2013 Seventh International Conference on Next Generation Mobile Apps, Services and Technologies 2013
DOI: 10.1109/ngmast.2013.50
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Throughput Optimization for Cooperative Spectrum Sensing in Cognitive Radio Networks

Abstract: In this paper, the channel utilization (throughput vs sensing time relationship) is analyzed for cooperative spectrum sensing under different combining rules and scenarios. The combining rules considered in this study are the OR hard combining rule, AND the hard combining rule, the Equal Gain Soft combining rule and the two-bit quantized (softened hard) combining rule. For all combining rules, the detection performance, with a Gaussian distribution assumption, is expressed in two different scenarios, CPUP (Con… Show more

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Cited by 34 publications
(29 citation statements)
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“…It is also important to note that most of the research efforts on different fusion rules for cooperative sensing are analytical and/or Matlab simulations based [3]- [5]. Recently a few measurement-based studies on cooperative sensing can be found in [6]- [8].…”
Section: This Paper Is a Revised And Expanded Version Of The Paper Prmentioning
confidence: 99%
“…It is also important to note that most of the research efforts on different fusion rules for cooperative sensing are analytical and/or Matlab simulations based [3]- [5]. Recently a few measurement-based studies on cooperative sensing can be found in [6]- [8].…”
Section: This Paper Is a Revised And Expanded Version Of The Paper Prmentioning
confidence: 99%
“…In the propose model we have used OR rule because it has better detection performance when the number of cooperating CR users is large. [12], and provides slightly better performance at low Pf [13].…”
Section: Introductionmentioning
confidence: 97%
“…DFC combines those decisions and makes a final decision [18]. Different conventional diversity techniques are used to combine the independent decision which are discussed in [19] and [20]. In this paper, we have considered Maximal Ratio Combining (MRC) scheme with Energy and Bayesian detection.…”
Section: Introductionmentioning
confidence: 99%