ResearchSpace

Load-driven resource allocation for enhanced interference mitigation in cellular networks

Show simple item record

dc.contributor.author Asaka, OT
dc.contributor.author Adejo, A
dc.contributor.author Onumanyi, Adeiza J
dc.contributor.author Bello-Salau, H
dc.contributor.author Oluwamotemi, FT
dc.date.accessioned 2022-05-04T19:38:08Z
dc.date.available 2022-05-04T19:38:08Z
dc.date.issued 2021-07
dc.identifier.citation Asaka, O., Adejo, A., Onumanyi, A.J., Bello-Salau, H. & Oluwamotemi, F. 2021. Load-driven resource allocation for enhanced interference mitigation in cellular networks. http://hdl.handle.net/10204/12385 . en_ZA
dc.identifier.isbn 978-1-6654-3493-5
dc.identifier.isbn 978-1-6654-3494-2
dc.identifier.uri DOI: 10.1109/ICMEAS52683.2021.9739816
dc.identifier.uri http://hdl.handle.net/10204/12385
dc.description.abstract Cellular users are often considered to be uniformly distributed within the communication network for the purposes of simplified analysis. Based on this assumption, the inter-cell interference experienced by users has been handled using soft frequency reuse (SFR) techniques. However, in real networks, the distribution of users in the network regions are not uniform. Therefore, analysis for random deployment of users under SFR is essential for improved accuracy of analysis and better handling of interference. This research presents an SFR algorithm (Load-Driven SFR) that intelligently adjusts resource allocation parameters (base station bandwidth assignment) according to the load distribution in the network. Interference mitigation is enhanced and Load-Driven SFR outperforms several implementations of the standard SFR algorithm using fixed bandwidth allocation, especially for edge user’s SINR (up to 3.2% improvement) and edge user’s Capacity (up to 202% improvement). en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9739816 en_US
dc.source 1st International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS), Abuja, Nigeria, 15-16 July 2021 en_US
dc.subject 5G networks en_US
dc.subject Algorithms en_US
dc.subject Cellular networks en_US
dc.subject Frequency reuse en_US
dc.subject Network load en_US
dc.subject Resource allocation en_US
dc.subject Simulation en_US
dc.subject Soft frequency reuse en_US
dc.subject User distribution en_US
dc.title Load-driven resource allocation for enhanced interference mitigation in cellular networks en_US
dc.type Conference Presentation en_US
dc.description.pages 6pp en_US
dc.description.note Copyright: 2021 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9739816 en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea Advanced Internet of Things en_US
dc.identifier.apacitation Asaka, O., Adejo, A., Onumanyi, A. J., Bello-Salau, H., & Oluwamotemi, F. (2021). Load-driven resource allocation for enhanced interference mitigation in cellular networks. http://hdl.handle.net/10204/12385 en_ZA
dc.identifier.chicagocitation Asaka, OT, A Adejo, Adeiza J Onumanyi, H Bello-Salau, and FT Oluwamotemi. "Load-driven resource allocation for enhanced interference mitigation in cellular networks." <i>1st International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS), Abuja, Nigeria, 15-16 July 2021</i> (2021): http://hdl.handle.net/10204/12385 en_ZA
dc.identifier.vancouvercitation Asaka O, Adejo A, Onumanyi AJ, Bello-Salau H, Oluwamotemi F, Load-driven resource allocation for enhanced interference mitigation in cellular networks; 2021. http://hdl.handle.net/10204/12385 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Asaka, OT AU - Adejo, A AU - Onumanyi, Adeiza J AU - Bello-Salau, H AU - Oluwamotemi, FT AB - Cellular users are often considered to be uniformly distributed within the communication network for the purposes of simplified analysis. Based on this assumption, the inter-cell interference experienced by users has been handled using soft frequency reuse (SFR) techniques. However, in real networks, the distribution of users in the network regions are not uniform. Therefore, analysis for random deployment of users under SFR is essential for improved accuracy of analysis and better handling of interference. This research presents an SFR algorithm (Load-Driven SFR) that intelligently adjusts resource allocation parameters (base station bandwidth assignment) according to the load distribution in the network. Interference mitigation is enhanced and Load-Driven SFR outperforms several implementations of the standard SFR algorithm using fixed bandwidth allocation, especially for edge user’s SINR (up to 3.2% improvement) and edge user’s Capacity (up to 202% improvement). DA - 2021-07 DB - ResearchSpace DP - CSIR J1 - 1st International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS), Abuja, Nigeria, 15-16 July 2021 KW - 5G networks KW - Algorithms KW - Cellular networks KW - Frequency reuse KW - Network load KW - Resource allocation KW - Simulation KW - Soft frequency reuse KW - User distribution LK - https://researchspace.csir.co.za PY - 2021 SM - 978-1-6654-3493-5 SM - 978-1-6654-3494-2 T1 - Load-driven resource allocation for enhanced interference mitigation in cellular networks TI - Load-driven resource allocation for enhanced interference mitigation in cellular networks UR - http://hdl.handle.net/10204/12385 ER - en_ZA
dc.identifier.worklist 25656 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record