Tight Lower Bounds on the Contact Distance Distribution in Poisson Hole Process

In this letter, we derive new lower bounds on the cumulative distribution function (CDF) of the contact distance in the Poisson Hole Process (PHP) for two cases: (i) reference point is selected uniformly at random from $\mathbb{R}^2$ independently of the PHP, and (ii) reference point is located at the center of a hole selected uniformly at random from the PHP. While one can derive upper bounds on the CDF of contact distance by simply ignoring the effect of holes, deriving lower bounds is known to be relatively more challenging. As a part of our proof, we introduce a tractable way of bounding the effect of all the holes in a PHP, which can be used to study other properties of a PHP as well.Comment: To appear in IEEE Wireless Communications Letter

Coexistence of RF-powered IoT and a Primary Wireless Network with Secrecy Guard Zones

This paper studies the secrecy performance of a wireless network (primary network) overlaid with an ambient RF energy harvesting IoT network (secondary network). The nodes in the secondary network are assumed to be solely powered by ambient RF energy harvested from the transmissions of the primary network. We assume that the secondary nodes can eavesdrop on the primary transmissions due to which the primary network uses secrecy guard zones. The primary transmitter goes silent if any secondary receiver is detected within its guard zone. Using tools from stochastic geometry, we derive the probability of successful connection of the primary network as well as the probability of secure communication. Two conditions must be jointly satisfied in order to ensure successful connection: (i) the SINR at the primary receiver is above a predefined threshold, and (ii) the primary transmitter is not silent. In order to ensure secure communication, the SINR value at each of the secondary nodes should be less than a predefined threshold. Clearly, when more secondary nodes are deployed, more primary transmitters will remain silent for a given guard zone radius, thus impacting the amount of energy harvested by the secondary network. Our results concretely show the existence of an optimal deployment density for the secondary network that maximizes the density of nodes that are able to harvest sufficient amount of energy. Furthermore, we show the dependence of this optimal deployment density on the guard zone radius of the primary network. In addition, we show that the optimal guard zone radius selected by the primary network is a function of the deployment density of the secondary network. This interesting coupling between the two networks is studied using tools from game theory. Overall, this work is one of the few concrete works that symbiotically merge tools from stochastic geometry and game theory

A Stochastic Geometry approach towards Green Communications in 5G

In this dissertation, we investigate two main research directions towards net- work efficiency and green communications in heterogeneous cellular networks (HetNets) as a promising network structure for the fifth generation of mobile systems. In order to analyze the networks, we use a powerful mathematical tool, named stochastic geometry. In our research, first we study the performance of MIMO technology in single-tier and two-tier HetNets. In this work, we apply a more realistic network model in which the correlation between tiers is taken into account. Comparing the obtained results with the commonly used model shows performance enhancement and greater efficiencies in cellular networks. As the second part of our research, we apply two Cell Zooming (CZ) techniques to HetNets. With focus on green communications, we present a K−tier HetNet in which BSs are only powered by energy har- vesting. Despite the uncertain nature of energy arrivals, combining two CZ techniques, namely telescopic and ON/OFF scenarios, enables us to achieve higher network performance in terms of the coverage and blocking probabilities while reducing the total power consumption and increasing the energy and spectral efficiencies

Network-Level Integrated Sensing and Communication: Interference Management and BS Coordination Using Stochastic Geometry

In this work, we study integrated sensing and communication (ISAC) networks with the aim of effectively balancing sensing and communication (S&C) performance at the network level. Focusing on monostatic sensing, the tool of stochastic geometry is exploited to capture the S&C performance, which facilitates us to illuminate key cooperative dependencies in the ISAC network and optimize key network-level parameters. Based on the derived tractable expression of area spectral efficiency (ASE), we formulate the optimization problem to maximize the network performance from the view point of two joint S&C metrics. Towards this end, we further jointly optimize the cooperative BS cluster sizes for S&C and the serving/probing numbers of users/targets to achieve a flexible tradeoff between S&C at the network level. It is verified that interference nulling can effectively improve the average data rate and radar information rate. Surprisingly, the optimal communication tradeoff for the case of the ASE maximization tends to employ all spacial resources towards multiplexing and diversity gain, without interference nulling. By contrast, for the sensing objectives, resource allocation tends to eliminate certain interference especially when the antenna resources are sufficient, because the inter-cell interference becomes a more dominant factor affecting sensing performance. Furthermore, we prove that the ratio of the optimal number of users and the number of transmit antennas is a constant value when the communication performance is optimal. Simulation results demonstrate that the proposed cooperative ISAC scheme achieves a substantial gain in S&C performance at the network level.Comment: 13 pages, 12 figures. This work has been submitted to the IEEE for possible publicatio