A novel adaptive fuzzy-based sliding mode control for channel state estimation in cognitive radio for reduction of interference. (7th May 2020)

• Record Type: Journal Article
• Authors: Vadivukkarasi, S.; Santhi, S.
• Is Part Of: International journal of networking and virtual organisations. Volume 23:Number 4(2020)
• Page Start: 358
• Page End: 372
• Publication Date: 2020-05-07
• Subjects: cognitive radio -- channel state information -- sliding mode control -- SMC -- adaptive fuzzy -- bit error rate; Computer networks -- Periodicals; Information networks -- Periodicals; Virtual corporations -- Periodicals; Electronic commerce -- Periodicals; Management information systems -- Periodicals; Management -- Data processing -- Periodicals; 004.65
• Languages: English
• ISSNs: 1470-9503

Abstract

Research in spectrum availability and its effective utilisation is becoming an epicentre of research in recent times with the increasing scarcity of radio spectrum. An effective solution is in the form of cognitive radios (CRs) which are quite intelligent to effectively utilise the scarcely available spectrum in an efficient and economic manner. Apart from being intelligent, they represent reconfigurable wireless communication systems, which are self-aware of their environment and learn to adapt it for dynamic changes. They are characteristic of efficient spectrum utilisation. This research paper defines the objective of determining the channel state information through sliding model control-based intelligent adaptive fuzzy algorithm. The CR has ability to operate in a particular radio configuration based on device status and environmental aspects including interference noise. The proposed adaptive fuzzy SMC-based channel state estimation has been compared against conventional and recent techniques and outputs established in terms of bit error rate and mean squared error. The proposed sliding rule method is quite an ideal choice for the proposed scenario characterised by dynamically changing input conditions to the sensing components of the CR network.