Optimization of spectrum sensing in cognitive radio using genetic algorithm

Deka, Rashmi; Chakraborty, Sayan; Roy, Swabarna

doi:10.2298/fuee1203235d

Cited by 17 publications

(12 citation statements)

References 15 publications

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“…For maximizing the throughput for SUs avoiding the collision trade‐off between sensing accuracy and transmission of data is described in Zhang et al and Al‐Doseri . For maximizing the utilities and many multiobjective functions, scientists took help of metaheuristic algorithms like genetic algorithm (GA) in Balieiro et al, Kamran and Moessner, and Khalid and Anpalagan . To solve the problem of channel allocation, game theory technique has been proposed.…”

Section: Introductionmentioning

confidence: 99%

Guided joint spectrum sensing and resource allocation using a novel random walk grey wolf optimization for frequency hopping cognitive radio networks

Karthikeyan

Srividhya

Kundu

2019

Int J Communication

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Summary Effective use of unused licensed spectrum by secondary nodes without causing any harmful interference to the primary users is one of the challenging task, and in this paper, a detailed description of joint spectrum sensing and resource allocation in cognitive radio (CR) networks is discussed. The CR system utility is maximized by joint spectrum sensing and channel resource allocation scheme based on random walk grey wolf optimization (RW‐GWO) algorithm for frequency hopping cognitive radio‐based networks. In this paper, the nodes will sense the presence of primary users in the same channel and move to another channel in the guidance of a guide node (GN) if primary signal is detected in the channel. In order to achieve collision‐free communication, primary signals and secondary signals use the channels strategically and the mechanism is described in this paper. RW‐GWO is used to derive the optimum sensing and data transmission schedules. It selects the sensing nodes to sense the spectrum and other nodes take part in transmitting the data. GNs not only guide the nodes to hop to the next channel if the primary channel is detected, but also distribute the nodes in different available secondary hopping channels. Simulation results show that reliable spectrum sensing and efficient channel allocation can be achieved in our proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Guided joint spectrum sensing and resource allocation using a novel random walk grey wolf optimization for frequency hopping cognitive radio networks

Karthikeyan

Srividhya

Kundu

2019

Int J Communication

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“…For example, it is used to optimize bit error rate performance in Deka et al, 19 spectrum sensing period, 20 transmit power allocation, 21 quality of service parameters, 22 and test-bed implementation under controlled radio environments. Genetic algorithm is well suited for multiobjective optimization problems in CR networks as it can search for the best possible solutions over a large search space under constraints whereas the traditional optimization techniques normally tend to be trapped at local optima.…”

Section: Introductionmentioning

confidence: 99%

Joint spectrum sensing and resource allocation optimization using genetic algorithm for frequency hopping–based cognitive radio networks

Yoo

Shrestha

Seo

et al. 2018

Int J Communication

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In cognitive radio (CR) networks, secondary users should effectively use unused licensed spectrums, unless they cause any harmful interference to the primary users. Therefore, spectrum sensing and channel resource allocation are the 2 main functionalities of CR networks, which play important roles in the performance of a CR system. To maximize the CR system utility, we propose a joint out-of-band spectrum sensing and operating channel allocation scheme based on genetic algorithm for frequency hopping-based CR networks.In this paper, to effectively sense the primary signal on hopping channels at each hopping slot time, a set of member nodes sense the next hopping channel, which is called out-of-band sensing. To achieve collision-free cooperative sensing reporting, the next channel detection notification mechanism is presented.Using genetic algorithm, the optimum sensing and data transmission schedules are derived. It selects a sensing node set that participate the spectrum sensing for the next expected hopping channel during the current channel hopping time and another set of nodes that take opportunity for transmitting data on the current hopping channel. The optimum channel allocation is performed in accordance with each node's individual traffic demand. Simulation results show that the proposed scheme can achieve reliable spectrum sensing and efficient channel allocation.

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“…The use of the unlicensed band by different communication systems must be still performed in accordance to some regulations, such as Dynamic Frequency Selection (DFS) and listen-before-talking (LBT). Thereby, different technologies, such as carrier sense multiple access or spectrum sensing [8], may be used. These coordination mechanisms, that are variants of dynamic spectrum access (DSA), are necessary, so that efficient co-existence between different systems in unlicensed spectrum can be maintained.…”

Section: Introductionmentioning

confidence: 99%

Wireless Networks Coexistence in Unlicensed Bands

Nikolić

Tošić

Milošević

et al. 2017

IJEEC

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-Mobile communication networks are constantly evolving, and each new generation provides considerably higher data transmission capabilities. Having in mind predictions of high cellular data traffic growth over the next few years, it is clear that the licensed band communications would have problems to support such a high bandwidth demand. One of the possible solutions to this problem is to adaptively use some additional spectrum out of the dedicated licensed band, such as the unlicensed bands. LTE-A standard introduced a new mechanism, named Carrier Aggregation, which provides the possibility to simultaneously use multiple frequency bands, such as the licensed and unlicensed bands. In order to work in an unlicensed band, LTE has to employ some new procedures that provide shared access with other systems using the same frequency band, such as WiFi. These procedures include spectrum sensing, dynamic frequency selection, as well as the coordination of the shared access. Performance measurements and the analysis of the procedures in 5 GHz frequency band will be shown in this paper. Since there is no available LTE hardware operating in 5 GHz band, it has to be made in a laboratory using the software radio approach. The description of such an experiment may be complex, and therefore we describe and propose the concept of the automatic experiment code generation. The automatic code generation is based on the semantic descriptions of experiments, and it is flexible due to the adoption of the domain and system ontologies for formal representation of the semantics of the problem.

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Optimization of spectrum sensing in cognitive radio using genetic algorithm

Cited by 17 publications

References 15 publications

Guided joint spectrum sensing and resource allocation using a novel random walk grey wolf optimization for frequency hopping cognitive radio networks

Guided joint spectrum sensing and resource allocation using a novel random walk grey wolf optimization for frequency hopping cognitive radio networks

Joint spectrum sensing and resource allocation optimization using genetic algorithm for frequency hopping–based cognitive radio networks

Wireless Networks Coexistence in Unlicensed Bands

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