Open AccessEquivalent convex optimisation approach for green cognitive radio‐based cooperative networks
Author(s) -
Soleimanpourmoghadam Mohadese,
Esmaeili Shima,
Talebi Siamak
Publication year - 2018
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.2017.0870
Subject(s) - cognitive radio , mathematical optimization , computer science , lexicographical order , fractional programming , convex optimization , transformation (genetics) , throughput , convex function , regular polygon , nonlinear programming , mathematics , telecommunications , wireless , nonlinear system , biochemistry , chemistry , physics , geometry , combinatorics , quantum mechanics , gene
Ensuring total rate maximisation whilst keeping Greenhouse gas emission (GHGE) at a minimum in green cooperative cognitive radio networks is key to achieving maximum network quality. This study employs the multi‐objective lexicographic algorithm to a proposed multi‐objective optimisation problem scheme to deal with these conflicting objectives through two consecutive steps. The challenge posed by maximum throughput – a complex non‐convex optimisation problem – is first resolved through a mathematical manipulation resulting in a fractional programming model which is then converted to its simplified convex programming equivalent by applying the Charnes–Cooper transformation. Next, the GHGE minimisation issue is tackled effectively by applying a convex programming. Simulation results confirm that the proposed approach offers superior performance compared to well‐known schemes in terms of throughput gain and emission quality.