Traffic Pattern Prediction Based Spectrum Sharing for Cognitive Radios

Li, Xiukui; Zekavat, S.A.

doi:10.5772/7838

Cited by 13 publications

(11 citation statements)

References 60 publications

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“…Wang et al [25] refer that several research works have indicated that channel occupancy exhibits behavioural patterns and can be statistically modelled. However, different traffic models apply to different applications (e.g., voice communication, video data, and general packet data) [54]. In CR scenarios, primary user traffic is usually modelled as a binary sequence of alternating busy (ON) and idle (OFF) states with variable durations.…”

Section: Primary User Traffic Modellingmentioning

confidence: 99%

Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

2011

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Currently, the radio spectrum is statically allocated and divided between licensed and unlicensed frequencies. Due to this inflexible policy, some frequency bands are growing in scarcity, while large portions of the entire radio spectrum remain unused independently of time and location. Cognitive Radio is a recent network paradigm that aims a more flexible and efficient usage of the radio spectrum. Basically, it allows wireless devices to opportunistically access portions of the entire radio spectrum without causing any harmful interference to licensed users. The present document surveys the literature on Cognitive Radio. It aims to provide a comprehensive and self-contained description of this research topic area, mainly focusing on communication protocols, spectrum decision issues, and future research directions. It is a tutorial in nature and consequently does not require any previous knowledge about Cognitive Radio. Readers are only required to have some general background on wireless data networks. Emphasis is put on Cognitive Radio genesis, issues that must be addressed, related technologies, standardization efforts, the state of the art, and future research directions according to the vision of the authors.

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Section: Primary User Traffic Modellingmentioning

confidence: 99%

Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

2011

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“…Considered Network Publication Year Description [11] 2010 Residual idle time distribution scheme to estimate the transmission duration in remaining idle time [12] 2010 A proactive scheme for unlicensed users to perform channel switching before licensed user appear on the network [13] 2009 The need to perform intelligent channel decision for improved utilization [14] CRNs 2009 Improved spectrum sharing based on traffic pattern prediction in cognitive radio networks [15] 2008 Forecasting the traffic pattern to reduce the frequency hopping rate and interference effects in CRNs [16] 2008 The intelligent utilization of channel histories to predict the forthcoming PR activities If any PR node appear on the same channel during CRSN communication, the CRSN node has to immediately leave the channel for PR communication. The addition of CR capability to wireless sensor nodes for effective spectrum utilization has also invoked certain challenges as well.…”

Section: Referencesmentioning

confidence: 99%

Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks

2018

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Channel Bonding (CB) is a technique used to provide larger bandwidth to users. It has been applied to various networks such as wireless local area networks (WLANs), Wireless Sensor Networks (WSNs), Cognitive Radio Networks (CRNs), and Cognitive Radio Sensor Networks (CRSNs). The implementation of CB in CRSNs needs special attention as Primary Radio (PR) nodes traffic must be protected from any harmful interference by Cognitive Radio (CR) sensor nodes. On the other hand, CR sensor nodes need to communicate without interruption to meet their data rate requirements and conserve energy. If CR nodes perform frequent channel switching due to PR traffic then it will be difficult to meet their quality of service (QoS) and data rate requirements. So, CR nodes need to select those channels which are stable. By stable, we mean those channels which having less PR activity or long remaining idle time and cause less harmful interference to PR nodes. In this paper, we propose two approaches Remaining Idle Time aware intelligent Channel Bonding (RITCB) and Remaining Idle Time aware Intelligent Channel Bonding with Interference Prevention (RITCB-IP) for cognitive radio sensor networks which select stable channels for CB which have longest remaining idle time. We compare our approaches with four schemes such as Primary radio user activity aware channel bonding scheme (PRACB), Sample width algorithm (SWA), Cognitive radio network over white spaces (KNOWS) and AGILE. Simulation results show that our proposed approaches RITCB and RITCB-IP decrease harmful interference (HIR) and increases the life time of cognitive radio sensor nodes. Index Terms-Channel bonding; cognitive radio; dynamic spectrum access; wireless sensor networks; channel switching; primary user activity; remaining idle time. 1 We use the term CR nodes and CRSN nodes for the same types of nodes throughout the manuscript and they are used interchangeably.

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“…The authors [8,9] have presented different traffic forecast procedures and have discussed about the process of assessing channel accessibility through predicting traffic patterns of PUs for cognitive radios in an infrastructure of CR network as clarified in [5] above. In this model, SUs can forecast the call arrival rate and call holding time of primary users that utilized this channel.…”

Section: Literature Surveymentioning

confidence: 99%

Call Arrival Rate Prediction and Blocking Probability Estimation for Infrastructure based Mobile Cognitive Radio Personal Area Network

Nathani¹,

Manna²

2017

Adv. sci. technol. eng. syst. j.

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The Cognitive Radio usage has been estimated as non-emergency service with low volume traffic. Present work proposes an infrastructure based Cognitive Radio network and probability of success of CR traffic in licensed band. The Cognitive Radio nodes will form cluster. The cluster nodes will communicate on Industrial, Scientific and Medical band using IPv6 over Low-Power Wireless Personal Area Network based protocol from sensor to Gateway Cluster Head. For Cognitive Radio-Media Access Control protocol for Gateway to Cognitive Radio-Base Station communication, it will use vacant channels of licensed band. Standalone secondary users of Cognitive Radio Network shall be considered as a Gateway with one user. The Gateway will handle multi-channel multi radio for communication with Base Station. Cognitive Radio Network operators shall define various traffic data accumulation counters at Base Station for storing signal strength, Carrier-to-Interference and Noise Ratio, etc. parameters and record channel occupied/vacant status. The researches has been done so far using hour as interval is too long for parameters like holding time expressed in minutes and hence channel vacant/occupied status time is only probabilistically calculated. In the present work, an infrastructure based architecture has been proposed which polls channel status each minute in contrary to hourly polling of data. The Gateways of the Cognitive Radio Network shall monitor status of each Primary User periodically inside its working range and shall inform to Cognitive Radio-Base Station for preparation of minutewise database. For simulation, the occupancy data for all primary user channels were pulled in one minute interval from a live mobile network. Hourly traffic data and minutewise holding times has been analyzed to optimize the parameters of Seasonal Auto Regressive Integrated Moving Average prediction model. The blocking probability of an incoming Cognitive Radio call has been assessed as a function of instantaneous occupancy and the blocksize of trunk servers.

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Traffic Pattern Prediction Based Spectrum Sharing for Cognitive Radios

Cited by 13 publications

References 60 publications

Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks

Call Arrival Rate Prediction and Blocking Probability Estimation for Infrastructure based Mobile Cognitive Radio Personal Area Network

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