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User Assignment with Distributed Large Intelligent Surface (LIS) Systems

Hu, Sha LU ; Chitti, Krishna LU ; Rusek, Fredrik LU and Edfors, Ove LU (2018) IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2018
Abstract
In this paper, we consider a wireless communication system where a large intelligent surface (LIS) is deployed comprising a number of small and distributed LIS-Units. Each LIS-Unit has a separate signal process unit (SPU) and is connected to a central process unit (CPU) that coordinates the behaviors of all the LIS-Units. With such a LIS system, we consider the user assignments both for sum-rate and minimal user-rate maximizations. That is, assuming $M$ LIS-Units deployed in the LIS system, the objective is to select $K$ ($K\!\leq\!M$) best LIS-Units to serve $K$ autonomous users simultaneously. Based on the nice property of effective inter-user interference suppression of the LIS-Units, the optimal user assignments can be effectively... (More)
In this paper, we consider a wireless communication system where a large intelligent surface (LIS) is deployed comprising a number of small and distributed LIS-Units. Each LIS-Unit has a separate signal process unit (SPU) and is connected to a central process unit (CPU) that coordinates the behaviors of all the LIS-Units. With such a LIS system, we consider the user assignments both for sum-rate and minimal user-rate maximizations. That is, assuming $M$ LIS-Units deployed in the LIS system, the objective is to select $K$ ($K\!\leq\!M$) best LIS-Units to serve $K$ autonomous users simultaneously. Based on the nice property of effective inter-user interference suppression of the LIS-Units, the optimal user assignments can be effectively found through classical linear assignment problems (LAPs) defined on a bipartite graph. To be specific, the optimal user assignment for sum-rate and user-rate maximizations can be solved by linear sum assignment problem (LSAP) and linear bottleneck assignment problem (LBAP), respectively. The elements of the cost matrix are constructed based on the received signal strength (RSS) measured at each of the $M$ LIS-Units for all the $K$ users. Numerical results show that, the proposed user assignments are close to optimal user assignments both under line-of-sight (LoS) and scattering environments. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2018
conference location
Bologna, Italy
conference dates
2018-09-09 - 2018-09-12
external identifiers
  • scopus:85060538856
ISBN
978-1-5386-6009-6
978-1-5386-6010-2
DOI
10.1109/PIMRC.2018.8580675
language
English
LU publication?
yes
id
a8da6707-9ec6-4ad8-b4e8-e8720f003e6e
date added to LUP
2017-09-07 09:02:37
date last changed
2019-02-27 05:10:49
@inproceedings{a8da6707-9ec6-4ad8-b4e8-e8720f003e6e,
  abstract     = {In this paper, we consider a wireless communication system where a large intelligent surface (LIS) is deployed comprising a number of small and distributed LIS-Units. Each LIS-Unit has a separate signal process unit (SPU) and is connected to a central process unit (CPU) that coordinates the behaviors of all the LIS-Units. With such a LIS system, we consider the user assignments both for sum-rate and minimal user-rate maximizations. That is, assuming $M$ LIS-Units deployed in the LIS system, the objective is to select $K$ ($K\!\leq\!M$) best LIS-Units to serve $K$ autonomous users simultaneously. Based on the nice property of effective inter-user interference suppression of the LIS-Units, the optimal user assignments can be effectively found through classical linear assignment problems (LAPs) defined on a bipartite graph. To be specific, the optimal user assignment for sum-rate and user-rate maximizations can be solved by linear sum assignment problem (LSAP) and linear bottleneck assignment problem (LBAP), respectively. The elements of the cost matrix are constructed based on the received signal strength (RSS) measured at each of the $M$ LIS-Units for all the $K$ users. Numerical results show that, the proposed user assignments are close to optimal user assignments both under line-of-sight (LoS) and scattering environments.},
  author       = {Hu, Sha and Chitti, Krishna and Rusek, Fredrik and Edfors, Ove},
  isbn         = {978-1-5386-6009-6 },
  language     = {eng},
  location     = {Bologna, Italy},
  month        = {12},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {User Assignment with Distributed Large Intelligent Surface (LIS) Systems},
  url          = {http://dx.doi.org/10.1109/PIMRC.2018.8580675},
  year         = {2018},
}