Performance Improvement by Introducing Mobility in Wireless Communication Networks

Communication technology is a major contributor to our lifestyles. Improving the performance of communication system brings with various benefits to human beings. This report covers two typical such systems: wireless sensor networks and cellular networks. Both relate to peoples lives closely. For example, people can use wireless sensor networks to get a better understanding of the environment; and use cellular networks to contact with others. We study the influence of mobility in these two networks. In wireless sensor networks, we consider the usage of mobile sinks to collect sensory data from static nodes. The mobile sinks can be attached to robots or vehicles. For the former case, we consider the non-holonomic model and propose a path planning algorithm. The generated paths are smooth, collision free, closed, and letting all the sensory data be collected. For the latter case, we design data collection protocols for a single mobile sink which aim at balancing the energy consumption among sensor nodes to improve the network lifetime. We also design an algorithm for multiple mobile sinks to collect urgent sensory information within the allowed latency. Regarding the mobility in cellular networks, we mean the service providers are mobile. Conventional approaches usually consider how to optimally deploy static base stations according to a certain metric, such as throughput. However, due to the explosive demands, it will be difficult to satisfy the user requirements by the current facilities. Base station densification is a solution, but it is not cost efficient, because of the high prices of renting sites and backhaul links. Introducing mobility is to let the base stations fly in the sky, resulting in less investment. We consider one of the key issues of using drones to serve cellular users: drone deployment. From simple to complex, we study how to deploy a given number of drones in the area of interest to maximize the served user number; and what is the minimum number of drones and their placements to serve all the users. We have implemented all the proposed algorithms by either simulations or experiments, and the results have confirmed the effectiveness of these approaches.