Impact of channel estimation error on decentralized detection in bandwidth constrained wireless sensor networks

This paper describes about the performance analysis and comparison between hard decision (majority rule) logic and soft decision (maximal ratio combining) logic approaches using cooperative spectrum sensing (CSS) with censoring scheme. We have considered both sensing channel (S-channel) and reporting channel (R-channel) are affected by Rician fading. Radio links present in the channel gets heavily faded and the information received at the fusion center (FC) becomes erroneous because of fading effect present in the channel. Threshold based censoring scheme is used to eliminate the heavily faded cognitive radios (CRs) in R-channel. Two fusion rules namely, majority logic and maximal ratio combining (MRC) are considered individually at the fusion center to estimate the performance of CSS by censoring of R-channel links. The performance is evaluated in terms of missed detection probability (Q m ) and total error probability (Q m þ Q f ) in both majority logic and MRC logic. Comparison table between perfect and imperfect channels is provided to know which fusion rule (MRC, majority) performs better under Rician fading. Simulations are performed under both perfect and imperfect channels by varying the network parameters like probability of false alarm (P f ), S-channel SNR, R-channel SNR, Rician fading parameter (K) and number of CR users (N).

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“…Only 'k' CRs send their information to FC and MRC logic is applied as follows. MRC logic can be obtained by simplifying LRT fusion rule [26]:…”

Section: Maximal Ratio Combining (Mrc) Rulementioning

confidence: 99%

Threshold Based Censoring of Cognitive Radios in Rician Fading Channel

Ranjeeth

Anuradha

2016

Wireless Pers Commun

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“…The signal from k-th CR user received at the FC is: (6) where represent the bit energy of the each CR, in case of BPSK signal that bit energy values indicated as ( and -), corresponding and , respectively. We are considering R-channel also Hoyt faded and that fading coefficient is modeled as a zero-mean complex Gaussian random variable with variance, , i.e., CN(0, )as in [10] and noise present in the channel is considered as zero-mean complex Gaussian noise with variance, , CN(0, ). Let us consider that { } and are mutually independent.…”

Section: System Modelmentioning

confidence: 99%

“…Let us consider that { } and are mutually independent. Fading coefficients present in the R-channel are estimated by MMSE estimation strategy, then as follows [10]: In the above equations, represents the estimated value of fading coefficient ( ) after using MMSE estimation and represents the bit energy of Rchannel radio link. Finally, the channel estimation error can be calculated by taking the difference between the actual fading coefficient and the estimated channel coefficient i.e.…”

Section: System Modelmentioning

confidence: 99%

“…= . We assume that the estimation error has zero mean complex Gaussian random variable and the variance is given as [10]:…”

Section: System Modelmentioning

confidence: 99%

“…After censoring scheme, all the uncensored signals are received at the FC. The received form of k-th selected CR is (10) where channel noise 2 CN(0, ) k n n σ and is the BPSK modulated binary decisions.…”

Section: System Modelmentioning

confidence: 99%

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Rank based censoring of cognitive radios with cooperative spectrum sensing under hoyt fading channel

Ranjeeth

Anuradha

2015

2015 International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT)

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Performance of cooperative spectrum sensing with hard decision fusion technique (majority logic) has been evaluated under Hoyt fading environment with the application of censoring scheme. In this paper we have considered Hoyt fading in both reporting channel (R-channel) and sensing channel (S-channel). In a cooperative spectrum sensing (CSS) scheme, the detection primary user (PU) activity is improved by eliminating the heavily faded cognitive radio (CR) users. CRs which are heavily faded those are eliminated by using censoring scheme in the R-channel. Rank based censoring scheme is used to censors the CRs in the presence of Hoyt fading in both perfect and imperfect channels. A hard decision based fusion technique called majority logic rule is considered at the fusion center (FC) to evaluate the performance using missed detection probability and total error probability ( ). This has been performed in both perfect and imperfect channels by varying the network parameters like: probabilities of false alarm ( ), R-channel SNR, S-channel SNR and Hoyt fading parameter (q).

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