Analysis and Design of Millimeter Wave Cellular Networks
Creators: name: Xu, Simin
Publisher: name: The Australian National University
Year: 2021

description: Millimeter wave (mmWave) communications has been widely acknowledged as an attractive strategy for the rapidly growing data rate requirements of cellular user equipments (UEs), due to the vast amounts of available frequencies at the mmWave band. However, the unique propagation characteristics of mmWave, including 1) high path loss, 2) extreme sensitivity to blockage, and 3) rapid channel fluctuations, bring serious challenges to the deployment of mmWave cellular networks. Against this background, this thesis focuses on the analysis and design of mmWave cellular networks. In Chapter 1, the motivation of the studies presented in this thesis is described. Moreover, a literature review of several key research topics is presented, including mmWave channel models, mmWave-enabled heterogeneous networks (HetNets), mmWave precoding, mmWave-based non-orthogonal multiple access (NOMA), and mmWave prototypes. Furthermore, an overview of this thesis is provided. In Chapter 2, a two-tier mmWave cellular HetNet is considered. As pointed out by the 3rd Generation Partnership Project (3GPP), a major issue in the HetNet is that high-power BSs are often heavily loaded, while low-power BSs are always lightly loaded and therefore not fully exploited. This load disparity inevitably leads to suboptimal resource allocation across the network, where a large number of UEs may be associated with one high-power BS but experience poor date rates. To increase the load of low-power BSs and strike a load balance between high-power BSs and low-power BSs, an association bias factor needs to be added to increase the possibility that UEs are associated with low-power BSs. In this chapter, we conduct novel analysis to assess the impact of the bias factor on the rate coverage performance of the considered network. In order to obtain tractable analytical results on the rate coverage probability, we model the considered network using a stochastic geometry based approach. We first analyze the loads of high-power BSs and low-power BSs, based on which we derive a new expression for the rate coverage probability of the network. Through numerical results, we demonstrate the correctness of our analysis. In addition, we thoroughly examine the impact of load balancing and various network parameters on the rate coverage probability, offering valuable guidelines on the design of practical mmWave HetNets. In Chapter 3, a relay assisted mmWave cellular network is considered. In this network, the BS adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay and then the relay transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. Similar to Chapter 2, in order to obtain tractable analytical results on the system-level coverage probability, we model the system using a stochastic geometry based approach. New expression is derived for the signal-to-interference-plus-noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe overestimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis. In Chapter 4, a summary of the conclusions drawn from this thesis is presented. Moreover, a number of future research directions are identified, including integrated mmWave/sub-6 GHz cellular networks, the mobility support in mmWave cellular networks, ultra-low latency mmWave cellular networks, and the transport layer design of mmWave cellular networks.