On Modeling Heterogeneous Wireless Networks Using Non-Poisson Point Processes

Future wireless networks are required to support 1000 times higher data rate, than the current LTE standard. In order to meet the ever increasing demand, it is inevitable that, future wireless networks will have to develop seamless interconnection between multiple technologies. A manifestation of this idea is the collaboration among different types of network tiers such as macro and small cells, leading to the so-called heterogeneous networks (HetNets). Researchers have used stochastic geometry to analyze such networks and understand their real potential. Unsurprisingly, it has been revealed that interference has a detrimental effect on performance, especially if not modeled properly. Interference can be correlated in space and/or time, which has been overlooked in the past. For instance, it is normally assumed that the nodes are located completely independent of each other and follow a homogeneous Poisson point process (PPP), which is not necessarily true in real networks since the node locations are spatially dependent. In addition, the interference correlation created by correlated stochastic processes has mostly been ignored. To this end, we take a different approach in modeling the interference where we use non-PPP, as well as we study the impact of spatial and temporal correlation on the performance of HetNets. To illustrate the impact of correlation on performance, we consider three case studies from real-life scenarios. Specifically, we use massive multiple-input multiple-output (MIMO) to understand the impact of spatial correlation; we use the random medium access protocol to examine the temporal correlation; and we use cooperative relay networks to illustrate the spatial-temporal correlation. We present several numerical examples through which we demonstrate the impact of various correlation types on the performance of HetNets.Comment: Submitted to IEEE Communications Magazin

On the Outage Probability of the Full-Duplex Interference-Limited Relay Channel

In this paper, we study the performance, in terms of the asymptotic error probability, of a user which communicates with a destination with the aid of a full-duplex in-band relay. We consider that the network is interference-limited, and interfering users are distributed as a Poisson point process. In this case, the asymptotic error probability is upper bounded by the outage probability (OP). We investigate the outage behavior for well-known cooperative schemes, namely, decode-and-forward (DF) and compress-and-forward (CF) considering fading and path loss. For DF we determine the exact OP and develop upper bounds which are tight in typical operating conditions. Also, we find the correlation coefficient between source and relay signals which minimizes the OP when the density of interferers is small. For CF, the achievable rates are determined by the spatial correlation of the interferences, and a straightforward analysis isn't possible. To handle this issue, we show the rate with correlated noises is at most one bit worse than with uncorrelated noises, and thus find an upper bound on the performance of CF. These results are useful to evaluate the performance and to optimize relaying schemes in the context of full-duplex wireless networks.Comment: 30 pages, 4 figures. Final version. To appear in IEEE JSAC Special Issue on Full-duplex Wireless Communications and Networks, 201

Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial

This paper presents a tutorial on stochastic geometry (SG)-based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. This paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of this paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. This paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, this paper highlights the state-of-the-art research and points out future research directions