Joint Antenna Selection and Power Allocation for Clustered Downlink NOMA Networks With Alamouti Space‐Time Block Coding

ABSTRACT In this paper, the problem of joint antenna selection and power allocation (J‐AS‐PA) for Alamouti space‐time block coding (STBC)‐based clustered downlink nonorthogonal multiple‐access (NOMA) networks is considered. Essentially, the aim is to assign a pair of antennas to each user cluster and perform power allocation to maximize the network sum‐rate, while satisfying quality‐of‐service (QoS) requirements for all users. However, the problem is nonconvex and computationally‐expensive. In turn, it is split into two subproblems; antenna selection, and power allocation over each (user cluster, antenna pairs) combination, and then solved via a two‐stage solution procedure. In Stage 1, antenna selection is solved using the stable marriage matching algorithm, whereas the power allocation problem is reformulated as a concave maximization problem. In Stage 2, a swap matching algorithm is devised to ensure stability and further improve the network sum‐rate. Simulation results illustrate that the proposed solution procedure achieves a near‐optimal network sum‐rate in comparison with the global optimal J‐AS‐PA scheme, and is superior to the OMA‐based network. Not only that, but the Alamouti‐based schemes will be shown to outperform the conventional non‐Alamouti STBC counterpart schemes, which is due to the spatial‐diversity gains. Lastly, light is shed on the effect of imperfect successive interference cancellation (SIC) and channel state information (CSI), where the Alamouti‐based schemes demonstrate more robustness against SIC and CSI errors than other benchmark schemes.

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Publication Details

Journal
International Journal of Communication Systems
Published
2025-05-19
DOI
https://doi.org/10.1002/dac.70125
Primary Topic
Advanced Wireless Communication Technologies
Type
article
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article

Joint Antenna Selection and Power Allocation for Clustered Downlink NOMA Networks With Alamouti Space‐Time Block Coding

Mohammed W. Baidas, Reem T. Akasha
1 links
International Journal of Communication Systems
Advanced Wireless Communication Technologies
article

Joint Antenna Selection and Power Allocation for Clustered Downlink NOMA Networks With Alamouti Space‐Time Block Coding

Mohammed W. Baidas, Reem T. Akasha
article en

Abstract

ABSTRACT In this paper, the problem of joint antenna selection and power allocation (J‐AS‐PA) for Alamouti space‐time block coding (STBC)‐based clustered downlink nonorthogonal multiple‐access (NOMA) networks is considered. Essentially, the aim is to assign a pair of antennas to each user cluster and perform power allocation to maximize the network sum‐rate, while satisfying quality‐of‐service (QoS) requirements for all users. However, the problem is nonconvex and computationally‐expensive. In turn, it is split into two subproblems; antenna selection, and power allocation over each (user cluster, antenna pairs) combination, and then solved via a two‐stage solution procedure. In Stage 1, antenna selection is solved using the stable marriage matching algorithm, whereas the power allocation problem is reformulated as a concave maximization problem. In Stage 2, a swap matching algorithm is devised to ensure stability and further improve the network sum‐rate. Simulation results illustrate that the proposed solution procedure achieves a near‐optimal network sum‐rate in comparison with the global optimal J‐AS‐PA scheme, and is superior to the OMA‐based network. Not only that, but the Alamouti‐based schemes will be shown to outperform the conventional non‐Alamouti STBC counterpart schemes, which is due to the spatial‐diversity gains. Lastly, light is shed on the effect of imperfect successive interference cancellation (SIC) and channel state information (CSI), where the Alamouti‐based schemes demonstrate more robustness against SIC and CSI errors than other benchmark schemes.

International Journal of Communication SystemsVol. 38(10)
Kuwait Petroleum Corporation (Kuwait) (KW), Kuwait University (KW)
Openalex Percentile: Top 91%
Advanced Wireless Communication Technologies
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