Planning omni-present networks of the future

Abstract

On one hand, customers expect mobile broadband at any time and place at increasing bandwidth while on the other hand there is an evolution towards smart cities which include video monitoring and large amount of extra sensors putting additional strain on the existing network. Because of this, optimal long term network planning is of crucial importance. This planning has to take into account the ever increasing bandwidth demand and user adoption. In this publication, a genetic algorithm is proposed to find the optimal location of base stations to achieve a full coverage. Using this algorithm, a clear comparison has been made between a short-term (incremental) and a long-term (anticipated) planning. Keywords-network rollout; wireless network planning I.The role of an omni-present network in the smart city Bandwidth to any device is increasing and people are willing to pay to connect to rich media at all times. Recent evolutions in wireless networks open up higher bandwidth connections to the customer and the battle for customers has been recently focused on this aspect. Next to the end customers, smart cities are also a great driver for bandwidth, as many smart monitoring and feedback applications could greatly benefit from a high bandwidth and reliable connectionsWith the advent of sensor networks, cloud computing and wearable end devices, applications require to be constant online and have a sufficient bandwidth available. Many novel services target the customer end device and send dedicated data to these customers, but bandwidth demand is not limited to this server-to-client push or pull communication. As sensor maps and cloud computing demand bandwidth to push data quickly from input up to calculation and knowledge generation.Cities, transportation lines and hubs are, next to the traditional office and home environments, hotspots of these demands for bandwidth. While at home and at work, one or a limited amount of access points could suffice, a city wide network will require an area covering set of access points, providing sufficient bandwidth to customers in reach. An optimal tuning of this network is required and the first task to tackle is determining the amount and location of wireless access points to put in the network, in order to cover a full transportation line and/or part of a city. This will enable novel applications for people on the go, for machines on the road or track, detailed transportation monitoring, etc. all leading to the emergence of a true smart city.While the smart city is all about applications, clearly moving towards the smart city is about data, devices and linking these together. In this chicken-egg problem, the availability of an omni-present network triggered by a push from transportation and municipal investments could well be the stepping stone towards novel applications. The way to get there is to find the optimal match between costs, coverage and bandwidth for a continuously increasing bandwidth and connectivity demand. This paper focuses on developing a solid algorithmic basis...