Adaptive full duplex communications in cognitive radio networks

Towhidlou, Vahid; Shikh-Bahaei, Mohammad

doi:10.1109/pimrc.2017.8292550

Cited by 10 publications

(16 citation statements)

References 16 publications

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“…12 CR system and its applications, existing limitations and their suitable methods, are reviewed in previous studies. [13][14][15][16] Conflicts of spectrum rights and the requirement among passive astronomy system and active wireless communication systems are prominently higher because of the remarkable growth of wireless communication. 17,18 Further, spectrum sharing and spectrum sensing in CR are reviewed and discussed.…”

Section: Resultsmentioning

confidence: 99%

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Dinesh¹,

Venkatakrishnan²,

Jeyanthi

2020

Int J Communication

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Summary At present, the demand for wireless communications is growing tremendously. Cognitive radio network plays an important role in making the spectrum to be used effectively. Uncertainty in channels and interference were generally occurs that reduced the system efficiency. To overcome the load usage problem, the proposed system of spectrum sensing and scheduling algorithms is introduced, where the available spectrums are sensed or detected and scheduled to load the free spectrum. Spectrum sensing is a cognitive radio basic function to thwart the harmful interference with licensed users and detect the available spectrum for enhancing the spectrum's utilization. In the proposed technique, initially, the spectrum sharing and sensing method is put forward to raise the throughput and quality of service necessity. At this time, spectrum sharing in common with scheduling process is presented, where the available spectrum, the load is scheduled and sensed to free the spectrum. Here, the modified spider monkey optimization (MSMO) technique is used for spectrum sensing and detecting free spectrums, thereby enhancing the energy efficiency of the available spectrum. This technique will found the optimal solution and increases the expectation of some decisions. Modified round robin algorithm is used for scheduling load. In this algorithm, every packet flow has its packet queue presented in the network interface controller. The performance analysis is finally measured using metrics such as throughput, handoff, success probability, and false alarm probability.

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Section: Resultsmentioning

confidence: 99%

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Dinesh¹,

Venkatakrishnan²,

Jeyanthi

2020

Int J Communication

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“…where i ∈ [1,15] and j ∈ [1,20]. By using a decision threshold at the output, the predicted value y 3 can be expressed as a binary symbol:…”

Section: B Neural Network Based Predictionmentioning

confidence: 99%

“…where D 0,T R = log 2 (1 + SNRs,s 1+χSNRs,s ) is SU's maximum achievable data rate in TR mode in the OFF state [20].…”

Section: • Cmentioning

confidence: 99%

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A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

Zhang

Hou

Towhidlou

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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We propose a neural network (NN) predictor and an adaptive mode selection scheme for the purpose of both improving secondary user's (SU's) throughput and reducing collision probability to the primary user (PU) in full-duplex (FD) cognitive networks. SUs can adaptively switch between FD transmissionand-reception (TR) and transmission-and-sensing (TS) modes based on the NN prediction results for each transmission duration. The prediction performance is then analysed in terms of prediction error probability. We also compare the performance of our proposed scheme with conventional TR and TS modes in terms of SUs average throughput and collision probability, respectively. Simulation results show that our proposed scheme achieves even better SUs average throughput compared with TR mode. Meanwhile, the collision probability can be reduced close to the level of TS mode.

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“…To the best of our knowledge, we are among the first ones exploring this method in vehicular networks. Other related works are either not in the area of vehicular networks such as [6], [7], [8], [9], [10], [11] and [12], or in vehicular communications but assumed ideal energy detection such as [13] and [14]. Unlike these works, we have assumed imperfect energy detection and investigated the effect of threshold, transmit power, SIC capability, sensing time, collision duration and throughput on the network performance.…”

Section: Introductionmentioning

confidence: 99%

Collision Avoidance in V2X Communication Networks

Zang¹,

Towhidlou²,

Shikh-Bahaei³

2019

2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)

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In this paper we investigate collision detection and avoidance in a vehicular network of full duplex (FD) operating nodes. Each vehicle in this network senses the energy level of the channel before and during its transmission. The measured energy is compared against a dynamic threshold which is preset based on the target detection probability, transmitter's power, sensing time and self-interference cancellation (SIC) capability of the vehicles' on board units (OBU). Probabilities of detection and false alarm, detection threshold before and during transmission, and effect of residual self interference (SI) on these metrics have been formulated. It is shown that the proposed scheme would experience a shorter collision duration. Meanwhile, it also requires a minimum SIC capability for acceptable operation, below which, system throughput would be poor due to high false alarm probability. Numerical simulations verify the accuracy of our analysis. They also illustrate that the proposed model perform better than the fixed threshold strategy. A trade-off between half duplex (HD) and FD has been found and the scheme would be applicable even if SIC capability of OBUs is relatively poor, with no need for complicated and expensive devices for future vehicular communication.

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Adaptive full duplex communications in cognitive radio networks

Cited by 10 publications

References 16 publications

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

Collision Avoidance in V2X Communication Networks

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