Performance of power detector sensors of DTV signals in IEEE 802.22 WRANs

Shellhammer, Stephen J.; N, Sai Shankar; Tandra, Rahul; Tomcik, James

doi:10.1145/1234388.1234392

Cited by 157 publications

(106 citation statements)

References 3 publications

Supporting

Mentioning

105

Contrasting

Order By: Relevance

“…Spectrum sensing with application to the IEEE 802.22 standard has been studied in (Cordeiro et al, 2007;Kim & Andrews, 2010;Lim et al, 2009;Shellhammer et al, 2006). The spectrum sensing approach proposed in (Kim & Andrews, 2010) uses a spectral covariance sensing algorithm which exploits different statistical correlations of the signal and noise in frequency domain.…”

Section: Spectrum Sensing For Ieee 80222mentioning

confidence: 99%

“…The performance of power detector sensors for digital TV signals in IEEE 802.22 is studied in (Shellhammer et al, 2006). The authors studied the performance of a power detector in various IEEE 802.22 scenarios such as the "keep out region," also referred as the noise-limited contour.…”

Section: Spectrum Sensing For Ieee 80222mentioning

confidence: 99%

“…The shadowing fading is modeled by a log-normal distribution with zero mean and a variance of 5.5 dB (Shellhammer et al, 2006). The total In Fig.…”

Section: Spectrum Sensing With Rayleigh Fading and Shadowingmentioning

confidence: 99%

See 2 more Smart Citations

Improving Spectrum Sensing Performance by Exploiting Multiuser Diversity

Do¹,

Mark²

2012

Foundation of Cognitive Radio Systems

View full text Add to dashboard Cite

Section: Spectrum Sensing For Ieee 80222mentioning

confidence: 99%

Section: Spectrum Sensing For Ieee 80222mentioning

confidence: 99%

See 1 more Smart Citation

Improving Spectrum Sensing Performance by Exploiting Multiuser Diversity

Do¹,

Mark²

2012

Foundation of Cognitive Radio Systems

View full text Add to dashboard Cite

“…978-1-4244-5638-3/10/$26.00 ©2010 IEEE According to [11], the receiver noise characteristic consists of a typical noise power spectral density (PSD) and a noise uncertainty. The noise uncertainty specification is necessary since even though the sensing mechanism may involve calibration based on the noise power estimation, the estimate often exhibits some inaccuracy, which must be modeled.…”

Section: A Signal Acquisition and System Set-upmentioning

confidence: 99%

A Novel Robust Detection Algorithm Using Jarqur-Bera Statistic for Spectrum Sensing

Iyengar

2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

View full text Add to dashboard Cite

Abstract-In this paper, the DTV (digital television) spectrum sensing problem is studied, which plays a key role in the cognitive radio. In contrast to the existing higher-order-statistics (HOS) approach, we propose a novel robust spectrum-sensing method, which is based on the JB (Jarqur-Bera) statistic. In our new studies, the existing HOS spectrum sensing technique may often not be robust. Our proposed JB-statistic based detector has been justified to be superior for the simulated microphone signals as well as the real DTV signals.

show abstract

“…Therefore, each of the CFAR and CDR principles can general ensure either one of the error probabilities under low level within a limited sensing time, i.e., false alarm probability P f a for CFAR and false detection probability (1 − P d ) Spectrum sensing is to determine whether a licensed band is currently used by its primary user. This can be formulated into a binary hypothesis testing problem [19,20]:…”

Section: Introductionmentioning

confidence: 99%

Fundamental Limitations in Energy Detection for Spectrum Sensing

Peng

2018

JSAN

View full text Add to dashboard Cite

Abstract:A key enabler for Cognitive Radio (CR) is spectrum sensing, which is physically implemented by sensor and actuator networks typically using the popular energy detection method. The threshold of the binary hypothesis for energy detection is generally determined by using the principles of constant false alarm rate (CFAR) or constant detection rate (CDR). The CDR principle guarantees the CR primary users at a designated low level of interferences, which is nonetheless subject to low spectrum usability of secondary users in a given sensing latency. On the other hand, the CFAR principle ensures secondary users' spectrum utilization at a designated high level, while may nonetheless lead to a high level of interference to the primary users. The paper introduces a novel framework of energy detection for CR spectrum sensing, aiming to initiate a graceful compromise between the two reported principles. The proposed framework takes advantage of the summation of the false alarm probability P f a from CFAR and the missed detection probability (1 − P d ) from CDR, which is further compared with a predetermined confidence level. Optimization presentations for the proposed framework to determine some key parameters are developed and analyzed. We identify two fundamental limitations that appear in spectrum sensing, which further define the relationship among the sample data size for detection, detection time, and signal-to-noise ratio (SNR). We claim that the proposed framework of energy detection yields merits in practical policymaking for detection time and design sample rate on specific channels to achieve better efficiency and less interferences.

show abstract

Performance of power detector sensors of DTV signals in IEEE 802.22 WRANs

Cited by 157 publications

References 3 publications

Improving Spectrum Sensing Performance by Exploiting Multiuser Diversity

Improving Spectrum Sensing Performance by Exploiting Multiuser Diversity

A Novel Robust Detection Algorithm Using Jarqur-Bera Statistic for Spectrum Sensing

Fundamental Limitations in Energy Detection for Spectrum Sensing

Contact Info

Product

Resources

About