Spectrum Management Analysis for Cognitive Radio IoT

Nallarasan, V.; Kottilingam, K.

doi:10.1109/iccci50826.2021.9402690

Cited by 23 publications

(2 citation statements)

References 17 publications

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“…CR scans the spectrum for licensed users recognition to allow unlicensed users to utilize the assigned spectrum when it is not used as illustrated in Figure 1 [ 24 ]. Spectrum holes are the channels that are available and not in usage at the time and space of sensing [ 25 , 26 ].…”

Section: Cognitive Radio Overviewmentioning

confidence: 99%

LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network

Salika

Nasser

Mroue³

et al. 2022

Sensors

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In this paper, we propose a new protocol called LoRaCog to introduce the concept of Cognitive Radio (CR) in the LoRa network. LoRaCog will enable access to a wider spectrum than that of LoRaWAN by using the unutilized spectrum and thus has better efficiency without impacting the end devices’ battery consumption. LoRa networks are managed by LoRaWAN protocol and operate on the unlicensed Industrial, Scientific and Medical (ISM) band. LoRaWAN is one of thriving protocols for Low-Power Wide-Area Networks (LPWAN) implemented for the Internet of Things (IoT). With the growing demand for IoT, the unlicensed spectrum is expected to be congested, unlike the licensed spectrum, which is not fully utilized. This can be fairly balanced by applying CR to the LoRa network, where the End Devices (EDs) may change the operating channel opportunistically over the free/available licensed spectrum. Spectrum sensing, channel selection and channel availability relevance become essential features to be respected by the proposed protocol. The main objective of adding CR to LoRaWAN is reducing the congestion and maintaining LoRaWAN’s suitability for battery-operated devices. This is achieved by modifying LoRaWAN components such as the ED receive window RX2 rearrangement, spectrum sensing functionality by gateway (GW) for identifying unused channels, and reaching a decision on the unused channels by network server (NS). These changes will create LoRaCog meeting spectrum efficiency and maintain the same level of battery consumption as in LoRaWAN. Numerical simulations show a significant decrease in the rejected packet rate (more than 50%) with LoRaCog when more EDs use cognitive channels. As the results prove, LoRaWAN can reach above 50% rejected packets for the simulated environment versus 24% rejection for LoRaCog using only one additional channel (means total two channels). This means that the system can eliminate rejected packets almost completely when operating over the possible many channels. As well, these results show the flexibility in the system to utilize the available frequencies in an efficient and fair way. The results also reveal that a lower number of GWs is needed for LoRaCog from LoRaWAN to cover the same area.

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Section: Cognitive Radio Overviewmentioning

confidence: 99%

LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network

Salika

Nasser

Mroue³

et al. 2022

Sensors

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“…Where the jammers aim to indiscriminately advance their Jammer Received Signal Strength (JRSS), and the intruder's target is to decrease the overall privacy rate. In comparison to old strategies, a numerical number of outputs have verified and proven that the implemented game strategies are successful against the attackers with reference to data rate, secrecy rate and latency [1][2][3].…”

Section: Introductionmentioning

confidence: 96%

Jamming Attack Mitigation in CR-IoT Using Game Theory

Venkatachalam¹,

Kottursamy²

2022

RIA

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Jamming attack is Cognitive radio Internet of thing network disables the spectrum sharing and reduces the spectrum utilization .detection and mitigation of such attacks is the main component in realizing cognitive radio-based spectrum sharing in cognitive radio-based internet of thing network this work proposes a game theory-based jamming attack mitigation strategy. The problem of jamming attack mitigation is modeled as a zero-sum game and solved by finding Nash equilibrium. The cognitive node which tries to share the spectrum pays the zero-sum game with the jamming attacker and selects the best strategy of selecting the best frequency without getting into the jamming attack. The result of the proposed mechanism proves that the gaming mechanism can tackle the jamming attack.

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Detection Performance Analysis of Cooperative Spectrum Sensing UFMC-Based Cognitive Radio for 5G System

Mengistu,

Melesse

2023

Lecture Notes in Networks and Systems

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Spectrum Management Analysis for Cognitive Radio IoT

Cited by 23 publications

References 17 publications

LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network

LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network

Jamming Attack Mitigation in CR-IoT Using Game Theory

Detection Performance Analysis of Cooperative Spectrum Sensing UFMC-Based Cognitive Radio for 5G System

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