Maximizing energy efficiency in 6G cognitive radio network

The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation. Sixth-Generation (6G) networks, utilizing Cognitive Radio (CR) technology within CR Network (CRN), can enhance spectrum utilization by accessing unused spectrum when licensed Primary...

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Veröffentlicht in:Digital communications and networks Jg. 11; H. 5; S. 1356 - 1369
Hauptverfasser: Ghafoor, Umar, Masood Siddiqui, Adil
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.10.2025
KeAi Communications Co., Ltd
Schlagworte:
Charnes-cooper transformation
CRN
Energy efficiency
HMA
Outer approximation algorithm
SMEC
6G
Charnes-cooper transformation
Energy efficiency
Outer approximation algorithm
HMA
CRN
SMEC
ISSN:2352-8648, 2352-8648
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Zusammenfassung:The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation. Sixth-Generation (6G) networks, utilizing Cognitive Radio (CR) technology within CR Network (CRN), can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment (PME) is inactive or served by a Primary Base Station (PrBS). Secondary Mobile Equipment (SME) accesses this spectrum through a Secondary Base Station (SrBS) using opportunistic access, i.e., spectrum sensing. Hybrid Multiple Access (HMA), combining Orthogonal Multiple Access (OMA) and Non-Orthogonal Multiple Access (NOMA), can enhance Energy Efficiency (EE). Additionally, SME Clustering (SMEC) reduces inter-cluster interference, enhancing EE further. Despite these advancements, the integration of CR technology, HMA, and SMEC in CRN for better bandwidth utilization and EE remains unexplored. This paper introduces a new CR-assisted SMEC-based Downlink HMA (CR-SMEC-DHMA) method for 6G CRN, aimed at jointly optimizing SME admission, SME association, sum rate, and EE subject to imperfect sensing, collision, and Quality of Service (QoS). A novel optimization problem, formulated as a non-linear fractional programming problem, is solved using the Charnes-Cooper Transformation (CCT) to convert into a concave optimization problem, and an ϵ-optimal Outer Approximation Algorithm (OAA) is employed to solve the concave optimization problem. Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA, surpassing the performance of current OMA-enabled CRN, NOMA-enabled CRN, SMEC-OMA enabled CRN, and SMEC-NOMA enabled CRN methods, with ϵ-optimal results obtained at ϵ=10−3, while satisfying Performance Measures (PMs) including SME admission in SMEC, SME association with SrBS, SME-channel opportunistic allocation through spectrum sensing, sum rate and overall EE within the 6G CRN.
ISSN:2352-8648
2352-8648
DOI:10.1016/j.dcan.2025.06.008