Resource allocation in optical beam-steered indoor networks

M. Torres Vega, J. Famaey, A.M.J. Koonen, A. Liotta

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
213 Downloads (Pure)

Abstract

Optical Wireless (OW) technologies deploying narrow multiwavelength light beams offer a promising alternative to traditional wireless indoor communications as they provide higher bandwidths and overcome the radio spectrum congestion typical of the 2.4 and 5GHz frequency bands. However, unlocking their full potential requires exploring novel control and management techniques. Specifically, there is a need for efficient and intelligent resource management and localization techniques that allot wavelengths and capacity to devices. In this paper we present a resource allocation model for one such indoor optical wireless approach, a Beam-steered Reconfigurable Optical-Wireless System for Energy-efficient communication (BROWSE). BROWSE aims to supply each user within a room with its own downstream infrared light beam with at least 10Gbps throughput, while providing a 60GHz radio channel upstream. Using Integer Linear Programming (ILP) techniques, we have designed and implemented a resource allocation model for the BROWSE OW downstream connection. The designed model optimises the trade-off between energy-consumption and throughput, while providing TDM capabilities to effectively serve densely deployed devices with a limited number of simultaneous available wavelengths. Through several test-scenarios we have assessed the model’s performance, as well as its applicability to future ultra-high bandwidth video streaming applications.
Original languageEnglish
Title of host publicationIEEE/IFIP Network Operations and Management Symposium (NOMs 2016), 25-29 April 2016, Istanbul, Turkey
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages418-426
ISBN (Electronic)978-1-5090-0223-8
DOIs
Publication statusPublished - 4 Jul 2016

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