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User Assignment wit...
User Assignment with Distributed Large Intelligent Surface (LIS) Systems
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- Hu, Sha (author)
- Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
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- Chitti, Krishna (author)
- Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
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- Rusek, Fredrik (author)
- Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
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- Edfors, Ove (author)
- Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
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(creator_code:org_t)
- 2018
- 2018
- English.
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In: 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). - 9781538660096 - 9781538660102
- Related links:
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http://dx.doi.org/10...
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https://lup.lub.lu.s...
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https://doi.org/10.1...
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Abstract
Subject headings
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- 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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
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