Spectrum sensing challenges &amp; their solutions in cognitive radio based vehicular networks

Hossain, Awlad; Noor, Rafidah Md; Azzuhri, Saaidal Razalli; Z’aba, Muhammad Reza; Ahmedy, Ismail; Yau, Kok‐Lim Alvin; Chembe, Christopher

doi:10.1002/dac.4748

Cited by 18 publications

(6 citation statements)

References 66 publications

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“…SU does the spectrum sensing (finding out the presence or absence of any PU) [24]. At the same time, segment management and channel allocation management are carried by RSUs.…”

Section: Proposed Routing Algorithmmentioning

confidence: 99%

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Multi-Objective Harris Hawks Optimization Algorithm Based 2-Hop Routing Algorithm for CR-VANET

et al. 2021

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Vehicular Ad Hoc Network (VANET) emerges to ameliorate road accident, traffic congestion, and infotainment. Cognitive radio (CR) is integrated with VANET (termed as CR-VANET) to deal with the spectrum scarcity problems. For better data transmission, routing is very important in a highly dynamic CR-VANET environment. Routing in CR-VANET has several challenges due to vehicles' high-speed movements and channel accessibility issues. This paper proposes a 2-Hop routing algorithm based on the Multi-Objective Harris Hawks Optimization (2HMO-HHO) algorithm that chooses the optimal forwarders between the source and destination vehicles. Selecting 2-hops instead of multiple hops or the entire route increases the selected route's stability and assures successful data transmission. The simulations performed in OMNeT++ with SUMO show that the proposed algorithm achieves promising results on throughput, delay, packet delivery ratio, packet loss rate and communication overhead.INDEX TERMS VANET; routing algorithm; 2-hop routing; Harris Hawks Optimization; cognitive radio; throughput; packet delivery ratio; delay; packet loss rate; communication overhead.

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“…SU does the spectrum sensing (finding out the presence or absence of any PU) [24]. At the same time, segment management and channel allocation management are carried by RSUs.…”

Section: Proposed Routing Algorithmmentioning

confidence: 99%

“…Here, PUs are considered static, and they follow a simple ON/OFF PU activity [24]. SUs are equipped with two antennas, one for DSRC and another for CR usage.…”

Section: B Application Scenariomentioning

confidence: 99%

Multi-Objective Harris Hawks Optimization Algorithm Based 2-Hop Routing Algorithm for CR-VANET

et al. 2021

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“…This smart sensing strategy adopts a pre‐emptive switching mechanism which helps in alternating between higher quality channels for the objective of preventing jamming attacks that are introduced by malicious users. This strategy included a power conserving protocol that saved power when the condition of low bandwidth is essentially realized in the network 12 . It is also considered to be a more intelligent radio which completely focusses on improving QoS through the selection of frequency channels that inherits a maximized rate of signal to noise ratio (SNR).…”

Section: Introductionmentioning

confidence: 99%

“…This strategy included a power conserving protocol that saved power when the condition of low bandwidth is essentially realized in the network. 12 It is also considered to be a more intelligent radio which completely focusses on improving QoS through the selection of frequency channels that inherits a maximized rate of signal to noise ratio (SNR). Despite a number of advantages provisioned by the cognitive radio toward the aspect of handling spectrum scarcity problem, its implementation is determined to introduce certain potential challenges.…”

Section: Introductionmentioning

confidence: 99%

Certificateless linkable ring signature‐based blockchains for securing cognitive radio networks

Kumari

Guru²,

Manoharan³

et al. 2022

Concurrency and Computation

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Rapid advancement in industrial applications of Internet of Things (IoT) has dramatically increased the number of Internet connected devices resulting in big challenges of scalability, adaptability, connectivity, and accessibility. Cognitive radio is efficient in handling spectrum allocation problem by facilitating the allocation of unlicensed spectrum dynamically to the IoT applications. However, cognitive radio network (CRN) capability of spectrum sensing is highly vulnerable to diversified number of security attacks. Malicious user disturbs the spectrum sensing potential and minimizes its accuracy by launching attacks during the detection of primary signal. In this article, certificateless linkable ring signature-based blockchains (CLRSB) is proposed for securing CRNs by achieving reliable discrimination between trustworthy users through cryptographic keys. It initially transformed the complete set of users such as PUs and SUs into the structure of blocks representing the smart contracts-based traditional public ledger blockchain that gets integrated to form a decentralized network for attaining improvement in efficient spectrum sensing. It adopted a mayfly optimization algorithm (MFOA)-improved CNN (MFOA-ICNN)-based spectrum sensing method for preventing the interference between PUs and SUs during spectrum access. It also used MFOA for optimizing the features with balanced trade-off between exploration and exploitation to identify the remarkable features that attributes toward efficient spectrum sensing. It specifically used CLRS for protecting information about the transaction initiator for the objective of protecting blockchain privacy. Simulation experiments of this CLRSB confirmed better response time and minimized frame loss on an average by 18.13% and 17.81%, better than the baseline schemes used for investigation.

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“…It aims to achieve accident-free tra c and smooth roads ow with a small congestion probability.There are many communication methods to transmit data between cars. One of the V2V communication system methods is radio frequency (RF) communication (Hossain, 2021). However, due to the popularity of RF, the RF channels are mostly booked and crowded.…”

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confidence: 99%

Car To Car Communication Using RF Cognitive Radio with VLC Common Control Channel

Okasha

Zekry

Newagy

2023

Preprint

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This paper combines the advantages of both cognitive radio (CR) communication and visible light communication (VLC) for car-to-car applications to achieve a higher data rate, low delay, minimum outage probability, minimum cost, and minimum bit error rate (BER). CR technology hops among the existing radio frequency (RF) available channels to increase the RF spectrum usage efficiency and dodge the scarcity limitation. Moreover, using CR as a license-free application will reduce car-to-car communication costs. However, CRs require a common control channel (CCC) to communicate the spectrum availability map within the CR network and to inform the receiver end about the change in the transmitter-end channel. Therefore, the CCC is the bottleneck in the car-to-car CR network. Therefore, we explore the types of CCCs and use each of them to solve this bottleneck issue. In the proposed scheme, we assume alternative CCCs such as licensed overlay, unlicensed CR overlay in the ISM band, underlay CR, and using VLC. A MATLAB simulation for a car-to-car framework is built to demonstrate and compare these types of CCC through the chosen metrics. Our metrics include data rate, delay, outage probability, cost, and bit error rate. The comparison analyses shall include comparing VLC versus the other CCC types. We compare practical systems, not the theoretically achievable system therefore the results might prefer a CCC type according to one metric and prefer another type of CCC due to the second metric. Our results show that VLC can achieve up to 90% of the licensed data rate with a small outage probability of 21.2% while maintaining moderate BER and delay. In addition, VLC presents the minimum cost, and as the introduced combined metric it placed second after the licensed type with a score of 84.2%. In conclusion, with the VLC’s bright future of expansion and growing the car-to-car application, we have proven VLC is worthy of implementation practically in modern cars.

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Spectrum sensing challenges & their solutions in cognitive radio based vehicular networks

Cited by 18 publications

References 66 publications

Multi-Objective Harris Hawks Optimization Algorithm Based 2-Hop Routing Algorithm for CR-VANET

Multi-Objective Harris Hawks Optimization Algorithm Based 2-Hop Routing Algorithm for CR-VANET

Certificateless linkable ring signature‐based blockchains for securing cognitive radio networks

Car To Car Communication Using RF Cognitive Radio with VLC Common Control Channel

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