Spectrum Sensing for Dynamic Spectrum Access of TV Bands

Cordeiro, Carlos; Ghosh, Monisha; Cavalcanti, Dave; Challapali, K.

doi:10.1109/crowncom.2007.4549801

Cited by 107 publications

(70 citation statements)

References 8 publications

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“…The performance gains of the new detectors are in the range between 2 dB and 6 dB near the SNR value of -20 dB. These are significant in this operating region [23], [24]. Fig.…”

Section: Numerical Results and Discussionmentioning

confidence: 68%

Novel <inline-formula> <tex-math notation="TeX">${\rm S}\alpha{\rm S} $</tex-math></inline-formula> PDF Approximations and Their Applications in Wireless Signal Detection

Chen

2015

IEEE Trans. Wireless Commun.

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“…The performance gains of the new detectors are in the range between 2 dB and 6 dB near the SNR value of -20 dB. These are significant in this operating region [23], [24]. Fig.…”

Section: Numerical Results and Discussionmentioning

confidence: 68%

Novel <inline-formula> <tex-math notation="TeX">${\rm S}\alpha{\rm S} $</tex-math></inline-formula> PDF Approximations and Their Applications in Wireless Signal Detection

Chen

2015

IEEE Trans. Wireless Commun.

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“…However, they (negatively) contribute to the TDP for CID cases since they are treated as the events of interest in (11) and (12). The TDP for CID cases can be expressed as follows…”

Section: And Inmentioning

confidence: 99%

“…TDP considers both the detection latency and the unavoidable misdetection in the stage of detection. Prior to the definition of TDP, we first introduce a new parameter of the so-called RDT, which is conceptually similar to the channel detection time specified in IEEE 802.22 STD [11][12][13]. The definition of RDT is given as follows.…”

Section: Tdpmentioning

confidence: 99%

Time-constrained detection probability and sensing parameter optimization in cognitive radio networks

Choi

Yoo

2013

J Wireless Com Network

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Sensing-throughput tradeoff has widely been investigated in cognitive radio networks. Detection probability and interference ratio are usually considered the main constraints to the protection of primary signals. However, the detection probability defined during a sensing duration does not fully capture the goal of primary protection because two important factors are not taken into consideration. Neither the detection latency during the detection of the primary signal nor the unavoidable misdetection of the primary signal due to its ability to only occupy the channel between two consecutive sensing durations are considered. Motivated by these problems, we propose a new detection probability called the time-constrained detection probability (TDP) and investigate the effect of the sensing interval on the TDP. This sensing interval consists of a sensing duration and a transmission duration. Moreover, both an optimal sensing duration and an optimal sensing interval are proposed, which not only satisfy both the TDP and the interference ratio constraints for primary protection, but also maximize the achievable throughput for secondary users. Numerical analyses show the relationship between the sensing interval and the TDP and the optimal sensing parameters consisting of the optimal sensing duration and the optimal sensing interval.

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“…A decision on whether a specific spectrum band is occupied by a PU or not can be taken by comparing the received energy with a pre-determined detection threshold. The detection thresholds for some primary systems have been specified by the IEEE 802.22 standard [10]. However, these fixed and identical detection thresholds are not adequate for multi-band CRNs, since different sub-carriers may suffer from different fading.…”

Section: Introductionmentioning

confidence: 99%

Joint optimization of detection threshold and resource allocation in infrastructure-based multi-band cognitive radio networks

Shi

Wang

et al. 2012

J Wireless Com Network

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Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on the PUs' rate loss and the power budget of the CR base station. Two schemes, referred to as offline and online algorithms respectively, are proposed to solve the optimization problem. While the offline algorithm finds the global optimal solution with high complexity, the online algorithm provides a close-to-optimal solution with much lower complexity and realtime capability. The performance of the proposed schemes is evaluated by extensive simulations and compared with the conventional static threshold selection algorithm specified in the IEEE 802.22 standard.

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Spectrum Sensing for Dynamic Spectrum Access of TV Bands

Cited by 107 publications

References 8 publications

Novel <inline-formula> <tex-math notation="TeX">${\rm S}\alpha{\rm S} $</tex-math></inline-formula> PDF Approximations and Their Applications in Wireless Signal Detection

Novel <inline-formula> <tex-math notation="TeX">${\rm S}\alpha{\rm S} $</tex-math></inline-formula> PDF Approximations and Their Applications in Wireless Signal Detection

Time-constrained detection probability and sensing parameter optimization in cognitive radio networks

Joint optimization of detection threshold and resource allocation in infrastructure-based multi-band cognitive radio networks

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