Power-Controlled Cognitive Radio Spectrum Allocation with Chemical Reaction Optimization

Lam, Albert Y. S.; Li, V. O. K.

doi:10.1109/twc.2013.061713.120255

Cited by 24 publications

(12 citation statements)

References 15 publications

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“…In this section, a novel intelligent algorithm named QCRO is proposed for multiple-relay selection in a secure massive MIMO two-way relay network. Inspired by the chemical reaction optimization (CRO) algorithm [39] and quantum evolutionary theory [9], QCRO employs a set of quantum molecules, which is varied by different quantum evolutionary rules. Here we introduce the principle of QCRO.…”

Section: Methodsmentioning

confidence: 99%

“…The comparisons of QCRO algorithm, particle swarm optimization (PSO) algorithm [40], chemical reaction optimization (CRO) algorithm [39], single-relay selection (SRS) strategy [32], and random multiple-relay selection (RMRS) strategy on the security performance are presented in Figs. 1 -5.…”

Section: Performance Comparisons With Qcromentioning

confidence: 99%

“…For comparison purpose, we set the maximum number of iterations for QCRO, PSO, and CRO algorithms to the same value, and all these algorithms are set to the same population size. The other parameters of PSO and CRO algorithms are set to the optimal values cited in [40] and [39], respectively. For QCRO algorithm, all quantum bits are initialized to 0.5 and the initial kinetic energy each quantum molecule is set to 1000.…”

Section: Performance Comparisons With Qcromentioning

confidence: 99%

See 2 more Smart Citations

Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

Su¹,

Gao²,

Zhang³

2020

Preprint

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With the advent of Internet of Everything (IoE) and the era of big data, massive multiple-input multiple-output (MIMO) is considered an essential technology to meet the growing communication requirements for beyond 5G and the forthcoming 6G networks. This paper considers a secure massive MIMO system, where the legitimate user and the base station (BS) exchange messages via two-way relays with the presence of passive eavesdroppers. To achieve the trade-off between the physical-layer security and communication reliability, we design a cooperative transmission mode based on multiple-relay collaboration, where some relays broadcast the received signals and other relays act as friendly jammers to prevent the interception by eavesdroppers. A quantum chemical reaction optimization (QCRO) algorithm is proposed to find the most suitable scheme for multiple-relay collaboration. Simulation results highlight excellent performance of the proposed transmission mode under QCRO in different communication scenarios, which can be considered a potential solution for the security issue in future wireless networks.

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Section: Methodsmentioning

confidence: 99%

Section: Performance Comparisons With Qcromentioning

confidence: 99%

Section: Performance Comparisons With Qcromentioning

confidence: 99%

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Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

Su¹,

Gao²,

Zhang³

2020

Preprint

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“…Chemical Reaction Optimization (CRO) is a recently proposed Nature-inspired metaheuristic for optimization [24]. Under certain conditions, it has been proved to be able to converge to the global optimum for combinatorial optimization problems (like EVCSPP) [25] and it has been demonstrated to have very good performance in solving real-world problems, e.g., [26], [27]. CRO is general-purpose and we apply CRO to EVCSPP.…”

Section: Methods Iv: Chemical Reaction Optimizationmentioning

confidence: 99%

Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

Lam

Leung

Chu

2014

IEEE Trans. Smart Grid

383

132

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To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans. So the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to recharge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being re-charged. Based on these new perspectives, we formulate the Electric Vehicle Charging Station Placement Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.

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“…An approach based on artificial bee colony (ABC) is presented in [14], where the authors show that the ABC algorithm obtains results close to the optimal values. A binary harmony search algorithm (BHSA) is used in [15], where the authors compare performance with a GA. Their results show that the BHSA is faster and it obtains better solutions than the GA. A chemistry inspired algorithm CRO is used in [16][17][18], and it outperforms a canonical genetic algorithm, QGA [13] and PSO to the cognitive radio spectrum allocation problem. A survey on the state-of-the-art of machine-learning techniques in cognitive radios is presented in [17].…”

Section: Related Workmentioning

confidence: 99%

Spectrum allocation in cognitive radio networks using chaotic biogeography‐based optimisation

et al. 2018

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Cognitive radio networks are a promising technology for the improvement of the spectrum utilisation. The basic idea is to maximise the utilisation of the available spectrum by dynamically assigning available channels to secondary users. This problem known as the spectrum allocation problem is non-deterministic polynomial-time hard (NP-hard). Chaotic biogeographybased optimisation (CBBO) is a recently proposed evolutionary algorithm that can be applied to the above-mentioned problem. The authors compare CBBO with other popular algorithms in different spectrum allocation problem cases. The results show that CBBO performs in general better or similar to the other algorithms. 8 IET Netw.

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Power-Controlled Cognitive Radio Spectrum Allocation with Chemical Reaction Optimization

Cited by 24 publications

References 15 publications

Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

Spectrum allocation in cognitive radio networks using chaotic biogeography‐based optimisation

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