Pseudo BER Based SNR Estimation for Energy Detection Scheme in Cognitive Radio

2013 IEEE Global Communications Conference (GLOBECOM)

Ottersten

2013

Abstract-In addition to spectrum sensing capability required by a Cognitive Radio (CR), Signal to Noise Ratio (SNR) estimation of the primary signals is crucial in order to adapt its coverage area dynamically using underlay techniques. Furthermore, in practical scenarios, the fading channel may be correlated due to various causes such as insufficient scattering in the propagation path and antenna mutual coupling. In this context, we consider the SNR estimation problem for a CR in the presence of channel correlation. We study an eigenvaluebased SNR estimation technique for large-scale CR networks using asymptotic Random Matrix Theory (RMT). We carry out detailed theoretical analysis of the signal plus noise hypothesis to derive the asymptotic eigenvalue probability distribution function (a.e.p.d.f.) of the received signal's covariance matrix in the presence of the correlated channel. Then an SNR estimation technique based on the derived a.e.p.d.f. is proposed for PU SNR in the presence of channel correlation and its performance is evaluated in terms of normalized Mean Square Error (MSE). It is shown that the PU SNR can be accurately estimated in the presence of channel correlation using the proposed technique even in low SNR region.

Section: Snr Estimation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Eigenvalue based SNR estimation for cognitive radio in presence of channel correlation

2013 IEEE Global Communications Conference (GLOBECOM)

Ottersten

2013

“…Furthermore, the PU SNR knowledge provides channel quality information for the secondary system, which can be further used for implementing adaptive techniques such as adaptive bit loading, handoff algorithms and optimal soft value calculation for improving the performance of channel decoders [17]. Despite its important applications, only a few contributions in the literature address the SNR estimation problem in the context of a CR [18][19][20][21]. Furthermore, the SNR estimation techniques proposed under the assumption of the white noise and uncorrelated channel scenario may not perform well in the presence of channel/noise correlation.…”

Section: A Motivation and Contributionsmentioning

confidence: 99%

“…In [19], a pseudo bit error rate based SNR estimation has been proposed for the ED scheme. The contribution in [20] utilizes the priori knowledge of SNR, which can be obtained using estimation techniques, for realizing the adaptive SS techniques.…”

Section: Related Workmentioning

confidence: 99%

SNR Estimation for Multi-dimensional Cognitive Receiver under Correlated Channel/Noise

IEEE Trans. Wireless Commun.

Ottersten

2013

Abstract-In addition to Spectrum Sensing (SS) capability required by a Cognitive Radio (CR), Signal to Noise Ratio (SNR) estimation of the primary signals at the CR receiver is crucial in order to adapt its coverage area dynamically using underlay techniques. In practical scenarios, channel and noise may be correlated due to various reasons and SNR estimation techniques with the assumption of white noise and uncorrelated channel may not be suitable for estimating the primary SNR. In this paper, firstly, we study the performance of different eigenvaluebased SS techniques in the presence of channel or/and noise correlation. Secondly, we carry out detailed theoretical analysis of the signal plus noise hypothesis to derive the asymptotic eigenvalue probability distribution function (a.e.p.d.f.) of the received signal's covariance matrix under the following two cases: (i) correlated channel and white noise, and (ii) correlated channel and correlated noise, which is the main contribution of this paper. Finally, an SNR estimation technique based on the derived a.e.p.d.f is proposed in the presence of channel/noise correlation and its performance is evaluated in terms of normalized Mean Square Error (MSE). It is shown that the PU SNR can be reliably estimated when the CR sensing module is aware of the channel/noise correlation.

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Bogale

IEEE Commun. Surv. Tutorials

et al. 2015

200

111

Abstract-Cognitive Radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, regulatory and standardization bodies have put their significant efforts towards the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, synchronization issues, etc. may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions towards combating various practical imperfections is very important for successful implementation of the cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches towards addressing these imperfections. Finally, it provides some interesting open research issues.