Quantum-Assisted Metaheuristics for Adaptive Resource Allocation in 6G Networks
- Title
- Quantum-Assisted Metaheuristics for Adaptive Resource Allocation in 6G Networks
- Creator
- Rao, M Nagabhushana; Paulin, M Sudha; Varghese, Juvitha; Rekha, N.; Rekha, M.D.; Gogineni, Saikiran
- Description
- With 6G wireless communication systems, the level of demands is now ultra-low-latency, connectivity of devices in large numbers, and flexible spectrum utilization. To resolve these issues, in the current paper, the Quantum-Assisted Metaheuristic (QAM) framework is proposed that combines quantum-inspired operators and traditional metaheuristic methods of adaptive resource allocation in 6G networks. This framework uses quantum-enhanced exploration, dynamically tuned parameters and hybrid quantum-classical computing to trade-off scalability against efficiency, depending on the traffic and channel conditions. Oh! SIM Evaluating a simulated 6G environment, it proves that QAM can be used to improve spectral efficiency by up to 28 percent and the allocation latency by 31 percent over the state-of-the-art metaheuristics, and still treats users of varying densities fairly with a fairness index of 0.94. The results demonstrate the strength and extensiveness of the QAM, and makes it a viable solution to the efficient and intelligent management of resources in next generation wireless networks. 2025 IEEE.
- Source
- 2025 International Conference on Future Technologies, ICFT 2025;
- Date
- 01-01-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- 6G networks; adaptive resource allocation; low latency; metaheuristics; network optimization; quantum computing; spectrum management
- Coverage
- Rao M.N., School of Computer Science & Technology, Malla Reddy (MR) Deemed to Be University, Dept. of CSE, Telangana, India; Paulin M.S., School of Business and Management, Christ University, Bangalore, India; Varghese J., School of Management, Kristu Jayanti College (Autonomous), Bangalore, India; Rekha N., School of Commerce, Finance and Accountancy, Christ (Deemed to Be) University, Bangalore, India; Rekha M.D., Department of Commerce, Christ (Deemed to Be University), Bangalore, India; Gogineni S., School of Computer Science & Engineering, Malla Reddy (MR) Deemed to Be University, Dept. of CSE, Telangana, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833156815-3;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Rao, M Nagabhushana; Paulin, M Sudha; Varghese, Juvitha; Rekha, N.; Rekha, M.D.; Gogineni, Saikiran, “Quantum-Assisted Metaheuristics for Adaptive Resource Allocation in 6G Networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26004.