Connectivity of Cognitive Radio Networks: Proximity vs. Opportunity

Abstract

We address the connectivity of large-scale ad hoc cognitive radio networks in which secondary users exploit channels that are temporarily and locally unused by primary users. In ad hoc cognitive radio networks the existence of a communications link between two secondary users depends not only on the distance between them, but also on the transmitting and receiving activities of nearby primary users. We introduce the concept of "connectivity region," which is defined as the set of density pairs -- the density of the secondary users and the density of the primary transmitters -- under which the secondary network is connected. Using theories and techniques from continuum percolation (i.e., the coupling argument, ergodic theory, and certain combinatorial results), we analytically characterize the connectivity region of the secondary network and show its three basic properties: contiguity, the monotonicity of the boundary, and the uniqueness of the infinite connected component. Furthermore, we reveal the tradeoff between proximity (the number of neighbors) and the occurrence of spectrum opportunities by studying the impact of the secondary users' transmission power on the connectivity region of the secondary network, and design the transmission power of the secondary users to maximize their tolerance to the primary traffic load. The presentation contains briefing charts.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2009
Accession Number
ADA554758

Entities

People

  • Ananthram Swami
  • Qing Zhao
  • Wei Ren

Organizations

  • University of California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Ad Hoc Networks
  • Boundaries
  • Cognitive Radio
  • Communication Channels
  • Couplings
  • Heterogeneous Networks
  • Mesh Networks
  • Military Research
  • Networks
  • Percolation
  • Probability
  • Spectra
  • Transmitters
  • Transmitting
  • Two Dimensional
  • Wireless Networks

Readers

  • Graph Algorithms and Convex Optimization.
  • Radio communications and signal processing.
  • Systems Analysis and Design