Set optimization for efficient interference alignment in heterogeneous networks

Bibliographic Details
Main Author: Castanheira, Daniel
Publication Date: 2014
Other Authors: Silva, Adão, Gameiro, Atílio
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10773/12528
Summary: To increase capacity and offload traffic from the current macro-cell cellular system operators are considering the deployment of small-cells. It is expected that both the small and macro-cells will coexist in the same spectrum resulting in unsustainable levels of interference. Interference alignment is considered as an effective method to deal with such interfer- ence. By using interference alignment the small-cells align their transmission along a common direction to allow the macro-cell receiver to completely remove it. It is clear that if the two systems have no limitations on the information that may be exchanged between them to perform the signal design, then the performance may be improved in comparison to the case of no or partial cooperation. However, this full cooperation strategy requires a high-rate connection between the macro and small-cells, which may not be available. To overcome this problem we consider that the alignment direction is selected from a finite set, known to both macro and small-cell terminals. We provide sufficient conditions for this set that guarantee full-diversity, at the macro- cell, and propose an efficient method to optimize the set elements. Results show that an alignment set with a description length of 1 bit is enough to achieve the same diversity as in the case where an infinite amount of information is exchanged between both systems. The proposed set optimization method achieves better performance than random vector quantization and similar performance to Grassmannian quantization.
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spelling Set optimization for efficient interference alignment in heterogeneous networksSmall-cellsInterference AlignmentZero-ForcingMIMO SystemsDiversity MethodsCodebook DesignRayleigh ChannelsFeedbackRandom Vector QuantizationTo increase capacity and offload traffic from the current macro-cell cellular system operators are considering the deployment of small-cells. It is expected that both the small and macro-cells will coexist in the same spectrum resulting in unsustainable levels of interference. Interference alignment is considered as an effective method to deal with such interfer- ence. By using interference alignment the small-cells align their transmission along a common direction to allow the macro-cell receiver to completely remove it. It is clear that if the two systems have no limitations on the information that may be exchanged between them to perform the signal design, then the performance may be improved in comparison to the case of no or partial cooperation. However, this full cooperation strategy requires a high-rate connection between the macro and small-cells, which may not be available. To overcome this problem we consider that the alignment direction is selected from a finite set, known to both macro and small-cell terminals. We provide sufficient conditions for this set that guarantee full-diversity, at the macro- cell, and propose an efficient method to optimize the set elements. Results show that an alignment set with a description length of 1 bit is enough to achieve the same diversity as in the case where an infinite amount of information is exchanged between both systems. The proposed set optimization method achieves better performance than random vector quantization and similar performance to Grassmannian quantization.Institute of Electrical and Electronics Engineers (IEEE)2014-07-28T10:37:20Z2014-06-01T00:00:00Z2014-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/12528eng1536-127610.1109/TWC.2014.2322855Castanheira, DanielSilva, AdãoGameiro, Atílioinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-06T03:50:55Zoai:ria.ua.pt:10773/12528Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:48:36.047036Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Set optimization for efficient interference alignment in heterogeneous networks
title Set optimization for efficient interference alignment in heterogeneous networks
spellingShingle Set optimization for efficient interference alignment in heterogeneous networks
Castanheira, Daniel
Small-cells
Interference Alignment
Zero-Forcing
MIMO Systems
Diversity Methods
Codebook Design
Rayleigh Channels
Feedback
Random Vector Quantization
title_short Set optimization for efficient interference alignment in heterogeneous networks
title_full Set optimization for efficient interference alignment in heterogeneous networks
title_fullStr Set optimization for efficient interference alignment in heterogeneous networks
title_full_unstemmed Set optimization for efficient interference alignment in heterogeneous networks
title_sort Set optimization for efficient interference alignment in heterogeneous networks
author Castanheira, Daniel
author_facet Castanheira, Daniel
Silva, Adão
Gameiro, Atílio
author_role author
author2 Silva, Adão
Gameiro, Atílio
author2_role author
author
dc.contributor.author.fl_str_mv Castanheira, Daniel
Silva, Adão
Gameiro, Atílio
dc.subject.por.fl_str_mv Small-cells
Interference Alignment
Zero-Forcing
MIMO Systems
Diversity Methods
Codebook Design
Rayleigh Channels
Feedback
Random Vector Quantization
topic Small-cells
Interference Alignment
Zero-Forcing
MIMO Systems
Diversity Methods
Codebook Design
Rayleigh Channels
Feedback
Random Vector Quantization
description To increase capacity and offload traffic from the current macro-cell cellular system operators are considering the deployment of small-cells. It is expected that both the small and macro-cells will coexist in the same spectrum resulting in unsustainable levels of interference. Interference alignment is considered as an effective method to deal with such interfer- ence. By using interference alignment the small-cells align their transmission along a common direction to allow the macro-cell receiver to completely remove it. It is clear that if the two systems have no limitations on the information that may be exchanged between them to perform the signal design, then the performance may be improved in comparison to the case of no or partial cooperation. However, this full cooperation strategy requires a high-rate connection between the macro and small-cells, which may not be available. To overcome this problem we consider that the alignment direction is selected from a finite set, known to both macro and small-cell terminals. We provide sufficient conditions for this set that guarantee full-diversity, at the macro- cell, and propose an efficient method to optimize the set elements. Results show that an alignment set with a description length of 1 bit is enough to achieve the same diversity as in the case where an infinite amount of information is exchanged between both systems. The proposed set optimization method achieves better performance than random vector quantization and similar performance to Grassmannian quantization.
publishDate 2014
dc.date.none.fl_str_mv 2014-07-28T10:37:20Z
2014-06-01T00:00:00Z
2014-06-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/12528
url http://hdl.handle.net/10773/12528
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1536-1276
10.1109/TWC.2014.2322855
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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