Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is co...

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Veröffentlicht in:Entropy (Basel, Switzerland) Jg. 23; H. 11; S. 1454
Hauptverfasser: Li, Huanyu, Li, Hui, Zhou, Youling
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.11.2021
MDPI
Schlagworte:
Algorithms
Approximation
Communications systems
Complexity
Dynamic programming
Efficiency
Game theory
joint resource optimization
maritime user allocation
non-orthogonal multiple access
Nonorthogonal multiple access
offshore communications
Optimization
Polynomials
power allocation
Propagation
Radio communications
Satellite communications
Simulation
South China Sea
ISSN:1099-4300, 1099-4300
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Zusammenfassung:This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.
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ISSN:1099-4300
1099-4300
DOI:10.3390/e23111454