The impressive market spread of IEEE 802.11 based wireless local area networks (WLAN) calls for quantitative approaches in the network planning procedure. It is common belief that such networks have the potential to replace traditional indoor wired local networks and allow flexible access outdoors, eventually competing with classical cellular systems (GSM, GPRS, UMTS, etc.). The appropriate positioning of the access points (AP) is crucial to determining the network effectiveness. In a companion paper we argue that previously proposed approaches to coverage planning neglect the features of the IEEE 802.11 access mechanism, which limits system capacity when access point coverage areas overlap. We describe the optimization models with hyperbolic and quadratic objective functions that directly accounts system capacity and we propose heuristics combining greedy and local search phases. Computational results show that our heuristics provide near-optimal solutions within a reasonable amount of time.

WLAN Coverage Planning: Optimization Models and Alghorithms

AMALDI, EDOARDO;CAPONE, ANTONIO;CESANA, MATTEO;MALUCELLI, FEDERICO;
2004

Abstract

The impressive market spread of IEEE 802.11 based wireless local area networks (WLAN) calls for quantitative approaches in the network planning procedure. It is common belief that such networks have the potential to replace traditional indoor wired local networks and allow flexible access outdoors, eventually competing with classical cellular systems (GSM, GPRS, UMTS, etc.). The appropriate positioning of the access points (AP) is crucial to determining the network effectiveness. In a companion paper we argue that previously proposed approaches to coverage planning neglect the features of the IEEE 802.11 access mechanism, which limits system capacity when access point coverage areas overlap. We describe the optimization models with hyperbolic and quadratic objective functions that directly accounts system capacity and we propose heuristics combining greedy and local search phases. Computational results show that our heuristics provide near-optimal solutions within a reasonable amount of time.
Proceedings of VTC 2004
0780382552
TLC
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/250991
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