On predicting in-building WiFi coverage with a fast discrete approach
International Journal of Mobile Network Design and Innovation
Mono- and multiobjective formulations for the indoor wireless LAN planning problem
Computers and Operations Research
Dependable wireless mesh networks: An integrated approach
International Journal of Parallel, Emergent and Distributed Systems - Papers from the Workshop on Dependable Parallel and Network-Centric Systems
A multiobjective optimization framework for IEEE 802.16e network design and performance analysis
IEEE Journal on Selected Areas in Communications - Special issue on broadband access networks: Architectures and protocols
IEEE Transactions on Wireless Communications
LTE access network planning and optimization: a service-oriented and technology-specific perspective
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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Wireless LANs have experienced great success in the past five years. This technology has been quickly adopted in private and public areas to provide convenient network access. The fast pace of development has often induced an uncoordinated deployment strategy where WLAN planning tools have barely been used. This article highlights the difficulty of planning such wireless networks in indoor environments. The first issue that must be faced in WLAN planning is accurate description of the quality of a network based on realistic propagation predictions. The second issue is to implement a search strategy that provides several alternative solutions. Thus, the radio engineer can choose the most promising one among them based on his/her experience and maybe some additional constraints. A description of already proposed planning strategies is given and opens out onto a new multiobjective planning formulation. This formulation evaluates coverage, interference level, and quality of service (in terms of data throughput per user) to measure the quality of a planning solution. A Tabu multiobjective algorithm is then implemented to search for the optimal set of non-dominated planning solutions, and a final selection process extracts the most significant solutions for the end user. This multiobjective QoS-oriented method is illustrated with a practical example that shows the performance of looking for several solutions, each expressing different trade-offs between the planning objectives