Distributed recursive energy detection

Ainomae, Ahti; Trump, Tonu; Bengtsson, Mats

doi:10.1109/wcnc.2014.6952327

Cited by 6 publications

(10 citation statements)

References 13 publications

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“…In the ring-around topology [15], the power estimates are exchanged circularly between the nodes. At time instant n, node k has access only to one estimateP (k−1)modK (n) from the node (k − 1)modK for calculatingP k (n + 1).…”

Section: Network Topologiesmentioning

confidence: 99%

“…First we derive a general model for Special Session on Recent Advances in Broadband Access Networks 2014 analysing the mean and variance of the estimates of the ATC, CTA [16] and ring-around [15] algorithms in one framework. Next we analyse the resulting energy detection performance.…”

Section: Performance Analysismentioning

confidence: 99%

“…According to [19,Lemma 5.6.11], if for a matrix norm it holds that L 2 (I − M) L 1 < 1 (15) then lim n→∞ [L 2 (I − M )L 1 ] n → 0. Thus given the doubly stochastic matrices L 1 , L 2 and C, the choice of step sizes in M should guarantee that the stability condition (15) holds.…”

Section: A Mean Of Estimatesmentioning

confidence: 99%

“…In [15] we proposed and analysed an estimation based recursive calculation of the test statistics for the energy detectors in cognitive radio network with ring topology. The test statistic in form of a converged power estimate is the soft information used for making the detection decision at every node.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we analyse the Adapt and Combine (ATC) version of diffusion LMS type of received power estimation algorithm. The performance of the ATC diffusion based distributed power estimator is compared with the previously proposed CTA [16] and ring [15] schemes to complete the analysis. The resulting energy detection performance is studied and is dependent on the performance of the used distributed recursive power estimation algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Distributed diffusion LMS based energy detection

Ainomae

Trump

Bengtsson

2014

2014 6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

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Cognitive radio (CR) is seen as a promising technology to make radio spectrum usage more effective by providing an opportunistic access for secondary users to the licensed spectrum areas. CR systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. This paper studies distributed spectrum sensing in a cognitive radio context. We investigate distributed energy detection schemes without using any fusion center. We propose the usage of distributed, diffusion least mean square (LMS) type of power estimation algorithms. In this paper an Adapt and Combine (ATC) diffusion based power estimation scheme is proposed and the performance is compared with the Combine and Adapt (CTA) and ring-around schemes in a common framework. The PU signal is assumed to be slowly fading. We analyse the resulting energy detection performance and verify the theoretical findings through simulations.

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Section: Network Topologiesmentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

Section: A Mean Of Estimatesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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