Efficient spectrum availability information recovery for wideband dsa networks: A weighted compressive sampling approach

Bassem Khalfi*, Bechir Hamdaoui, Mohsen Guizani, Nizar Zorba

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

There have recently been research efforts that leverage compressive sampling to enable wideband spectrum sensing recovery at sub-Nyquist rates. These efforts consider homogenous wideband spectrum, where all bands are assumed to have similar primary user traffic characteristics. In practice, however, wideband spectrum is not homogeneous, in that different bands could present different occupancy patterns. In fact, applications of similar types are often assigned spectrum bands within the same block, dictating that wideband spectrum is indeed heterogeneous. In this paper, we consider heterogeneous wideband spectrum and exploit its inherent block-like structure to design efficient compressive spectrum sensing techniques that are well suited for heterogeneous wideband spectrum. We propose a weighted ℓ(1) -minimization sensing information recovery algorithm that achieves more stable recovery than that achieved by existing approaches, while accounting for the variations of spectrum occupancy across both the time and frequency dimensions. In addition, we show that our proposed algorithm requires a smaller number of sensing measurements when compared to the state-of-the-art approaches.

Original languageEnglish
Pages (from-to)2162-2172
Number of pages11
JournalIEEE Transactions on Wireless Communications
Volume17
Issue number4
DOIs
Publication statusPublished - Apr 2018
Externally publishedYes

Keywords

  • Wideband spectrum sensing
  • compressive sampling
  • heterogeneous wideband spectrum occupancy

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