Maximizing system throughput by cooperative sensing in Cognitive Radio Networks

Li, Shuang; Zheng, Zizhan; Ekici, Eylem; Shroff, Ness B.

doi:10.1109/infcom.2012.6195526

Cited by 17 publications

(22 citation statements)

References 21 publications

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“…Proof: (sketch) By adding the k+1-th SU into the sensing set, we can at least achieve the same system throughput as before by ignoring its observation. The detailed proof can be found in our technical report [16].…”

Section: A N D + D ≤ T Cmentioning

confidence: 91%

Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Zheng

Ekici

et al. 2014

IEEE/ACM Trans. Networking

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Cognitive Radio Networks allow unlicensed users to opportunistically access the licensed spectrum without causing disruptive interference to the primary users (PUs). One of the main challenges in CRNs is the ability to detect PU transmissions. Recent works have suggested the use of secondary user (SU) cooperation over individual sensing to improve sensing accuracy. In this paper, we consider a CRN consisting of a single PU and multiple SUs to study the problem of maximizing the total expected system throughput. We propose a Bayesian decision rule based algorithm to solve the problem optimally with a constant time complexity. To prioritize PU transmissions, we re-formulate the throughput maximization problem by adding a constraint on the PU throughput. The constrained optimization problem is shown to be NP-hard and solved via a greedy algorithm with pseudo-polynomial time complexity that achieves strictly greater than 1/2 of the optimal solution. We also investigate the case for which a constraint is put on the sensing time overhead, which limits the number of SUs that can participate in cooperative sensing. We reveal that the system throughput is monotonic over the number of SUs chosen for sensing. We illustrate the efficacy of the performance of our algorithms via a numerical investigation.

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Section: A N D + D ≤ T Cmentioning

confidence: 91%

Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Zheng

Ekici

et al. 2014

IEEE/ACM Trans. Networking

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“…Most approaches find the optimum threshold by either minimizing the probability of false alarm or maximizing the probability of successful detection [44]. However, the detection performance is actually affected by both phenomena.…”

Section: Proposed Optimal Energy Detectionmentioning

confidence: 99%

A Voting-Based Distributed Cooperative Spectrum Sensing Strategy for Connected Vehicles

Aygün

Wyglinski

2017

IEEE Trans. Veh. Technol.

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In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge the proposed approach is novel. During the energy detection process, large scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current-state-ofthe-art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

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“…Inspired by network relaying, cooperative cognitive relay networks (CCRN) have recently been investigated as a potential mechanism to improve the secondary network throughput. Two cooperation mechanisms have been proposed: cooperation among secondary users [16][17][18][19] and cooperation between primary and secondary users [20][21][22][23][24][25]. In the first case, secondary users access or sense the primary spectrum in a cooperative manner to enhance their performance; while in the second case, secondary users serve as relays for the primary network to achieve a 'win-win' situation, which is also the focus of this paper.…”

Section: Related Workmentioning

confidence: 99%

Achievable transmission capacity of cognitive radio networks with cooperative relaying

Jing

Chen

et al. 2015

J Wireless Com Network

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With the rapid development of cognitive radio technologies, spectrum sharing becomes a promising approach to improving the efficiency of spectrum utilization and mitigating the spectrum scarcity problem. Previous research on cognitive networks argues that secondary users can only work under a low-transmission power in an underlay spectrum sharing model, especially when the primary transmitter is far away from the primary receiver. Motivated by the idea of cooperative communications, in this paper, we propose a cooperative framework in which a primary transmitter, being aware of the existence of the secondary network, may select a secondary user that is not in transmitting or receiving mode to relay its traffic. The feasible relay location region and optimal power ratio between the primary network and the secondary network are derived in the underlay spectrum sharing model. Based on the optimal power ratio, we derive the maximum achievable transmission capacity of the secondary network under the outage constraints from both the primary and the secondary network with or without cooperative relaying. Numerical results indicate that secondary users can achieve a higher transmission capacity with cooperative relaying, and that the capacity gain of the cooperative network is significantly affected by the location of the relay and the network system parameters.

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Maximizing system throughput by cooperative sensing in Cognitive Radio Networks

Cited by 17 publications

References 21 publications

Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

A Voting-Based Distributed Cooperative Spectrum Sensing Strategy for Connected Vehicles

Achievable transmission capacity of cognitive radio networks with cooperative relaying

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