Joint spectrum sensing, power, and bandwidth allocation for multiband cognitive radio systems. Issue 19 (14th October 2020)

• Record Type: Journal Article
• Authors: Karimi, Mohammad; Ahmadi, Shadi
• Is Part Of: IET communications. Volume 14:Issue 19(2020)
• Page Start: 3490
• Page End: 3497
• Publication Date: 2020-10-14
• Subjects: cognitive radio -- bandwidth allocation -- signal detection -- radio spectrum management -- linear programming -- convex programming -- resource allocation -- concave programming -- radiofrequency interference -- channel allocation; CR networks -- unused frequency bands -- joint spectrum sensing -- power allocation -- CR systems -- CR transmission -- multiband CR system -- average opportunistic CR data rate -- power budget -- nonconvex optimisation problem -- convex problem -- bandwidth allocation -- average achievable CR data rate -- multiband cognitive radio systems -- multiband cognitive radio signalling -- resource allocation -- Lagrange multiplier method -- linear programming; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.1305
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Multiband cognitive radio (CR) signalling allows CR networks to efficiently take advantage of the unused frequency bands. On the other hand, joint spectrum sensing and power allocation in CR systems has been shown to enable higher opportunities for CR transmission. In this work, the authors perform joint spectrum sensing and resource allocation (power and bandwidth) in a multiband CR system. This is achieved by defining an optimisation problem, which is formulated to maximise the average opportunistic CR data rate under constraints on interference, power budget, and total available bandwidth leading to a non‐convex optimisation problem. As the original formulated optimisation problem is inherently non‐convex, they convert it into a convex problem where the optimal solution is obtained using the Lagrange multipliers method and linear programming. For performance comparison, they consider the classical method based on equal bandwidth allocation for each subchannel. They provide several numerical results to contrast the performance of the proposed method compared to the classical method in terms of the average achievable CR data rate.