Alpha-Fair Joint User Grouping and Power Allocation in NOMA-Enabled Combat Network Radio System 


Vol. 51,  No. 4, pp. 926-937, Apr.  2026
10.7840/kics.2026.51.4.926


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  Abstract

We address α-fairness (alpha-fairness) in downlink NOMA for combat-network radio system (CNRS) and propose a joint user grouping and power allocation algorithm. Our proposed algorithm alternatively optimizes a fractional programming (FP) grouping step with utility-aware pruning and a successive convex approximation (SCA) power step. Both subproblems are solved subject to the conditions of optimization variables, successive interference cancellation (SIC) and quality-of-service (QoS) constraints. Monte Carlo simulations show that the proposed algorithm consistently outperforms single-variable optimization and conventional baselines, delivering higher Jain’s fairness index (JFI) and minimum user rate as the fairness metrics. These results demonstrate the value of α-fair formulations for tactical radios and offer actionable constraint settings for back-off design.

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[IEEE Style]

S. Jeong, J. Park, J. Oh, J. Han, J. Kang, "Alpha-Fair Joint User Grouping and Power Allocation in NOMA-Enabled Combat Network Radio System," The Journal of Korean Institute of Communications and Information Sciences, vol. 51, no. 4, pp. 926-937, 2026. DOI: 10.7840/kics.2026.51.4.926.

[ACM Style]

Subin Jeong, Jiho Park, Jimyung Oh, JeeHaeng Han, and Joonhyuk Kang. 2026. Alpha-Fair Joint User Grouping and Power Allocation in NOMA-Enabled Combat Network Radio System. The Journal of Korean Institute of Communications and Information Sciences, 51, 4, (2026), 926-937. DOI: 10.7840/kics.2026.51.4.926.

[KICS Style]

Subin Jeong, Jiho Park, Jimyung Oh, JeeHaeng Han, Joonhyuk Kang, "Alpha-Fair Joint User Grouping and Power Allocation in NOMA-Enabled Combat Network Radio System," The Journal of Korean Institute of Communications and Information Sciences, vol. 51, no. 4, pp. 926-937, 4. 2026. (https://doi.org/10.7840/kics.2026.51.4.926)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880