Resource management and association control in heterogeneous wireless network environments

Abstract

As advanced mobile communication systems such as mobile WiMAX (Worldwide Interoperability for Microwave Access) and LTE (Long Term Evolution) have been deployed recently, multiple wireless networks begin to coexist and complement each other in various forms. Such environments are called heterogeneous wireless network or HetNet in short. Even though the concept of HetNet is not new since WLANs (Wireless Local Are Networks) have been widely used in hot-spot areas complementing 2G/3G cellular systems with their higher capacity, HetNet begins to attract both researchers' and practitioners' attention recently mainly due to two reasons. First, the advances in circuits, electronics, and micro-electronics have made it possible to access more than one network simultaneously at hardware level, which was not common for mobile devices to support in the past. Second, cellular systems now offer comparable performance to those of WLANs thanks to a number of advanced technologies, such as MIMO (Multiple Input Multiple Output) and OFDM (Orthogonal Frequency Division Multiplexing), and smaller cell sizes, e.g., femtocells.

In this dissertation, we deal with three different problems that can arise in HetNet. First, we deal with a cost minimization problem for a multi-homed mobile terminal that downloads and plays a Video-on-Demand (VoD) stream. The cost consists of the user's dissatisfaction due to playback disruptions and communication cost for downloading the VoD stream. There are three components in our approach: parameter estimation, threshold adjustment, and threshold compensation. Since we do not assume any a priori knowledge about underlying random variables, necessary parameter values are estimated online. Using the resultant estimates, we formulate the problem as a Markov Decision Process (MDP) problem considering as if the random variables are exponentially distributed. To solve the MDP problem efficiently, we propose a threshold adjustment algorithm that exploits some structural properties of any optimal solution that are specific to our problem. Finally, to handle the cases where the random variables are not exponentially distributed, we propose a threshold compensation algorithm to compensate for the modeling error. Through extensive simulations, we compare the performance of our scheme with those of static threshold schemes.

Next, we deal with a Mobile Collaborative Community (MCC) which is a group of people volunteering their resources to assist peer members in communication. We present a framework to utilize the wireless spectrum, the most scarce resource of a Mobile Network Operator (MNO), and the energy budget of mobile users in an MCC as efficiently as possible. Then we formulate the problem as the static and stochastic optimization. Additionally, we propose a fast heuristic algorithm to find the near optimal solution to the complicated optimization problem. Through extensive simulations, we evaluate how much the proposed scheme is of benefit to the MNO and users in MCC. The performance of our heuristic algorithm and the impacts of various parameters on the performance are also investigated.

Lastly, we study a Point of Attachment (PoA) selection problem which is an extended version of the cell-site selection problem to HetNet. Load balancing through cell-site selection in wireless networks has gained much attention as an efficient way to utilize scarce wireless resources. The goal of this study is to formulate a problem that aims to maximize the network-wide utility in HetNet with heterogeneous user device capabilities. We prove the problem is NP-Hard and propose a heuristic algorithm which is an extension of the existing local search algorithm. We evaluate the performance of our proposed algorithm against two received signal strength based approaches.