Optimizing Spectrum Sensing Time With Adaptive Sensing Interval for Energy-Efficient CRSNs

Kong, Fanhua; Cho, Jinsung; Liu, Ben

doi:10.1109/jsen.2017.2758823

Cited by 11 publications

(7 citation statements)

References 31 publications

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“…In [1], the authors aim to optimize the dynamic spectrum access while guaranteeing sufficient PU protection. The paper proposes a new sensing scheme in which the sensing process is divided into two individual processes.…”

Section: Sensing Techniques and Scenariosmentioning

confidence: 99%

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A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

Tian¹,

Esseghir²,

Khoukhi³

2019

NPA

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A large scale of spectrum sensing techniques are proposed to improve the use of spectrum resources. However, the EE (energy efficiency) should be guaranteed for both primary and secondary users, especially under various detection performance constraints. In this regard, the linking between activities of PU (primary user) and dynamic access behaviors of SUs (secondary users) should be considered in an integrated way. This survey has compared different existing scenarios and frameworks on EE optimizations. The principal objective is to enhance the system throughput and to coordinate on the physical layer of both PU and SUs, in order to enable a high-quality spectrum detection and a more efficient spectrum access. In the technical part, several optimization methods are introduced under PU’s constraints, and different methods based on game theory are applied to suitable cooperative sensing scenarios for SUs’ optimal access. Finally, the complexity of algorithms is compared, to further reduce the execution time and deploy real-time adaptation for users with lower delay.

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Section: Sensing Techniques and Scenariosmentioning

confidence: 99%

“…Main focus and contribution [1] It formulates EE as averaged throughput per energy during a frame time, where the analysis of a frame of SU is divided into several cases of access actions determined by first and second sensing results.…”

Section: Referencementioning

confidence: 99%

A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

Tian¹,

Esseghir²,

Khoukhi³

2019

NPA

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“…This idea was also applied in the cognitive radio sensor networks. 18 In this paper, we consider a CRN with energy harvesting capability and apply the sensing interval approach to improve its performance. At the beginning of each time slot, the SU has to select whether to stay idle or sense the channel.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, if the channel is sensed busy, the SU stays idle for one complete frame. This idea was also applied in the cognitive radio sensor networks 18 …”

Section: Introductionmentioning

confidence: 99%

Optimal sensing energy and sensing interval in cognitive radio networks with energy harvesting

Abdelfattah

Rabia

Abdelrazek

2021

Int J Communication

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Summary Cognitive radio networks with energy harvesting aim to improve spectrum utilization and allow users to move freely. Cognitive radio technology enhances the utilization of the spectrum by permitting the unlicensed user (secondary user) to use the channel during the absence of the licensed user (primary user). A major issue in this approach is that the secondary user needs to sense the channel frequently, which leads to energy wasting. This problem can be dealt with using the notion of sensing interval where the channel is sensed every multiple of time slots. In this paper, we consider the problem of determining the optimal sensing energy and the optimal sensing interval that maximize the secondary user throughput and minimize both the consumed energy and the interference to the primary user. By formulating this optimization problem as a mixed observable Markov decision process, a dynamic policy for the secondary user is generated taking into account the total accumulated secondary user reward. Numerical results show that the proposed policy outperforms existing results, especially when the secondary user prefers the transmission mode to the energy‐saving mode. Additionally, the numerical results show that applying sensing interval concept for both idle and busy sensing results is better than applying it for the idle case only.

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“…To solve this problem, the concept of cognitive radio (CR) was first introduced by Mitola in [ 23 ], where licensed users (primary users (PUs)) can share their bands to unlicensed users (secondary users (SUs)) provided that quality of service (QoS) of the primary network is still guaranteed. Conventionally, SUs have to periodically sense the presence/absence of PUs, so that they can use vacant bands or move to another spectrum holes [ 24 , 25 ]. In [ 26 , 27 ], various spectrum sensing models for CR WSNs were introduced and compared.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Relay Selection Schemes in Beacon-Assisted Dual-Hop Cognitive Radio Wireless Sensor Networks under Impact of Hardware Noises

Tran

Duy

Choi

2018

Sensors

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To solve the problem of energy constraints and spectrum scarcity for cognitive radio wireless sensor networks (CR-WSNs), an underlay decode-and-forward relaying scheme is considered, where the energy constrained secondary source and relay nodes are capable of harvesting energy from a multi-antenna power beacon (PB) and using that harvested energy to forward the source information to the destination. Based on the time switching receiver architecture, three relaying protocols, namely, hybrid partial relay selection (H-PRS), conventional opportunistic relay selection (C-ORS), and best opportunistic relay selection (B-ORS) protocols are considered to enhance the end-to-end performance under the joint impact of maximal interference constraint and transceiver hardware impairments. For performance evaluation and comparison, we derive the exact and asymptotic closed-form expressions of outage probability (OP) and throughput (TP) to provide significant insights into the impact of our proposed protocols on the system performance over Rayleigh fading channel. Finally, simulation results validate the theoretical results.

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Optimizing Spectrum Sensing Time With Adaptive Sensing Interval for Energy-Efficient CRSNs

Cited by 11 publications

References 31 publications

A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

Optimal sensing energy and sensing interval in cognitive radio networks with energy harvesting

Performance Evaluation of Relay Selection Schemes in Beacon-Assisted Dual-Hop Cognitive Radio Wireless Sensor Networks under Impact of Hardware Noises

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