Optimal deployment of indoor wireless local area networks

We present a two‐phase methodology to address the problem of optimally deploying indoor wireless local area networks. In the first phase, we use Helmholtz's equation to simulate electromagnetic fields in a typical environment such as an office floor. The linear system which results from the dis...

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Bibliographic Details
Published in:Networks Vol. 81; no. 1; pp. 23 - 50
Main Authors: Oustry, Antoine, Le Tilly, Marion, Clausen, Thomas, D'Ambrosio, Claudia, Liberti, Leo
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.01.2023
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Subjects:
Computer Science
Electromagnetic fields
finite difference schema
frequency assignment
heuristics
indoor radio wave simulation
Linear algebra
Linear programming
Local area networks
Mathematical programming
mixed‐integer linear programming
Networking and Internet Architecture
Operations Research
Optimization
Partial differential equations
relaxation
Wireless networks
ISSN:0028-3045, 1097-0037
Online Access:Get full text
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Summary:We present a two‐phase methodology to address the problem of optimally deploying indoor wireless local area networks. In the first phase, we use Helmholtz's equation to simulate electromagnetic fields in a typical environment such as an office floor. The linear system which results from the discretization of this partial differential equation is solved with a state‐of‐the‐art library for sparse linear algebra. In the second phase, we formulate the network deployment problem in the setting of binary linear programming. This formulation employs the simulator output as input parameters, and jointly optimizes the number of access points, their locations, and their emission channels. We prove that this optimization problem is NP‐Hard, and use mathematical programming based techniques and heuristics to solve it. We present numerical experiments on medium‐sized buildings.
Bibliography:Funding information
Cisco Systems, Grant/Award Number: 594955; H2020 Marie Skłodowska‐Curie Actions, Grant/Award Number: 764759
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ISSN:0028-3045
1097-0037
DOI:10.1002/net.22116