Genetic Algorithm-Based Hybrid Spectrum Handoff Strategy in Cognitive Radio-Based Internet of Things

Abstract In Cognitive radio-based Internet of Things (CR-IoT) systems, the return of the primary user (PU) causes the secondary user (SU) that is communicating to face the spectrum handoff problem. In the process of spectrum handoff, the user terminal can’t get the idle channels in time because of the unknown channel usage state. To solve this problem, a hybrid spectrum handoff algorithm based on the channel idle probability is proposed. The algorithm considers the regularity of PU activities in space and time, defines the idle probability of channels from the perspective of week attributes and time periods, obtains the optimal time period length using genetic algorithm, generates a channel idle probability table, and provides the target channel sequence for SUs in combination with the proposed channel ordering scheme. Simulation results show that the hybrid spectrum switching algorithm based on the channel idle probability can reduce the energy consumption of SUs during spectrum switching, reduce the communication interruption rate, enable SUs to find idle channels faster and reduce the number of sensing times.

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Spectrum Sensing for Cognitive Radio Using Genetic Algorithm

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v14i09.9064 ◽

2018 ◽

Vol 14 (09) ◽

pp. 190 ◽

Cited By ~ 1

Author(s):

Shewangi Kochhar ◽

Roopali Garg

Keyword(s):

Genetic Algorithm ◽

Cognitive Radio ◽

False Alarm ◽

Spectrum Sensing ◽

Optimization Technique ◽

Primary User ◽

Time Frame ◽

Probability Of False Alarm ◽

Sensing Time ◽

Better Than

<p>Cognitive Radio has been skillful technology to improve the spectrum sensing as it enables Cognitive Radio to find Primary User (PU) and let secondary User (SU) to utilize the spectrum holes. However detection of PU leads to longer sensing time and interference. Spectrum sensing is done in specific “time frame” and it is further divided into Sensing time and transmission time. Higher the sensing time better will be detection and lesser will be the probability of false alarm. So optimization technique is highly required to address the issue of trade-off between sensing time and throughput. This paper proposed an application of Genetic Algorithm technique for spectrum sensing in cognitive radio. Here results shows that ROC curve of GA is better than PSO in terms of normalized throughput and sensing time. The parameters that are evaluated are throughput, probability of false alarm, sensing time, cost and iteration.</p>

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Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

Applied Sciences ◽

10.3390/app10051674 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1674 ◽

Cited By ~ 1

Author(s):

Kaleem Arshid ◽

Iftikhar Hussain ◽

Muhammad Khawar Bashir ◽

Shahid Naseem ◽

Allah Ditta ◽

...

Keyword(s):

Cognitive Radio ◽

Cognitive Radio Networks ◽

Service Time ◽

Primary User ◽

Spectrum Management ◽

Radio Networks ◽

Secondary User ◽

Traffic Pattern ◽

Spectrum Handoff ◽

Cognitive Radio User

Through the expeditious expansion of the wireless network, the unlicensed bandwidth-based devices are growing substantially as compared to the present vacant bandwidth. Cognitive radio networks present a proficient solution to the spectrum shortage diminution hitch by allowing the usage of the vacant part of the spectrum that is not currently in use of the Primary User licensed bandwidth to the secondary user or cognitive radio user. Spectrum management procedure in cognitive radio network comprises of spectrum sharing, sensing and handoff. Spectrum handoff plays a vital role in spectrum management and primarily focuses on single handoff strategies. This paper presents a primary user traffic pattern-based opportunistic spectrum handoff (PUTPOSH) approach to use in the cognitive radio networks. PUTPOSH permits a secondary user to sense the arrival of a primary user and use an opportunistic handoff scheme. The opportunistic handoff scheme firstly detects the arrival of the primary users by energy detection sensing and secondly, it allows a cognitive radio user to decide whether to do handoff or not contingent upon the overall service time to reduce the unused handoffs. The handoffs can either be reactive or proactive based on the arrival rate of the primary user. The simulation results show that the presented PUTPOSH approach (a) minimizes the number of handoffs and the overall service time, and (b) maintains the channel utilization and throughput of the system at a maximal point.

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Spectrum Handoff by Baum-Welch algorithm for services in Cognitive Radio Networks

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l3184.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 1717-1721

Keyword(s):

Cognitive Radio ◽

Markov Model ◽

Cognitive Radio Networks ◽

Transition Probabilities ◽

Primary User ◽

Radio Networks ◽

Available Bandwidth ◽

Spectrum Handoff ◽

Neural Network Algorithm ◽

Limited Spectrum

Cognitive Radio Networks (CRN) is the upcoming future prospect in 5G networks. Lack of available spectrum is a serious problem in the networking industry nowadays since, for each individual organization only a limited spectrum bandwidth is offered by National Telecommunications and Information Administration (NTIA). The problem arises due to the increase in the number of users who are supposed to use a limited amount of available bandwidth. Using spectrum handoff allows a cognitive user to access the available licensed spectrum in the absence of the primary user in that particular channel. Efficient spectrum sensing has to be done to check the availability of unused spectrum holes. Machine learning models such as Markov model and Hidden Markov model are used to predict the probabilities. In this paper we have presented a model for efficient sensing using Baum-Welch algorithm, a neural network algorithm which can train inner layer channel traits for given sequence of switching services to yield accurate results without huge datasets. Following emission probabilities are obtained for the channels that are trained from transition probabilities of channel services such as video, voice and data. From the obtained probability values each channel can be offered with best suited services.

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Spectrum Handoff in Cognitive Radio Networks: A Survey

Oriental journal of computer science and technology ◽

10.13005/ojcst/10.04.10 ◽

2017 ◽

Vol 10 (04) ◽

pp. 765-772 ◽

Cited By ~ 1

Author(s):

Nisar Lala ◽

Altaf Balkhi ◽

G M Mir

Keyword(s):

Cognitive Radio ◽

Cognitive Radio Networks ◽

Primary User ◽

Radio Networks ◽

Spectrum Utilization ◽

Secondary Users ◽

Spectrum Handoff ◽

Suitable Target ◽

Promising Solution ◽

Minimum Performance

Cognitive radio (CR) is a promising solution to improve the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Spectrum handoff is a different type of handoff in CR necessitated by the reappearance of primary user (PU) in the licensed band presently occupied by the secondary users (SUs). Spectrum handoff procedures aim to help the SUs to vacate the occupied licensed spectrum and find suitable target channel to resume the unfinished transmission. The purpose of spectrum mobility management in cognitive radio networks is to make sure that the transitions are made smoothly and rapidly such that the applications running on a cognitive user perceive minimum performance degradation during a spectrum handoff. In this paper, we will survey the literature on spectrum handoff in cognitive radio networks.

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The Allocation in Cognitive Radio Network: Combined Genetic Algorithm and ON/OFF Primary User Activity Models

Lecture Notes in Electrical Engineering - Advances in Ubiquitous Networking 2 ◽

10.1007/978-981-10-1627-1_1 ◽

2016 ◽

pp. 3-14

Author(s):

Yasmina El Morabit ◽

Fatiha Mrabti ◽

El Houssein Abarkan

Keyword(s):

Genetic Algorithm ◽

Cognitive Radio ◽

Cognitive Radio Network ◽

Primary User ◽

Radio Network ◽

User Activity ◽

Activity Models

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Spatial–Temporal Sensing and Utilization in Full Duplex Spectrum-Heterogeneous Cognitive Radio Networks for the Internet of Things

Sensors ◽

10.3390/s19061441 ◽

2019 ◽

Vol 19 (6) ◽

pp. 1441 ◽

Cited By ~ 10

Author(s):

Waqas Khalid ◽

Heejung Yu

Keyword(s):

Cognitive Radio ◽

Internet Of Things ◽

Primary User ◽

Activity Level ◽

Full Duplex ◽

The Internet ◽

Heterogeneous Environments ◽

Secondary Users ◽

Continuous Growth ◽

The Internet Of Things

The continuous growth of interconnected devices in the Internet of Things (IoT) presents a challenge in terms of network resources. Cognitive radio (CR) is a promising technology thatcan address the IoT spectral demands by enabling an opportunistic spectrum access (OSA) scheme. The application of full duplex (FD) radios in spectrum sensing enables secondary users (SUs) to perform sensing and transmission simultaneously, and improves the utilization of the spectrum. However, random and dense distributions of FD-enabled SU transmitters (FD-SU TXs) with sensing capabilities in small-cell CR-IoT environments poses new challenges, and creates heterogeneous environments with different spectral opportunities. In this paper, we propose a spatial and temporal spectral-hole sensing framework for FD-SU TXs deployed in CR-IoT spectrum-heterogeneous environment. Incorporating the proposed sensing model, we present the analytical formulation and an evaluation of a utilization of spectrum (UoS) scheme for FD-SU TXs present at different spatialpositions. The numerical results are evaluated under different network and sensing parameters to examine the sensitivities of different parameters. It is demonstrated that self-interference, primary user activity level, and the sensing outcomes in spatial and temporal domains have a significant influence on the utilization performance of spectrum.

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