Classification-based predictive channel selection for cognitive radios

Marko Höyhtyä; Sofie Pollin; Aarne Mämmelä

doi:10.1109/ICC.2010.5501787

Classification-based predictive channel selection for cognitive radios

Marko Höyhtyä, Sofie Pollin, Aarne Mämmelä

Katholieke Universiteit Leuven (KU Leuven)

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

49 Citations (Scopus)

Abstract

The proposed method classifies traffic patterns of primary channels in cognitive radio systems and applies different prediction rules to different types of traffic. This allows a more accurate prediction of the idle times of primary channels. An intelligent channel selection scheme then uses the prediction results to find the channels with the longest idle times for secondary use. We tested the method with Pareto and exponentially distributed stochastic traffic and with deterministic traffic. The predictive method using past information improves the throughput of the system compared to a system based on instantaneous idle time information. The classification-based predictive method improves the performance compared to pure prediction when the channels of interest include both stochastic and deterministic traffic. The amount of collisions with a primary user can drop 60% within a given interval compared to a predictive system operating without classification.

Original language	English
Title of host publication	2010 IEEE International Conference on Communications
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	1-6
ISBN (Electronic)	978-1-4244-6404-3, 978-1-4244-6403-6
ISBN (Print)	978-1-4244-6402-9
DOIs	https://doi.org/10.1109/ICC.2010.5501787
Publication status	Published - 2010
MoE publication type	A4 Article in a conference publication
Event	IEEE International Conference on Communications, ICC 2010 - Cape Town, South Africa Duration: 23 May 2010 → 27 May 2010

Conference

Conference	IEEE International Conference on Communications, ICC 2010
Abbreviated title	ICC 2010
Country/Territory	South Africa
City	Cape Town
Period	23/05/10 → 27/05/10

Keywords

cognitive radio
traffic control
prediction methods
analytical models
throughput
stochastic processes
microelectronics

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10.1109/ICC.2010.5501787

Cite this

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title = "Classification-based predictive channel selection for cognitive radios",

abstract = "The proposed method classifies traffic patterns of primary channels in cognitive radio systems and applies different prediction rules to different types of traffic. This allows a more accurate prediction of the idle times of primary channels. An intelligent channel selection scheme then uses the prediction results to find the channels with the longest idle times for secondary use. We tested the method with Pareto and exponentially distributed stochastic traffic and with deterministic traffic. The predictive method using past information improves the throughput of the system compared to a system based on instantaneous idle time information. The classification-based predictive method improves the performance compared to pure prediction when the channels of interest include both stochastic and deterministic traffic. The amount of collisions with a primary user can drop 60% within a given interval compared to a predictive system operating without classification.",

keywords = "cognitive radio, traffic control, prediction methods, analytical models, throughput, stochastic processes, microelectronics",

author = "Marko H{\"o}yhty{\"a} and Sofie Pollin and Aarne M{\"a}mmel{\"a}",

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doi = "10.1109/ICC.2010.5501787",

language = "English",

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pages = "1--6",

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note = "IEEE International Conference on Communications, ICC 2010, ICC 2010 ; Conference date: 23-05-2010 Through 27-05-2010",

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Höyhtyä, M, Pollin, S & Mämmelä, A 2010, Classification-based predictive channel selection for cognitive radios. in 2010 IEEE International Conference on Communications. IEEE Institute of Electrical and Electronic Engineers, pp. 1-6, IEEE International Conference on Communications, ICC 2010, Cape Town, South Africa, 23/05/10. https://doi.org/10.1109/ICC.2010.5501787

Classification-based predictive channel selection for cognitive radios. / Höyhtyä, Marko; Pollin, Sofie; Mämmelä, Aarne.
2010 IEEE International Conference on Communications. IEEE Institute of Electrical and Electronic Engineers, 2010. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Classification-based predictive channel selection for cognitive radios

AU - Höyhtyä, Marko

AU - Pollin, Sofie

AU - Mämmelä, Aarne

PY - 2010

Y1 - 2010

N2 - The proposed method classifies traffic patterns of primary channels in cognitive radio systems and applies different prediction rules to different types of traffic. This allows a more accurate prediction of the idle times of primary channels. An intelligent channel selection scheme then uses the prediction results to find the channels with the longest idle times for secondary use. We tested the method with Pareto and exponentially distributed stochastic traffic and with deterministic traffic. The predictive method using past information improves the throughput of the system compared to a system based on instantaneous idle time information. The classification-based predictive method improves the performance compared to pure prediction when the channels of interest include both stochastic and deterministic traffic. The amount of collisions with a primary user can drop 60% within a given interval compared to a predictive system operating without classification.

AB - The proposed method classifies traffic patterns of primary channels in cognitive radio systems and applies different prediction rules to different types of traffic. This allows a more accurate prediction of the idle times of primary channels. An intelligent channel selection scheme then uses the prediction results to find the channels with the longest idle times for secondary use. We tested the method with Pareto and exponentially distributed stochastic traffic and with deterministic traffic. The predictive method using past information improves the throughput of the system compared to a system based on instantaneous idle time information. The classification-based predictive method improves the performance compared to pure prediction when the channels of interest include both stochastic and deterministic traffic. The amount of collisions with a primary user can drop 60% within a given interval compared to a predictive system operating without classification.

KW - cognitive radio

KW - traffic control

KW - prediction methods

KW - analytical models

KW - throughput

KW - stochastic processes

KW - microelectronics

U2 - 10.1109/ICC.2010.5501787

DO - 10.1109/ICC.2010.5501787

M3 - Conference article in proceedings

SN - 978-1-4244-6402-9

SP - 1

EP - 6

BT - 2010 IEEE International Conference on Communications

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - IEEE International Conference on Communications, ICC 2010

Y2 - 23 May 2010 through 27 May 2010

ER -

Classification-based predictive channel selection for cognitive radios

Abstract

Conference

Keywords

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