A virtual control layer resource allocation framework for heterogeneous cognitive radio network
dc.contributor.author | Wang, Shi | |
dc.contributor.author | Maharaj, Bodhaswar Tikanath Jugpershad | |
dc.contributor.author | Alfa, Attahiru Sule | |
dc.contributor.email | sunil.maharaj@up.ac.za | en_ZA |
dc.date.accessioned | 2020-02-05T06:27:47Z | |
dc.date.available | 2020-02-05T06:27:47Z | |
dc.date.issued | 2019 | |
dc.description.abstract | To make best use of the various radio resources in the heterogeneous network enabled by the software de ned network or cognitive radio (CR) technology, a resource allocation framework with exibility and quick recon gurability in the network control layer is an important issue. In this paper, the authors propose a channel allocation framework with con gurable objectives and high computing ef ciency in the complicated context of a multi-user multi-channel CR network cell. First, a channel allocation protocol named the distribution probability matrix (DPM) is applied to model the channel allocation scenarios quantitatively. Then, a queueing analytical framework using DPM is built to model the CR system and comprehensive performance evaluations of every individual secondary user are obtained separately. An overall performance evaluation of the CR system is carried out using the concept of weighted throughput, which is introduced to represent the importance of the users and the feature to distinguish different types of users. Then, a parameter named overtime probability (OP) is introduced to describe the measure of delay approximately with high computing ef ciency. Thereby, an optimization of the system is formulated to maximize the overall weighted throughput under delay constraints represented by OP and a hill climbing algorithm is developed to nd the solution in terms of DPM. The numerical results reveal how to allocate the resources to achieve the optimization objective under various system settings and prove the computing ef ciency of the framework. | en_ZA |
dc.description.department | Electrical, Electronic and Computer Engineering | en_ZA |
dc.description.librarian | am2020 | en_ZA |
dc.description.sponsorship | The Sentech Chair in BWMC and DTI THRIP Program. | en_ZA |
dc.description.uri | http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 | en_ZA |
dc.identifier.citation | Wang, S., Maharaj, S. & Alfa, A.S. 2019, 'A virtual control layer resource allocation framework for heterogeneous cognitive radio network', IEEE Access, vol. 7, pp. 111605-111616. | en_ZA |
dc.identifier.issn | 2169-3536 (online) | |
dc.identifier.other | 10.1109/ACCESS.2019.2935126 | |
dc.identifier.uri | http://hdl.handle.net/2263/73112 | |
dc.language.iso | en | en_ZA |
dc.publisher | Institute of Electrical and Electronics Engineers | en_ZA |
dc.rights | This work is licensed under a Creative Commons Attribution 4.0 License. | en_ZA |
dc.subject | Control layer | en_ZA |
dc.subject | Delay | en_ZA |
dc.subject | Hill climbing algorithm | en_ZA |
dc.subject | Optimization | en_ZA |
dc.subject | Resource allocation | en_ZA |
dc.subject | Weighted throughput | en_ZA |
dc.subject | Cognitive radio (CR) | en_ZA |
dc.subject | Distribution probability matrix (DPM) | en_ZA |
dc.subject | Overtime probability (OP) | en_ZA |
dc.title | A virtual control layer resource allocation framework for heterogeneous cognitive radio network | en_ZA |
dc.type | Article | en_ZA |