Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users\u27 Stochastic Dynamics

During emergency situations, the public safety communication systems (PSCSs) get overloaded with high traffic loads. Note that these PSCSs are finite source networks. The goal of our study is to propose techniques for an efficient allocation of spectrum in finite source networks that can help alleviate the overloading of PSCSs. In a PSCS, there are two system segments, one for the system-access control and the other for communications, each having dedicated frequency channels. The first part of our research, consisting of three projects, is based on modeling and analysis of finite source systems for optimal spectrum allocation, for both access-control and communications. In the first project, Chapter 2, we study the allocation of spectrum based on the concept of cognitive radio systems. In the second project, Chapter 3, we study the optimal communication channel allocation by call admission and preemption control. In the third project, Chapter 4, we study the optimal joint allocation of frequency channels for access-control and communications. Note that the aforementioned spectrum allocation techniques require the knowledge of the call traffic parameters and the priority levels of the users in the system. For practical systems, these required pieces of information are extracted from the call records meta-data. A key fact that should be considered while analyzing the call records is that the call arrival traffic and the users priority levels change with a change in events on the ground. This is so because a change in events on the ground affects the communication behavior of the users in the system, which affects the call arrival traffic and the priority levels of the users. Thus, the first and the foremost step in analyzing the call records data for a given user, for extracting the call traffic information, is to segment the data into time intervals of homogeneous or stationary communication behavior of the user. Note that such a segmentation of the data of a practical PSCS is the goal of our fourth project, Chapter 5, which constitutes the second part of our study

Optimal admission and preemption control in finite-source loss systems

We study the optimal control of both admission and preemption in a two-class finite source loss system, and prove that the optimal low priority (LP) job admission policy is a state dependent threshold based policy. We also provide the sufficient cost conditions for which the LP job admission and preemption are always optimal. Finally, we demonstrate that the optimal LP job preemption policy is a threshold based policy, using numerical results