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Novel protected sub-frame selection based interference mitigation and resource assignment in heterogeneous multi-cloud radio access networks
Bayessa, Gezahegn Abdissa1,2; Tyagi, Sumarga K. Sah1,2; Parashar, Vivek3; Gao, Mingjin1,2; Shi, Jinglin1,2
2018-12-01
发表期刊SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
ISSN2210-5379
卷号20页码:165-173
摘要The future network in a real environment is assumed to involve a radio access network comprising several clouds, as opposed to the single-cloud scenario in the recent cloud radio access network (CRAN) literature. Hence, this research presents the more favorable multi-cloud scenario to address the limited coverage and processing abilities of CRAN, in which inter-tier and inter-cloud interferences are considered and resource allocation is presented to enhance both the spectral and energy efficiencies. In order to mitigate interferences and enhance the spectral and energy efficiency (EE), we adopted protective sub-frame (PSF) based interference mitigation. To deal with that, part of the total sub-frames construct PSF matrix from which the combinations of sub-channels are selected to communicate with the edge low quality of service (QoS) users. In line with this, we introduced a novel sub-frame selection algorithm using the concept of cooperative game of learning automata, in which UEs can learn past sub-frame selection history from other neighboring UEs and updated their probability as indicative of the stochastic characteristics of the selected sub-frame to influence the next sub-frame selection. Accordingly, power allocation for the selected combination of sub-frames is formulated to allocate transmission power based on the received SINR. Furthermore, the objective problem is formulated as a non-convex energy-efficient resource assignment problem and the non-convex problem is efficiently converted to convex feasible problem utilizing the nonlinear fractional programming, upon which we then develop an efficient iterative algorithm. Finally, we evaluated the performance of our proposed model in terms of convergence, EE, and overall system capacity. For that, simulation is conducted and results confirm that the corresponding cooperative learning automata-based sub-frame selection enhances the EE significantly with faster convergence and improved system capacity. (C) 2018 Elsevier Inc. All rights reserved.
关键词Heterogeneous Multi-cloud radio access network Interference Cooperative learning automata Protected sub-frame selection Power allocation Energy efficiency
DOI10.1016/j.suscom.2018.02.009
收录类别SCI
语种英语
资助项目CAS-TWAS Presidents Fellowship
WOS研究方向Computer Science
WOS类目Computer Science, Hardware & Architecture ; Computer Science, Information Systems
WOS记录号WOS:000451756100016
出版者ELSEVIER SCIENCE BV
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文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/3541
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Bayessa, Gezahegn Abdissa
作者单位1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.MGCGV, Chitrakoot, India
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Bayessa, Gezahegn Abdissa,Tyagi, Sumarga K. Sah,Parashar, Vivek,et al. Novel protected sub-frame selection based interference mitigation and resource assignment in heterogeneous multi-cloud radio access networks[J]. SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS,2018,20:165-173.
APA Bayessa, Gezahegn Abdissa,Tyagi, Sumarga K. Sah,Parashar, Vivek,Gao, Mingjin,&Shi, Jinglin.(2018).Novel protected sub-frame selection based interference mitigation and resource assignment in heterogeneous multi-cloud radio access networks.SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS,20,165-173.
MLA Bayessa, Gezahegn Abdissa,et al."Novel protected sub-frame selection based interference mitigation and resource assignment in heterogeneous multi-cloud radio access networks".SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 20(2018):165-173.
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