Multi-radio network optimisation using Bayesian belief propagation

Colin McGuire; Stephan Weiss

Multi-radio network optimisation using Bayesian belief propagation

Colin McGuire, Stephan Weiss

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

3 Citations (Scopus)

65 Downloads (Pure)

Abstract

In this paper we show how 5 GHz and “TV White Space” wireless networks can be combined to provide fixed access for a rural community. Using multiple technologies allows the advantages of each to be combined to overcome individual limitations when assigning stations between networks. Specifically, we want to maximise throughput under the constraint of satisfying both the desired individual station data rate and the transmit power within regulatory limits. For this optimisation, we employ Pearl's algorithm, a Bayesian belief propagation implementation, which is informed by statistics drawn from network trials on Isle of Tiree with 100 households. The method confirms results obtained with an earlier deterministic approach.

Original language	English
Title of host publication	2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)
Publisher	IEEE
Pages	421-425
Number of pages	5
ISBN (Print)	978-0-9928626-1-9
Publication status	Published - Sept 2014
Event	22nd European Signal Processing Conference - Lisbon Congress Centre, Lisbon, Portugal Duration: 1 Sept 2014 → 5 Sept 2014 Conference number: 2014

Conference

Conference	22nd European Signal Processing Conference
Abbreviated title	EUSIPCO
Country/Territory	Portugal
City	Lisbon
Period	1/09/14 → 5/09/14

Keywords

Bayes methods
belief networks
radio networks
pearl algorithm
multiradio network optimisation

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AU - Weiss, Stephan

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AB - In this paper we show how 5 GHz and “TV White Space” wireless networks can be combined to provide fixed access for a rural community. Using multiple technologies allows the advantages of each to be combined to overcome individual limitations when assigning stations between networks. Specifically, we want to maximise throughput under the constraint of satisfying both the desired individual station data rate and the transmit power within regulatory limits. For this optimisation, we employ Pearl's algorithm, a Bayesian belief propagation implementation, which is informed by statistics drawn from network trials on Isle of Tiree with 100 households. The method confirms results obtained with an earlier deterministic approach.

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KW - pearl algorithm

KW - multiradio network optimisation

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BT - 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)

PB - IEEE

T2 - 22nd European Signal Processing Conference

Y2 - 1 September 2014 through 5 September 2014

ER -

Multi-radio network optimisation using Bayesian belief propagation

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Keywords

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