Ali, A, Abbas, L, Shafiq, M, Bashir, AK ORCID: https://orcid.org/0000-0001-7595-2522, Afzal, MK, Liaqat, HB, Siddiqi, MH and Kwak, KS (2019) Hybrid Fuzzy Logic Scheme for Efficient Channel Utilization in Cognitive Radio Networks. IEEE Access, 7. pp. 24463-24476.
|
Published Version
Available under License In Copyright. Download (2MB) | Preview |
Abstract
© 2013 IEEE. The proliferation of mobile devices and the heterogeneous environment of wireless communications have increased the need for additional spectrum for data transmission. It is not possible to altogether allocate a new band to all networks, which is why fully efficient use of the already available spectrum is the demand of the day. Cognitive radio (CR) technology is a promising solution for efficient spectrum utilization, where CR devices, or secondary users (SUs), can opportunistically exploit white spaces available in the licensed channels. SUs have to immediately vacate the licensed channel and switch to another available channel when they detect the arrival of the incumbent primary user. However, performance for the SU severely degrades if successive channel switching happens. Moreover, taking the channel-switching decisions based on crisp logic is not a suitable approach in the brain-empowered CR networks (CRNs) where sensing information is not only imprecise and inaccurate but also involves a major uncertainty factor. In this paper, we propose a fuzzy logic-based decision support system (FLB-DSS) that jointly deals with channel selection and channel switching to enhance the overall throughput of CRNs. The proposed scheme reduces the SU channel switching rate and makes channel selection more adaptable. The performance of the proposed scheme is evaluated using a Matlab simulator, and a comprehensive comparison study with a baseline scheme is presented. The simulation results are promising in terms of the throughput and the number of handoffs and making our proposed FLB-DSS a good candidate mechanism for SUs while making judicious decisions in the CR environment.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.