Open AccessDecode and forward relaying for energy‐efficient multiuser cooperative cognitive radio network with outage constraints
Author(s) -
Naeem Muhammad,
Illanko Kandasamy,
Karmokar Ashok,
Anpalagan Alagan,
Jaseemuddin Muhammad
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2013.0119
Subject(s) - cognitive radio , computer science , mathematical optimization , fractional programming , telecommunications link , convergence (economics) , interference (communication) , iterative method , convex optimization , constraint (computer aided design) , power (physics) , telecommunications , wireless , nonlinear programming , algorithm , regular polygon , mathematics , nonlinear system , channel (broadcasting) , physics , geometry , quantum mechanics , economics , economic growth
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.