Modeling of initial contention window size for successful initial ranging process in IEEE 802.22 WRAN cell

Afzal, Humaira; Awan, Irfan; Mufti, Muhammad Rafiq; Sheriff, Ray E.

doi:10.1016/j.simpat.2014.11.007

Cited by 6 publications

(7 citation statements)

References 33 publications

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“…and b) the knowledge of IU signal power as well as noise power [97]. The IEEE 802.22 working group on WRANs recommended that the target false alarm probability ̅̅̅̅ , and target detection probability ̅̅̅ should be 0.1 and 0.9 respectively [184]. Therefore, the optimal threshold based on each target is calculated as follows [98]:…”

Section: Threshold Settingmentioning

confidence: 99%

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Comprehensive Survey on Quality of Service Provisioning Approaches in Cognitive Radio Networks: Part One

Fakhrudeen

Alani

2017

Int J Wireless Inf Networks

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Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part.

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Section: Threshold Settingmentioning

confidence: 99%

“…(4) & Eq. (5), an increase in observed samples increasesand noise uncertainty may decrease it[184]; this fact is illustrated Threshold setting (modified from[183]). Fig.…”

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confidence: 99%

Comprehensive Survey on Quality of Service Provisioning Approaches in Cognitive Radio Networks: Part One

Fakhrudeen

Alani

2017

Int J Wireless Inf Networks

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“…22 working group has been formed to develop the first international standard for wireless regional area networks (WRAN). Its basic purpose is to provide broadband access in remote and rural areas by effectively utilizing the unused TV band provided that no harmful interference is caused to the licensed users which may be digital TV, analog TV or wireless microphone [14], [15]. For more details about TV band and their related important issues, readers are directed to [16].…”

Section: Introductionmentioning

confidence: 99%

A framework for dynamic selection of backoff stages during initial ranging process in wireless networks

Mufti

Afzal

Awan

et al. 2017

Journal of Systems and Software

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Following are the answers to the comments of reviewers. The answers are in blue text. All queries have been addressed and author(s) have tried their best to make modifications as suggested. Reviewer #1: The work provides an innovative mathematical methodology regarding the selection process and association process for IEEE 802.22 networks. The approach is largely evaluated for several cases and is robust enough to serve as a knowledge base for the Base Station. Since the discussed environment is related to TV white spaces I would suggest to add to the introduction a well established review work on the topic, namely,

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“…A CR technology [13][14][15][16][17][18] has appeared as a hopeful solution to eliminate the problems of spectrum scarcity and inefficiency of its usage in wireless systems. Its basic idea is to permit unlicensed users to use the licensed band when the licensed channels are free.…”

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confidence: 99%

“…23,24 Basic functions of a CRN include spectrum decision, spectrum sensing, spectrum sharing, and spectrum handoff. 17,18 A lot of work has been done to maximize the performance of spectrum sharing and spectrum management. [25][26][27][28] Different methods and techniques regarding CRN have been developed to evaluate and improve the performance of the network, for example, improving spectrum sensing, utilizing the number of channels, improving and effectively utilizing the bandwidth of available channels, efficient handoff, and throughput management.…”

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confidence: 99%

Performance analysis of QoS in IoT based cognitive radio Ad Hoc network

Afzal

Mufti

Raza

et al. 2020

Concurrency and Computation

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Since the advent of Internet of Things (IoT), there is a dramatic increase in the number of devices being connected to networks. This increase causes spectrum shortage for devices competing to share the limited spectrum. Wireless IoT devices mostly utilize unlicensed radio spectrum. Soon, the bands in this spectrum will become overcrowded causing collisions among subscribers that will result in scarcity of spectrum.Therefore, in order to ease the smooth running and frequent proliferation in IoT objects, the efficient use of radio spectrum is necessary. One of the solutions to this problem is cognitive radio (CR) that has gained the attention among researchers.The network, formed by CRs, allows an unlicensed user to occupy and use the spectrum of a licensed user/primary user (PU) when the spectrum is found to be free.In this work, these two technologies are combined to get the advantages of both in ad hoc manner while relating this concept with trunking theory. The distances of CRs from nearby PUs are calculated using radio frequency identifications (RFIDs), and then based on these distances, some quality-of-service (QoS) parameters of CR network are analyzed. The main objective of this study is to go through the performance analysis of CR network integrated with IoT in the non-queued system. Numerical results show that this integration is beneficial for the survival of future wireless technologies. K E Y W O R D Scognitive radio, cognitive radio ad hoc network (CRAHN), internet of things (IoT), quality of service (QoS), trunked system INTRODUCTIONWireless networks promote mobility by allowing devices to move freely and save cost of installing cables, enabling us to expand networks to even remote areas. Such advantages encourage more devices to connect to wireless networks. Improvements in network infrastructure and increased speed, reliability, and ease in every successive generation (2G, 3G, and 4G) have encouraged more and more services being provided over wireless networks. These networks use a band of spectrum called radio spectrum for communication, having frequencies from 30 Hz to 300 GHz. In order to allow different technologies to utilize these frequencies, radio spectrum is divided into small chunks called frequency bands. For example, AM radio is assigned 300 KHz to 3 MHz frequency band; VHF television is assigned 30 to 300 MHz, etc.The spectrum bands can be broadly categorized as licensed and unlicensed bands. To transmit on the assigned channels within the given geographical area, with exclusive rights, individual companies have to pay a licensing fee, which enables the wireless operators to not interfere with the transmissions of other users. Licensing is unfeasible for certain uses, such as interaction between a wireless keyboard and a PC, or interaction

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Modeling of initial contention window size for successful initial ranging process in IEEE 802.22 WRAN cell

Cited by 6 publications

References 33 publications

Comprehensive Survey on Quality of Service Provisioning Approaches in Cognitive Radio Networks: Part One

Comprehensive Survey on Quality of Service Provisioning Approaches in Cognitive Radio Networks: Part One

A framework for dynamic selection of backoff stages during initial ranging process in wireless networks

Performance analysis of QoS in IoT based cognitive radio Ad Hoc network

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