Spectrum Exploration and Exploitation for Cognitive Radio: Recent Advances

Jarmo Lundén, Visa Koivunen, H. Vincent Poor

Research output: Contribution to journalReview article

61 Scopus citations

Abstract

The lack of availability of radio spectrum for wireless communication purposes is becoming a serious problem as more wireless systems and services are being developed and operate in crowded spectral bands. The scarcity of useful radio spectrum is mainly due to the static allocation and rigid regulation of the spectrum use rather than the spectrum being actually fully in use. Flexible spectrum use and cognitive radio technologies provide an approach to alleviating this problem by allowing for secondary spectrum use while the spectrum is underutilized by its primary licensed users. Idle spectrum is a time-frequency-location varying resource. It is a resource that also depends on the relative locations of the primary and secondary receivers and transmitters as well as the instantaneous propagation conditions. By acquiring awareness about the current radio environment and the other spectrum users, cognitive radios can more efficiently exploit idle spectrum and manage interference. Doing so requires a means to explore the spectrum to identify high-quality and persistent local spectral resources and access and share them among a number of users while strictly controlling the interference caused to others, in particular, licensed primary users (PUs). Situational awareness about the state of the spectrum allows for optimal exploitation of underutilized spectrum. For example, idle subbands may be allocated, and waveform parameters may be chosen to maximize the sum-rate for the cognitive users while making sure no harmful interference is caused to the other users of the spectrum.

Original languageEnglish (US)
Article number7079578
Pages (from-to)123-140
Number of pages18
JournalIEEE Signal Processing Magazine
Volume32
Issue number3
DOIs
StatePublished - May 1 2015

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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