems

Alansi, Mohammed; Elshafiey, Ibrahim; Alsanie, Abdulhameed

doi:10.1109/isspit.2011.6151580

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…The highest complexity, nonlinear and highest optimum performance maximum likelihood (ML) MUD is based on other detection methods . The ML detector calculates the minimum Euclidian distance by comparing all possible transmitted signal vectors with the received signal vector.…”

Section: Multiuser Detection Techniquesmentioning

confidence: 99%

Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

Yeşilyurt¹,

Ertug²

2018

ETRI Journal

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Multiuser detection (MUD) and channel estimation techniques in space‐division multiple‐access aided orthogonal frequency‐division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean‐squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML‐MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

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Section: Multiuser Detection Techniquesmentioning

confidence: 99%

Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

Yeşilyurt¹,

Ertug²

2018

ETRI Journal

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“…GAs have been e®ectively used in various areas, such as digital signal processing and wireless communications. GA-based MUD has been proposed in mobile communication, 27,28 where the analysis is based on the additive white Gaussian noise (AWGN) channel. Its employment in Rayleigh fading channels is considered in Ref.…”

Section: Mud For Racom Multifunction Systemmentioning

confidence: 99%

Multi-User Detection for Radar and Communication Multifunction System

Alansi

Elshafiey

Alsanie

et al. 2015

J CIRCUIT SYST COMP

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A multifunctional system that performs synthetic aperture radar (SAR) and communication tasks is presented. The system depends on orthogonal frequency division multiplexing (OFDM) waveform shaping and multiple input multiple output (MIMO) con¯guration to achieve enhancement in the spectral e±ciency of communication operation and provide interference rejection in SAR imaging. The SAR interval idle time is utilized to enhance the communication signal through diversity. Adaptive system features are introduced to achieve multi-user detection and improve the communication reliability, by means of space division multiple access (SDMA) and space-time block coding (STBC). Investigations of linear and nonlinear multi-user detection (MUD) techniques are provided. Moreover, a genetic algorithm-based system is developed to optimize the MUD problem and to provide near-optimal performance even for overloaded scenarios. A gain of more than 4 dB is achieved at bit error rate of 10 À2 .

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“…In addition, the authors in [24] presented a GA simulation tool applicable in the context of an SDMA-OFDM system for determining an optimized solution. Then the initially proposed FPGA implementation block diagram of GA to enhance system performance was introduced in [25].…”

Section: Introductionmentioning

confidence: 99%

FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems

Alansi

Elshafiey

Alsanie

et al. 2015

Wireless Pers Commun

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Robust multi-user detection (MUD) methods based on space division multiple access (SDMA) techniques are essential to efficiently exploit the electromagnetic spectrum. In this paper, an adaptive Genetic Algorithm-based tool for SDMA-OFDM Systems (GASOS) is developed to improve the performance and computational complexity in cases of fully-loaded and overloaded multi-user scenarios. The data flow in GASOS is appropriate in pipelining and parallelization to reduce operational time. A new GASOS-based MUD hardware design for SDMA-OFDM systems is proposed using FPGA architecture. The design details are presented together with their planned operational modules. Resource utilization is optimized, and the total number of clock cycles required is found to be 15 initially, in addition to one clock cycle per member of algorithm population. A clock frequency of 100 MHz is used and implementation is carried out on Xilinx Ò Virtex-6 FPGA, built in the development platform ML605 edition with JTAG Hardware Co-simulation. According to the results obtained from the developed algorithm and implementation tools, a high number of users can be physically possible and provided with support. Real-time based implementation of MUD systems has the potential to play a major role in next-generation communication systems.

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Genetic algorithm implementation of multi-user detection in SDMA-OFDM systems

Cited by 7 publications

References 6 publications

Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

Multi-User Detection for Radar and Communication Multifunction System

FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems

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