Decode and forward relaying for energy‐efficient multiuser cooperative cognitive radio network with outage constraints. Issue 5 (1st March 2014)

• Record Type: Journal Article
• Authors: Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad
• Is Part Of: IET communications. Volume 8:Issue 5(2014)
• Page Start: 578
• Page End: 586
• Publication Date: 2014-03-01
• Subjects: cognitive radio -- convex programming -- iterative methods -- radio networks -- decode and forward communication -- relay networks (telecommunication); decode and forward relaying -- energy efficient multiuser cooperative cognitive radio network -- outage constraints -- optimal allocation -- downlink cooperative cognitive radio network -- nonlinear non convex fractional programming problem -- interference constraints -- concave fractional programme -- Charnes‐Cooper transformation -- iterative algorithm -- parametric transformation -- optimal convergence; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2013.0119
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : We investigate the optimal allocation of power in the downlink cooperative cognitive radio network using decode and forward (DF) relaying technique. The power allocation in DF relaying for green cooperative cognitive radio with an objective of maximising energy‐efficiency is a constraint non‐linear non‐convex fractional programming problem. The optimisation needs to satisfy the primary users interference constraints and secondary users outage constraints. The authors present the optimal power allocation in DF relaying by transforming the constraint non‐linear non‐convex fractional power allocation problem into a concave fractional programme by using Charnes–Cooper transformation. The authors also present an iterative algorithm that uses parametric transformation and guarantees ε ‐optimal convergence. The convergence of the iterative algorithm is proved and numerical results obtained for cooperative cognitive radio network are presented with different network parameter settings.