Energy Efficient Optimal Resource Allocation in Multi-RAT Heterogeneous Network. Issue 15 (15th December 2021)
- Record Type:
- Journal Article
- Title:
- Energy Efficient Optimal Resource Allocation in Multi-RAT Heterogeneous Network. Issue 15 (15th December 2021)
- Main Title:
- Energy Efficient Optimal Resource Allocation in Multi-RAT Heterogeneous Network
- Authors:
- Debnath, Sanjoy
Jee, Anand
Sen, Debarati
Baishya, Srimanta
Arif, Wasim - Abstract:
- ABSTRACT: 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.
- Is Part Of:
- Applied artificial intelligence. Volume 35:Issue 15(2021)
- Journal:
- Applied artificial intelligence
- Issue:
- Volume 35:Issue 15(2021)
- Issue Display:
- Volume 35, Issue 15 (2021)
- Year:
- 2021
- Volume:
- 35
- Issue:
- 15
- Issue Sort Value:
- 2021-0035-0015-0000
- Page Start:
- 2246
- Page End:
- 2275
- Publication Date:
- 2021-12-15
- Subjects:
- Artificial intelligence -- Periodicals
006.3 - Journal URLs:
- http://www.tandfonline.com/toc/uaai20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/08839514.2021.1998300 ↗
- Languages:
- English
- ISSNs:
- 0883-9514
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1571.650000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21638.xml