A route stability-based multipath QoS routing protocol in cognitive radio ad hoc networks

AlQahtani, Salman A.; Alotaibi, Amerah M.

doi:10.1007/s11276-019-02014-6

Cited by 26 publications

(14 citation statements)

References 20 publications

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“…Therefore, previous activity of the SUs and PUs and previous channel utilization is observed, and then accordingly, the time slot to perform packet delivery is selected. AlQahtani and Alotaibi further extended the previous work and also proposed a routing metrics to select routing paths with higher stability.…”

Section: Channel Assignment In Literaturementioning

confidence: 95%

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Gupta

Dhurandher

2019

Int J Communication

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Summary With the advent of various emerging wireless products, the usage of limited spectrum has grown exponentially in the recent years. In the next few years, that mobile data traffic globally is expected to grow up to 50 EB/month, which is nearly a five times increase over year 2018. Therefore, it will become extremely difficult to satisfy the ever increasing demand through the current fixed spectrum assignment policy in which spectrum band is exclusively used for the particular applications, and it has also led to underutilization of a significant portion of the spectrum (like TV bands). Cognitive radio networks has emerged as a possible solution for the problem which makes dynamic spectrum access possible for unlicensed user when licensed user is not active. Among various operations of cognitive radio, channel assignment to the unlicensed user is very important. Further, wireless regional area network is one of the most important application of cognitive radio, which provides wireless broadband to the rural area using vacant TV channels. This paper discusses channel assignment techniques considering various functionalities for cognitive radio networks in respect of wireless regional area network in the existing literature. Initially, a comprehensive introduction to both cognitive radio networks and wireless regional area networks is provided, and in the end, the paper summarizes the various issues and research challenges in the channel assignment for wireless regional area networks.

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Section: Channel Assignment In Literaturementioning

confidence: 95%

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Gupta

Dhurandher

2019

Int J Communication

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“…is protocol ensures the path stability in terms of high connectivity but not offers the best QoS path. Similarly, recently Complexity a routing solution is offered to reduce the channel switching events during the transmission using the mobility pattern of PU [32]. is protocol offers the routing predictions based on the user mobility and previous routing pattern matching, which results in higher channel selection time due to the lower mobility and routing pattern prediction.…”

Section: Complexitymentioning

confidence: 99%

Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks

Malik

Hasan

2020

Complexity

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In the existing network-layered architectural stack of Cognitive Radio Ad Hoc Network (CRAHN), channel selection is performed at the Medium Access Control (MAC) layer. However, routing is done on the network layer. Due to this limitation, the Secondary/Unlicensed Users (SUs) need to access the channel information from the MAC layer whenever the channel switching event occurred during the data transmission. This issue delayed the channel selection process during the immediate routing decision for the channel switching event to continue the transmission. In this paper, a protocol is proposed to implement the channel selection decisions at the network layer during the routing process. The decision is based on past and expected future routing decisions of Primary Users (PUs). A learning agent operating in the cross-layer mode of the network-layered architectural stack is implemented in the spectrum mobility manager to pass the channel information to the network layer. This information is originated at the MAC layer. The channel selection is performed on the basis of reinforcement learning algorithms such as No-External Regret Learning, Q-Learning, and Learning Automata. This leads to minimizing the channel switching events and user interferences in the Reinforcement Learning- (RL-) based routing protocol. Simulations are conducted using Cognitive Radio Cognitive Network simulator based on Network Simulator (NS-2). The simulation results showed that the proposed routing protocol performed better than all the other comparative routing protocols in terms of number of channel switching events, average data rate, packet collision, packet loss, and end-to-end delay. The proposed routing protocol implies the improved Quality of Service (QoS) of the delay sensitive and real-time networks such as Cellular and Tele Vision (TV) networks.

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“…In work [3], the issues of effective distribution of the infrastructure of multipath network of wireless mobile phones charging are studied. Research [4] discusses the multipath routing protocol that ensures stability of information transmission in cognitive radio networks. Paper [5] deals with specific features of occurrence of mutual interference at optimal single-step routing for the organization of the D2D connection.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…In known studies [1][2][3][4][5][6], when solving the problem of routing in communications networks, the scalar approach based on taking into consideration only one quality indicator is used. This determines the relevance of the studies aimed at the solution of the problem of optimal routing in communications networks, taking into consideration the totality of quality indicators by using the methods for multicriterial optimization.…”

Section: Introductionmentioning

confidence: 99%

Methods for multicriterial selection of optimal routes in communication networks

Guo

Semenets

Bezruk

et al. 2019

EEJET

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Традиційно задачі маршрутизації у мережах зв'язку вирішуються на основі скалярного підходу, при якому враховуються тільки один показник якості. Однак передача інформації у мережах зв'язку характеризується сукупністю показників якості. Тому для отримання оптимального рішення задачі маршрутизації у мережах зв'язку повинен бути використаний багатокритеріальний підхід. Це визначає актуальність розв'язання проблеми маршрутизації у мережах зв'язку з урахуванням сукупності показників якості, що характеризують якість передачі інформації. Для розв'язання цієї проблеми в даній роботі використані методи багатокритеріальної оптимізації. Запропоновано методи дискретного вибору підмножини Парето-оптимальних варіантів маршрутизації з урахуванням сукупності показників якості. При цьому виключаються безумовно гірші варіанти маршрутизації і забезпечуються потенціально можливі значення сукупності показників якості. Також це дає можливість організації багатошляхової маршрутизації, при якій забезпечується рівномірна загрузка усіх ліній зв'язку. Досліджені практичні особливості застосування вибраних методів багатокритеріальної оптимізації для вибору оптимальних маршрутів у мережах зв'язку з урахуванням сукупності показників якості. Показані переваги і обмеження багатокритеріального підходу до розв'язання проблеми маршрутизації у мережах зв'язку. Результати роботи корисні для фахівців, які займаються плануванням і проектуванням оптимальних мереж зв'язку Ключові слова: передача інформації, мережа зв'язку, проектування, оптимальна маршрутизація, сукупність показників якості, багатокритеріальна оптимізація

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A route stability-based multipath QoS routing protocol in cognitive radio ad hoc networks

Cited by 26 publications

References 20 publications

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks

Methods for multicriterial selection of optimal routes in communication networks

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