Compressive autonomous sensing (CASe) for wideband spectrum sensing

Hongjian Sun, Arumugam Nallanathan, Jing Jiang, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Compressive spectrum sensing techniques present many advantages over traditional spectrum sensing approaches, e.g., low sampling rate, and reduced energy consumption. However, when the spectral sparsity level is unknown, there are two significant challenges. They are: 1) how to choose an appropriate number of measurements, and 2) when to terminate the greedy recovery algorithm. In this paper, a compressive autonomous sensing (CASe) framework is presented that gradually acquires the wideband signal using sub-Nyquist rate. Further, a sparsity-aware recovery algorithm is proposed to reconstruct the full spectrum while solving the problem of under-fitting or over-fitting. Simulation results show that the proposed system can not only reconstruct the spectrum using the appropriate number of measurements, but also considerably improve the recovery performance when compared with the existing approaches.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Communications, ICC 2012
Pages4442-4446
Number of pages5
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE International Conference on Communications, ICC 2012 - Ottawa, ON, Canada
Duration: Jun 10 2012Jun 15 2012

Other

Other2012 IEEE International Conference on Communications, ICC 2012
CountryCanada
CityOttawa, ON
Period6/10/126/15/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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