Sensing‐throughput optimisation for multichannel cooperative spectrum sensing with imperfect reporting channels

Firouzabadi, Abbas Dehghani; Rabiei, Amir Masoud

doi:10.1049/iet-com.2015.0097

Cited by 12 publications

(7 citation statements)

References 24 publications

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“…Optimal sensing duration was investigated [18]- [21] in an attempt to improve the overall system throughput, taking into account that a smaller number of SUs leads to a reduced sensing duration at the expense of reduced sensing diversity. Firouzabadi et al [22] considered wideband spectrum sensing and formulated the sensing problem as an optimization problem with the purpose of maximizing the opportunistic throughput of CRN by assuming the number of samples used to report the sensing decisions to the FC, the number of the sensing samples, the detection threshold and the overall sensing-plus-reporting time. Unlike previous work [18]- [22] whose optimization objectives were to maximize the secondary throughput, Zheng et al [23] proposed joint optimization of sensing time and the detection threshold with the aim of maximizing the energy efficiency of cognitive sensor networks.…”

Section: Related Workmentioning

confidence: 99%

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Alhussein

Sofotasios

et al. 2020

IEEE Trans. Sustain. Comput.

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The present contribution proposes a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach in a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. In this context, exact analytic expressions are first derived for the corresponding probability of detection, probability of false alarm and secondary throughput, assuming that each secondary user (SU) sends its detection outcome to a fusion center only when it has detected a primary signal. Capitalizing on the findings of the analysis, the effects of critical measures, such as the detection threshold, the number of SUs and the number of employed antennas, on the overall system performance are also quantified. In addition, the optimal detection threshold for each antenna based on the Neyman-Pearson criterion is derived and useful insights are developed on how to maximize the system throughput with a reduced number of SUs. It is shown that the C-CSS approach provides two distinct benefits compared with the conventional sensing approach, i.e., without censoring: i) the sensing tail problem, which exists in imperfect sensing environments, can be mitigated; ii) less SUs are ultimately required to obtain higher secondary throughput, rendering the system more sustainable.

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Section: Related Workmentioning

confidence: 99%

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Alhussein

Sofotasios

et al. 2020

IEEE Trans. Sustain. Comput.

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“…where T is the total number of samples and y i is the sum of the squares of T Gaussian independent random variables. It is shown that υ i follows a central Chi square χ 2 c distribution with T degrees of freedom if H 0 is true, otherwise it follows non-central χ 2 nc distribution with T degrees of freedom and non-centrality parameter λ i . The power received by ith SU is λ i , which is de-…”

Section: Local Sensingmentioning

confidence: 99%

“…The sensing decision of the local secondary user (SU) alone may not be reliable enough due to shadowing, multipath fading and time varying nature of wireless channels between SU and PU. To combat these issues, cooperative spectrum sensing (CSS) schemes have been proposed to take advantage of spatial diversity [1,2,3,4]. It can greatly increase the PD in shadowing channels.…”

Section: Introductionmentioning

confidence: 99%

“…The CSS schemes using imperfect reporting channel are not proposed widely in the literature. Indeed increasing the cooperative SUs can improve the performance of network in terms of the PD while maintaining the PF at a desired level if perfect reporting channel is considered [18]. However, it is difficult to achieve desired sensing performance although many SUs are involved in the CSS due to imperfect reporting channel.…”

Section: Introductionmentioning

confidence: 99%

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Efficient error detection in soft data fusion for cooperative spectrum sensing

Bhatti

Ahmed

Saeed

et al. 2018

AEU - International Journal of Electronics and Communications

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The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.

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“…The sensing decision of single SU alone may not be reliable due to fading channel and shadowing. To overcome these effects, cooperative spectrum sensing schemes have been considered to take advantage of spatial diversity [5–8], by which the probability of detection is greatly increased. A combining rule is applied at fusion centre (FC), in which the estimated energy reported by each SU is combined together to be compared with a threshold to decide the presence or the absence of PU.…”

Section: Introductionmentioning

confidence: 99%

Spatial correlation based analysis of soft combination and user selection algorithm for cooperative spectrum sensing

Bhatti

Nam

2017

IET Communications

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Sensing‐throughput optimisation for multichannel cooperative spectrum sensing with imperfect reporting channels

Cited by 12 publications

References 24 publications

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Efficient error detection in soft data fusion for cooperative spectrum sensing

Spatial correlation based analysis of soft combination and user selection algorithm for cooperative spectrum sensing

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