Ultra-Dense Networks: Is There a Limit to Spatial Spectrum Reuse?

The aggressive spatial spectrum reuse (SSR) by network densification using smaller cells has successfully driven the wireless communication industry onward in the past decades. In our future journey toward ultra-dense networks (UDNs), a fundamental question needs to be answered. Is there a limit to SSR? In other words, when we deploy thousands or millions of small cell base stations (BSs) per square kilometer, is activating all BSs on the same time/frequency resource the best strategy? In this paper, we present theoretical analyses to answer such question. In particular, we find that both the signal and interference powers become bounded in practical UDNs with a non-zero BS-to-UE antenna height difference and a finite UE density, which leads to a constant capacity scaling law. As a result, there exists an optimal SSR density that can maximize the network capacity. Hence, the limit to SSR should be considered in the operation of future UDNs.Comment: conference submission in Oct. 201

Drone Mobile Networks: Performance Analysis Under 3D Tractable Mobility Models

Reliable wireless communication networks are a significant but challenging mission for post-disaster areas and hotspots in the era of information. However, with the maturity of unmanned aerial vehicle (UAV) technology, drone mobile networks have attracted considerable attention as a prominent solution for facilitating critical communications. This paper provides a system-level analysis for drone mobile networks on a finite three-dimensional (3D) space. Our aim is to explore the fundamental performance limits of drone mobile networks taking into account practical considerations. Most existing works on mobile drone networks use simplified mobility models (e.g., fixed height), but the movement of the drones in practice is significantly more complicated, which leads to difficulties in analyzing the performance of the drone mobile networks. Hence, to tackle this problem, we propose a stochastic geometry-based framework with a number of different mobility models including a random Brownian motion approach. The proposed framework allows to circumvent the extremely complex reality model and obtain upper and lower performance bounds for drone networks in practice. Also, we explicitly consider certain constraints, such as the small-scale fading characteristics relying on line-of-sight (LOS) and non line-of-sight (NLOS) propagation, and multi-antenna operations. The validity of the mathematical findings is verified via Monte-Carlo (MC) simulations for various network settings. In addition, the results reveal some design guidelines and important trends for the practical deployment of drone networks