Energy‐efficient power allocation in underlay and overlay cognitive device‐to‐device communications

Sultana, Ajmery; Zhao, Lian; Fernando, Xavier

doi:10.1049/iet-com.2018.5464

Cited by 12 publications

(10 citation statements)

References 41 publications

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“…e optimization of the UAV's sensing performance and achievable average throughput are investigated in this section. First of all, from (5) and (6), it can be seen that the probability of the LoS link is highly related to the location of the UAV, because the flight height and the flight radius of the UAV will change the distance and elevation angle between the UAV and ground node. erefore, the values of the flight height and the flight radius are fixed in this paper; only the impact of the flight speed on sensing radian is analysed to investigate the relationship between sensing radian and throughput.…”

Section: Optimization Of Sementioning

confidence: 99%

“…In this section, we optimize the SE of UAV under multiradian CSS and prove that there exist an optimal mini sensing radian denoted as θ * 0 and an optimal number of mini sensing radians (2) Given N i , using Algorithm 1 to calculate θ 0 * ; (3) θ 0 k+1 � θ 0 * ; (4) Given θ 0 k+1 , using the numerical method to calculateN * ; (5) N i+1 � N * ; (6) calculate…”

Section: Se Optimization Scheme Of Multiradian Cssmentioning

confidence: 99%

“…However, the application of UAV communication also faces many challenges, and spectrum shortage is one of the key issues. Due to the rapid development of 5G network [5], device-to-device (D2D) technology [6], and Internet of ings (IoT) [7], the spectrum demand is growing rapidly. e UAV generally operates on IEEE S-band, IEEE L-band, and industrial, scientific, and medical (ISM) frequency bands, and these spectrum resources have been occupied by many wireless networks (such as Wi-Fi, Bluetooth, and IEEE 802.15.4 network) [8].…”

Section: Introductionmentioning

confidence: 99%

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Spectrum Efficiency Optimization for UAV-Based Cognitive Radio Network

Zhang

et al. 2020

Mathematical Problems in Engineering

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Unmanned aerial vehicle- (UAV-) assisted communication has great potential to provide on-demand wireless services and improve the outdoor link throughput. In this paper, a UAV-based cognitive radio network (CRN) is investigated in which the UAV works as a secondary user (SU). Considering the overlay spectrum sensing mode, the UAV can operate on the licensed spectrum bands of primary user (PU) only when PU is idle. In each working frame structure, both sensing time slot and transmission time slot are analysed in radians. Specifically, our objective is to maximize the spectrum efficiency (SE) of the UAV by jointly optimizing the sensing radian and the number of radians. For the single-radian and multiradian schemes, the dichotomy and alternative iterative optimization (AIO) algorithm are proposed to solve the SE optimization problem. Simulation results show that the proposed multiradian cooperative spectrum sensing (CSS) scheme can achieve better performance on ensuring the quality-of-service (QoS) of the PU, and it can significantly enhance the SE of the UAV especially in the severe channel environments.

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Section: Optimization Of Sementioning

confidence: 99%

Section: Se Optimization Scheme Of Multiradian Cssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spectrum Efficiency Optimization for UAV-Based Cognitive Radio Network

Zhang

et al. 2020

Mathematical Problems in Engineering

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“…Spectrum sharing between them has become a promising option. As a spectrum sharing technology, cognitive radio has been extensively investigated in many fields, such as device-to-device communication [3], vehicular communication [4], unmanned aerial vehicle (UAV) communication [5], and wireless sensor network [6]. However, cognitive satellite communications have many inherent characteristics, such as considerable propagation delay, wide beam coverage, cumulative uplink interference, sensitivity to interference, and so on [7].…”

Section: Introductionmentioning

confidence: 99%

A Distributed Collaborative Game-Theoretic Approach in Cognitive Satellite Communication Networks

et al. 2020

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Due to the increasing spectrum scarcity in satellite communications and terrestrial communications, cognitive satellite communications have received widespread attention. In this paper, we take the inherent feature that the terrestrial cognitive users suffer from inter-beam interference. In particular, for the first time, we consider the coupling characteristics of channel access and power optimization in opportunistic spectrum access based on distributed frameworks. We first formulate a joint channel access and power optimization game, which is proven to be an exact potential game and accordingly has at least one pure Nash Equilibrium (NE) point. The sufficient conditions for interference-free between cognitive users and for maximization of system utility are given, respectively. Also, the lower bound of the system utility is deduced theoretically. For discrete power control strategies, we then propose a joint-strategy iteration algorithm (JID) to converge to the general NE in two-dimensional discrete strategy space. Especially, to solve the challenge of finding the optimal NE solution in two-dimensional strategy space, we propose a novel joint-strategy iteration algorithm based on exploration and exploitation (JIDEE). Simultaneously, these two algorithms are extended to the case where the power control strategies are continuous. Finally, simulations are conducted to confirm the effectiveness of the formulated game and the two proposed algorithms. INDEX TERMS Cognitive satellite communication, spectrum sharing, exact potential game, exploration and exploitation.

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“…However, scarce spectrum resources are still the bottleneck restricting their adequate development due to the current spectrum segmentation and static frequency allocation policies. Cognitive radio has become a promising technology for solving the problem of spectrum scarcity, and has been widely studied in various fields, such as wireless network [1], unmanned aerial vehicle (UAV) communication [2], device-to-device communication [3], [4], vehicular communication [5], wireless sensor network [6].…”

Section: Introductionmentioning

confidence: 99%

Spectrum Access and Power Control for Cognitive Satellite Communications: A Game-Theoretical Learning Approach

et al. 2019

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With the increasing scarcity of spectrum resources in satellite and terrestrial communications, spectrum sharing becomes a promising option. In this paper, we investigate the spectrum access and power control problem in multibeam-based cognitive satellite communication network. Differ from the most existing spectrum access problems in terrestrial networks, we consider not only the interference between cognitive users, but also the co-channel interference from multi-beam satellite communication system to cognitive users. We formulate a spectrum access and power control game, and it is proved to be an ordinal potential game. The sufficient conditions for cognitive users not to interfere with each other are given, and the upper bound of the aggregation interference experienced by all cognitive users is deduced theoretically. Then, based on the trial and error (TE) algorithm, we propose a learning-based distributed spectrum access algorithm, which statistically converges to the best Nash equilibrium(NE). Furthermore, to simplify the coefficients design and improve the convergence performance, we propose an improved learning-based distributed spectrum access algorithm. Simulation results show that the average network throughput of the proposed game is close to the best, which validates the game-theoretic solution. Simulation results also show that the improved learning-based distributed spectrum access algorithm is superior to the original algorithm in terms of convergence speed, throughput performance, and practicability, which confirms the effectiveness of the improved algorithm. INDEX TERMS Cognitive satellite communication, power control and spectrum access, ordinary potential game, trial and error learning algorithm.

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Energy‐efficient power allocation in underlay and overlay cognitive device‐to‐device communications

Cited by 12 publications

References 41 publications

Spectrum Efficiency Optimization for UAV-Based Cognitive Radio Network

Spectrum Efficiency Optimization for UAV-Based Cognitive Radio Network

A Distributed Collaborative Game-Theoretic Approach in Cognitive Satellite Communication Networks

Spectrum Access and Power Control for Cognitive Satellite Communications: A Game-Theoretical Learning Approach

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