Base Station Placement in Integrated Aerial and Terrestrial Wireless Cellular Networks

Abstract

Base station (BS) location is an important problem in designing cellular networks since its solution has a profound impact on the overall network performance. An optimal BS location depends on the traffic distribution, propagation pathloss and many system parameters, which renders its analytical study difficult so that numerical algorithms are widely used instead. In this thesis, the problem is studied analytically from a fundamental perspective. By formulating the problem as a convex optimization problem, we can characterize the globally-optimum location and obtain a number of closed-form solutions and insights.

Afterwards, we consider drones as aerial BSs that can enhance network coverage or capacity by moving supply towards demand when required. Utilizing drone-BSs (DBSs) is a promising approach to boost the agility and flexibility of future wireless networks. The specific attributes of drones such as mobility could be especially useful for future applications with extreme demands. DBSs can play a remarkable role as a communication network facilitator when the temporal and spatial variations in user densities and rates are expected to result in difficult-to-predict traffic patterns. However, deploying DBSs in a network presents several challenges. One important issue is finding the efficient 3D placement of DBSs to satisfy the dynamic requirements of the system. Another challenge is the limited wireless backhaul capacity of DBSs and consequently, higher latency incurred. This issue can be alleviated by providing content caching in DBSs to decrease backhaul congestion and latency. In this thesis, we find locations of DBSs for various network objectives such as minimizing the number of DBSs or the transmit power, maximizing the number of covered users or total rate of the users in a wireless network, while considering the restrictions of the network such as finite backhaul capacity, disparate quality of service requirement of users, and limited access bandwidth into account. To this end, we propose various mathematical frameworks and efficient algorithms to design, optimize, and deploy drone-based communication systems. We also obtain user-BS associations and bandwidth allocations in different scenarios which is an involved problem due to mobility of DBSs. Extensive simulation results demonstrate the effectiveness of the proposed algorithms and provide useful insights that can be used to develop design guidelines.