Ultra dense networks with directional antennas, like millimetre wave (mmWave) networks, have some promising features about secure communications. This chapter explores the potential of physical layer security in mmWave ultra dense networks. Specifically, we mainly introduced the impact of mmWave channel characteristics, random blockages, and antenna gains on the secrecy performance. Our results reveal that mmWave frequency to high mmWave frequency is demanded to obtain a higher secrecy rate. In addition, new antenna pattern models are needed to well characterize the effective antenna gain for a random interferer seen by the typical receiver when the number of mmWave antennas grows large.

Due to the proliferation of smart devices, internet-of-things (IoT) devices, and device-to-device (D2D) communications, the amount of mobile traffic is ever-growing. To satisfy this skyrocketing wireless data traffic demand of mobile users, the densification of the network is unaviodable. However, the denser network not only improves the transmission rate, but also increases the impact of interferences. Therefore, careful deployment of base stations (BSs) is needed to guarantee the communication quality. This chapter provides insights into the deployment of BSs in the multi-layer ultra dense network (UDN). Throughout this chapter, we will model the channel between the BSs and a typical user equipment (UE) by considering the antenna height of the BSs and derive the expressions for the interference, the coverage probability, and the area spectral efficiency (ASE) of our considered multi-layer UDN using stochastic geometry. Through numerical results, we will show how the network performance can be maximized by selecting the proper antenna heights and the densities of BSs in the multi-layer UDN.

In recent years, the overall network data traffic is dramatic increasing,a promising solution is the deployment of ultra dense networks (UDNs) combined with millimeter wave (mmWave) communication technology, which is expected to enhance the overall performance of the network in terms of energy efficiency and load balancing. In this chapter,user association and power allocation inmmWave-based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. This chapter not only establish the system utility optimal function model in the limitations of power and QoS, but also gives an iterative gradient user association and power allocation algorithm to resolve the optimization issue. This algorithm provides a best ratio of convergence and can get a near optimal scheme. In addtion, through utilizing Lagrangian dual decomposition, the dual optimization issue is disintegrated to two sub-problems, we can resolve them respectively. The simulation datum indicate that our method is effective.