Research On Resource Allocation For MTC Applications In Cellular Networks

As the main application form of the Internet of Things (IoT), Machine Type Communication (MTC) is showing a booming trend. Deploying MTC depends on the connections between MTC devices and networks mostly, cellular networks are hence the most straightforward and realistic solution to enable the deployment for its ubiquitous coverage and low complexity connectivity. However, MTC has some significant characteristics, such as a huge number of devices, many application types and so on, it poses a serious challenge to the cellular networks resource allocation. Under such backgrounds, the research on resource allocation of MTC applications in cellular networks shows a great significance.In the cellular networks, the systems can be divided into several categories, such as random multiple access, Orthogonal Multiple Access (OMA) and Non Orthogonal Multiple Access (NOMA), according to its multiple access modes. Different multiple access methods will result in different effects on the resource management of cellular networks, for this reason, the dissertation mainly focuses on the resource allocation of MTC applications based on different multiple access modes, considering different system objectives.To tackle the resource allocation problems of MTC applications in the system of orthogonal multiple access mode, the dissertation presents an admission control and resource allocation joint optimization strategy. Firstly, we formulate an optimization problem of maximizing the number of MTC devices admitted in the networks to cope with the massive devices characteristic of MTC, considering the overload situation in Human to Human (H2H) and MTC co-existence scenario of OMA networks. For the reason that the optimization problem is Mixed Integer Non Linear Programming (MINLP), it is difficult to obtain the optimal solution. Because of the complexity of solving MINLP problems, then, relaxing constraints is used to transform the MINLP problem into a convex problem, which is the upper bound of the original problem. Lastly, in order to reduce the difficulty of solving convex problem, a low complicity admission control and resource allocation joint optimization algorithm is proposed. Simulation results show that the algorithm we proposed has minor degradation compared with the upper-bound, and is better than two other algorithms.To solve the resource allocation problems of MTC applications in the system of non orthogonal multiple access mode, the dissertation proposes a resource allocation strategy to maximize the weighted sum rate of the system. Firstly, according to the characteristics of the receiver in non orthogonal multiple access system, we establish the uplink data rate model of MTC devices. Then, basing on the data rate model, we formulate an optimization problem to maximize the weighted sum rate of the system. Because of the fact that the problem is non convex and discontinuous, we divide it into two sub problems:power allocation and sub carriers allocation. By using successive convex approximation and iterations, finally, we get the sub optimal solution to the original problem, and then propose a resource allocation algorithm which can maximize the weighted sum rate of the system, Simulation results show that the algorithm we proposed is better than the algorithm for comparison not only in the weighted sum rate aspect, but also in the number of connections aspect.