Enhanced Dynamic Spectrum Access in Multiband Cognitive Radio Networks via Optimized Resource Allocation

Piyush Bhardwaj, Ankita Panwar, Onur Ozdemir, Engin Masazade, Irina Kasperovich, Andrew L. Drozd, Chilukuri K. Mohan, Pramod K. Varshney

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

In this paper, we address the constrained resource allocation problems arising in the context of spectrum sharing in cognitive radio networks utilizing a multi-dimensional formulation. Given the activity of the primary users (PUs), we consider multiple objectives and constraints, viz., sum rate, fairness, number of active secondary users (SUs), power consumption, and quality of service requirements (of both PUs and SUs). The three dimensions for the optimization task are the assignment of power, frequency, and antenna directionality to various SUs. Efficient heuristic algorithms are developed for five variations of the NP-hard optimization problems. Solution quality tradeoffs are shown for three algorithms, viz., convex relaxation with tree pruning, convex relaxation with gradual removal, and a genetic algorithm (GA); results show that the GA provides a reasonable balance between solution quality and computational effort. The multi-objective problems are solved using a modification of the NSGA-II evolutionary algorithm, obtaining a set of Pareto-optimal solutions under computational constraints.

Original languageEnglish (US)
Article number7574388
Pages (from-to)8093-8106
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume15
Issue number12
DOIs
StatePublished - Dec 2016

Keywords

  • Cognitive radio
  • evolutionary computation
  • genetic algorithms
  • pareto optimization
  • radio spectrum management

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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