Energy-Infeasibility Tradeoff in Cognitive Radio Networks: Price-Driven Spectrum Access Algorithms

Xiangping Zhai, Liang Zheng, Chee Wei Tan

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

46 Citations (Scopus)

Abstract

We study the feasibility of the total power minimization problem subject to power budget and Signal-to-Interference-plus-Noise Ratio (SINR) constraints in cognitive radio networks. As both the primary and the secondary users are allowed to transmit simultaneously on a shared spectrum, uncontrolled access of secondary users degrades the performance of primary users and can even lead to system infeasibility. To find the largest feasible set of secondary users (i.e., the system capacity) that can be supported in the network, we formulate a vector-cardinality optimization problem. This nonconvex problem is however hard to solve, and we propose a convex relaxation heuristic based on the sum-of-infeasibilities in optimization theory. Our methodology leads to the notion of admission price for spectrum access that can characterize the tradeoff between the total energy consumption and the system capacity. Price-driven algorithms for joint power and admission control are then proposed that quantify the benefits of energy-infeasibility balance. Numerical results are presented to show that our algorithms are theoretically sound and practically implementable.
Original languageEnglish
Article number6678826
Pages (from-to)528 - 538
JournalIEEE Journal on Selected Areas in Communications
Volume32
Issue number3
Online published5 Dec 2013
DOIs
Publication statusPublished - Mar 2014

Research Keywords

  • Optimization
  • cognitive radio networks
  • spectrum access control
  • power and admission control

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