Conference Paper

Spectrum Sensing via Energy Detector in Low SNR

Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
DOI: 10.1109/icc.2011.5963316 Conference: Communications (ICC), 2011 IEEE International Conference on
Source: IEEE Xplore

ABSTRACT As required in the IEEE 802.22 proposal, spectrum sensing techniques should be capable enough to sense the primary signal with very low receiver sensitivity such as at -116 dBm. In this paper, the detection performance of an energy detector used for spectrum sensing in cognitive radio networks is investigated under such very low signal-to-noise ratio (SNR) levels. The analysis focuses on the derivation of a closed-form expression for the average missed-detection probability over Rayleigh fading and Nakagami-m fading channels. Subsequently, the detection threshold is optimized for minimizing the total error rate. The analysis is validated by numerical and simulation results. The sensing requirements defined in IEEE 802.22 are also discussed with numerical examples.

1 Follower
  • [Show abstract] [Hide abstract]
    ABSTRACT: Energy Detection (ED) is a well known approach for spectrum sensing due to its simplicity, low computational cost and its validity for all signal formats. However, it is ineffective under low signal to noise ratio conditions. On the other hand, the recent convergence of almost all the wireless standards to the incorporation of spatial dimension in these wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. Though it works well under all channel conditions but the related cost is high computational complexity of the algorithm. With the motivation of improving the sensing ability of cognitive radio under all channel conditions combined with the existing hardware constraints of low computational complexity, we have proposed an amalgamation of the aforementioned schemes (ED and PAPR based spatial spectrum sensing) with an element of adaptation by switching between these two techniques depending upon channel states. Proposed adaptive scheme is compared with ED and PAPR based spatial spectrum sensing on the basis of probability of detection, probability of false alarm and complexity.
    Consumer Communications and Networking Conference (CCNC), 2013 IEEE; 01/2013
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite its simplicity, drawback for the application of energy detection for spectrum sensing in cognitive radio is its poor performance in noise of uncertain power. In this paper we proposed a HOS based spectrum sensing method for cognitive radio network that give better performance than energy detection in noise of uncertain power. The proposed method based on distribution analysis as test statistic. The distribution of received signal traveling via wireless channel tends to have non gaussian distribution which will be different to the Gaussian noise. Sensing algorithm was tested using captured DTV signal. Result shows that our method performs well in the noise of uncertain power even at low SNR.
    IcoICT 2014; 05/2014
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: From the last decade much more emphasis were drawn to develop robust Cognitive Radio Networks (CRNs). For robust CRNs, Spectrum Sensing is one of the most important issue for its better existence in licensed spectrum. Spectrum sensing is used for finding unoccupied frequency bands, called white space or spectrum holes. However, spectrum sensing performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues due to low signal to noise ratio (SNR). In this paper, we propose a robust double threshold feature detector (DTFD) that detect even very low SNR primary user. Here we have used DTFD in cooperative spectrum sensing scenario in cognitive radio networks (CRNs) on a additive white Gaussian noise (AWGN) channel. Here individual detectors employ double threshold method in feature based detection of Orthogonal Frequency Division Multiplexing (OFDM) signal, and sends their results to fusion center (FC) where final decision takes place. Detection is done by using popular autocorrelation property of cyclic prefix (CP) in OFDM signal. From proposed technique, our objective is to achieve a better sensing performance under very low SNR, such that the primary networks and the CRNs can coexist in better way. Simulation results are done under theoretical perspective which illustrate that the proposed sensing technique can reliably detect OFDM signals at SNR as low as -20 dB.
    India Conference (INDICON), 2014 Annual IEEE; 09/2015

Full-text (2 Sources)

Available from
May 17, 2014