Energy Efficient Optimal Resource Allocation in Multi-RAT Heterogeneous Network

In this paper, we address the frequent problem associated with user association and resource allocation along with optimal deployment of base station (BS) in multiple radio access technology (Multi-RAT)-assisted heterogeneous network (Het-Net). Considering real time user scenarios, optimal resource...

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Bibliographic Details
Published in:Applied artificial intelligence 2021-12, Vol.35 (15), p.2246-2275
Main Authors: Debnath, Sanjoy, Jee, Anand, Sen, Debarati, Baishya, Srimanta, Arif, Wasim
Format: Article
Language:English
Subjects:
Algorithms
Blackout
Energy consumption
Evolutionary computation
Heuristic methods
Optimization
Optimization techniques
Radio equipment
Resource allocation
Resource utilization
Wireless communications
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Summary:In this paper, we address the frequent problem associated with user association and resource allocation along with optimal deployment of base station (BS) in multiple radio access technology (Multi-RAT)-assisted heterogeneous network (Het-Net). Considering real time user scenarios, optimal resource allocation in Het-Net while ensuring each user's minimum required data rate is a challenging task to be performed. Here, we propose a novel algorithm with a well-known and efficient meta-heuristic optimization technique to resolve the aforementioned problem. We use hybrid memory-based dragonfly algorithm with differential evolution (DADE) for its excellent convergence characteristics. Extensive simulations are performed to determine the optimal network utility under the consideration of nonuniform user distribution and fine-tuning their respective service class and contract of association parameters. Simulation results depict that the proposed algorithm improves the overall network utility in terms of radio resource utilization and energy consumption while satisfying the user demands. Comparative analysis of the proposed technique with the other state-of-the-art algorithm depicts the superiority of the proposed algorithm in terms of accuracy and consistency. We also perform optimal multi-RAT cell planning under the above constraints including a network blackout scenario. The algorithm ensures each user coverage by optimally allocating the available resources.
ISSN:0883-9514
1087-6545
DOI:10.1080/08839514.2021.1998300