Modeling and analysis of device-to-device communications and interference management in heterogeneous cellular networks
Date of Issue2016
School of Electrical and Electronic Engineering
Driven by the exponential increase in wireless data traffic, cellular networks are undergoing an unprecedented paradigm shift in the way that data is delivered to the mobile users. The high spectral efficiency and energy efficiency of short-range transmissions make small cell and device-to-device (D2D) networks as the key enablers of this shift. In this dissertation, we develop realistic and tractable analytical frameworks based on random spatial models (using tools from stochastic geometry) for modeling and analysis of the fundamental aspects of D2D networks and small cell deployments. In the context of D2D networks, this dissertation first develops a new spatial model in which the locations of D2D devices are modeled according to a Poisson cluster process. Using this model, we study the performance of a typical D2D receiver in terms of coverage probability and area spectral efficiency (ASE) for device-centric content placement. Here, the content of interest is available at the kth closest device from the typical device inside the same cluster. We discuss in detail the maximum and minimum gains, in terms of the coverage probability and ASE, achievable in the clustered D2D networks when such content placement is performed. The developed tools can be used to model various other smart content placement strategies where the content of interest lies closer to the typical device. Second, the proposed clustered D2D network model is used to develop a comprehensive analytical framework that characterizes the performance of cluster-centric content placement in cache enabled D2D networks. Different from device-centric content placement, cluster-centric content placement focuses on placing data in each cluster such that the collective performance of all the devices in the cluster is optimized. Using this model, we characterize the performance of the D2D network in terms of coverage probability and ASE under a variety of cluster-centric content placement strategies. Third, the cluster-centric analysis demonstrates significant improvement in the network performance when the device on which content is cached or device requesting content from a cache is biased to lie (or move) closer to the cluster center. Based on this insight, we develop and analyze a new generative double-variance Thomas cluster process model to incorporate such biased transmissions in the coverage and ASE analysis. Fourth, in the context of small cell deployments, this dissertation provides a baseline analytical framework to address the technical aspects of uplink and downlink communication in hybrid division duplex (HDD)-based two-tier heterogeneous networks. We propose coordinated interference management techniques that work in conjunction with uplink power control (in HDD-mode) to enhance the network performance. The effects of the proposed interference mitigation mechanisms on the whole network are captured by modeling the locations of transmitters as a Poisson hole process. The analysis shows significant improvement of the coverage probability under proposed dynamic interference mitigation.