The Optimization Of Indoor Wireless Networks Planning

The increasing number of mobile device users has led an increasing number of wireless network deployments. As generally assumed, mobile devices are mostly used indoors. The indoor wireless network planning problem has attracted a lot of attention from researchers. Due to the huge popularity of wireless networks, human exposure to radio-frequency sources, power consumption,interference and installation cost of wireless networks that still have good coverage will be increasingly important in the coming years. As these requirements are contradictory, it is not straight forward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. The main contributions of this thesis are listed as follows1.Multi-objective indoor homogeneous wireless network planning optimization algorithm: human exposure, power consumption, cost, and capacityDue to the huge popularity of wireless networks, human exposure to radio-frequency sources, power consumption and economic cost of wireless networks that still have good coverage will be increasingly important in the coming years. As these requirements are contradictory, it is not straight forward to design optimal wireless networks. In this thesis a developed genetic algorithm(GA) that generates further optimizations of indoor wireless network planning solutions, which is named Hybrid Indoor Genetic Optimization(HIGO) algorithm. The algorithm is compared with a heuristic network planner and Composite Differential Evolution(CoDE) algorithm for three scenarios and for two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage, minimum power consumption, minimal cost, and minimal human exposure.2. Indoor wireless homogeneous network planning for advanced exposure and installation cost minimizationHowever, concerns about the potential health impact of exposure to RF(Radio Frequency) sources have arisen and are getting accounted for in wireless network planning.In addition to adequate coverage and reduced human exposure, the installation cost of the wireless network is also an important criterion in the planning process. In this thesis, an algorithm is presented for optimal indoor wireless network planning, based on a maximization of coverage and a minimization of the full installation cost(not only access point cost) and the human exposure. Advanced fitness functions are presented, accounting for the total installation cost in a realistic way, and introducing exposure sensitivity levels per room.3. An algorithm for optimal wireless homogeneous network planning and frequency channel assignment in indoor WLANsAn algorithm is proposed for optimal network planning and frequency planning. It yields a network satisfying a user-imposed coverage requirement with a minimal number of access points and with a minimal interference between the access points. The frequency planning algorithm is based on a greedy algorithm and on a vertex-coloring approach, in which the coverage range and location of APs are taken into account. This network optimization algorithm is applied to an office environment and shows a good performance, while computation times are kept short.4. Multi-objective algorithm to indoor wireless heterogeneous networks planningWe also consider heterogeneous networks consisting of WiFi Access Points(APs)and Long Term Evolution(LTE) femtocells. The problem of heterogeneous network planning for optimal coverage with the high coverage rate, the lowest power consumption and the lowest exposure is addressed in this thesis. An application for a realistic office environment is investigated leading to reductions of power and exposure when multi-objective algorithms are applied. In this thesis, a combination of two algorithms,a genetic algorithm(GA) and a quasi-particle swarm optimization(quasi-PSO), is developed, yielding a novel hybrid algorithm. The algorithm has been compared against GA for the network planning problem.In summary, this thesis takes efforts on multi-objective indoor wireless network planning in both homo and heterogeneous environment. A series of simulations show that the proposed four optimization algorithm satisfy the requirements of high coverage,low power consumption, low exposure level, low interference and low install cost.