Characterization of aggregate interference in arbitrarily-shaped underlay cognitive networks

This paper characterizes the aggregate interference at the primary user (PU) due to M secondary users (SUs) in an underlay cognitive network, where appropriate SU activity protocols are employed in order to limit the interference generated by the SUs. Different from prior works, we assume that the PU can be located anywhere inside an arbitrarily-shaped convex network region. Using the moment generating function (MGF) of the interference from a random SU, we derive general expressions for the n-th moment and the n-th cumulant of the aggregate interference for guard zone and multiple-threshold SU activity protocols. Using the cumulants, we study the convergence of the distribution of the aggregate interference to a Gaussian distribution. In addition, we compare the well-known closed-form distributions in the literature to approximate the complementary cumulative distribution function (CCDF) of the aggregate interference. Our results show that care must be undertaken in approximating the aggregate interference as a Gaussian distribution, even for a large number of SUs, since the convergence is not monotonie in general. In addition, the shifted lognormal distribution provides the overall best CCDF approximation, especially in the distribution tail region, for arbitrarily-shaped network regions

Integrating Drones and Wireless Power Transfer into Beyond 5G Networks

As fifth generation (5G) standards have been established and 5G commercial products are just around the corner, both academia and industry have started to look at requirements for beyond 5G networks. Network flexibility and long battery life are among the key requirements for beyond 5G wireless communication systems. These critical requirements, which have not been sufficiently addressed in the previous generations, are the focus of this thesis. The first half of this thesis explores two important use cases of drones to provide flexible communication networks. First, the performance of a cellular network with underlay drone cell for temporary events inside a stadium is studied. Using stochastic geometry, a general analytical framework is proposed to analyze the uplink and the downlink coverage probabilities for both the aerial and the terrestrial systems. Our results show that for urban environment and dense urban environment, the drone is best deployed at a low height (e.g., 200 m or lower), regardless of the distance between the center of the stadium and the terrestrial base station. However, for suburban environment and high-rise urban environment, the best drone altitude varies. Second, the performance of emergency information dissemination in public safety scenarios using drone is studied. A drone-assisted multihop multicast device-to-device (D2D) network is considered, where an emergency alert message broadcasted by a drone at the first time slot is multicasted by the D2D users that have successfully received the message through multihop. The impact of different system parameters on the link and the network performance is investigated. Our results demonstrate that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. Under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m. The second half of this thesis investigates wireless power transfer networks. Specifically, the use of power beacons in a millimeter wave wireless ad hoc network is considered, where transmitters adopt the harvest-then-transmit protocol. First, the characteristic of the aggregate received power from power beacons is analyzed and the lognormal distribution is found to provide the best complementary cumulative distribution function approximation compared to other distributions considered in the literature. Then, a tractable model with discrete transmit power for each transmitter is proposed to compute the channel coverage probability and the total coverage probability. Our results show that our model provides a good accuracy and reveal the impact of different system parameters on the total coverage probability. Our results also illustrate that under practical setups, for power beacon transmit power of 50 dBm and transmitters with maximum transmit power between 20 - 40 dBm, which are safe for human exposure, the total coverage probability is around 90%. Thus, it is feasible and safe to power transmitters in a millimeter wave ad hoc network using power beacons

Stochastic Geometry for Modeling, Analysis and Design of Future Wireless Networks

This thesis focuses on the modeling, analysis and design of future wireless networks with smart devices, i.e., devices with intelligence and ability to communicate with one another with/without the control of base stations (BSs). Using stochastic geometry, we develop realistic yet tractable frameworks to model and analyze the performance of such networks, while incorporating the intelligence features of smart devices. In the first half of the thesis, we develop stochastic geometry tools to study arbitrarily shaped network regions. Current techniques in the literature assume the network regions to be infinite, while practical network regions tend to be arbitrary. Two well-known networks are considered, where devices have the ability to: (i) communicate with others without the control of BSs (i.e., ad-hoc networks), and (ii) opportunistically access spectrum (i.e., cognitive networks). First, we propose a general algorithm to derive the distribution of the distance between the reference node and a random node inside an arbitrarily shaped ad-hoc network region, which helps to compute the outage probability. We then study the impact of boundary effects and show that the outage probability in infinite regions may not be a meaningful bound for arbitrarily shaped regions. By extending the developed techniques, we further analyze the performance of underlay cognitive networks, where different secondary users (SUs) activity protocols are employed to limit the interference at a primary user. Leveraging the information exchange among SUs, we propose a cooperation-based protocol. We show that, in the short-term sensing scenario, this protocol improves the network's performance compared to the existing threshold-based protocol. In the second half of the thesis, we study two recently emerged networks, where devices have the ability to: (i) communicate directly with nearby devices under the control of BSs (i.e., device-to-device (D2D) communication), and (ii) harvest radio frequency energy (i.e., energy harvesting networks). We first analyze the intra-cell interference in a finite cellular region underlaid with D2D communication, by incorporating a mode selection scheme to reduce the interference. We derive the outage probability at the BS and a D2D receiver, and propose a spectrum reuse ratio metric to assess the overall D2D communication performance. We demonstrate that, without impairing the performance at the BS, if the path-loss exponent on cellular link is slightly lower than that on D2D link, the spectrum reuse ratio can have negligible decrease while the average number of successful D2D transmissions increases with the increasing D2D node density. This indicates that an increasing level of D2D communication is beneficial in future networks. Then we study an ad-hoc network with simultaneous wireless information and power transfer in an infinite region, where transmitters are wirelessly charged by power beacons. We formulate the total outage probability in terms of the power and channel outage probabilities. The former incorporates a power activation threshold at transmitters, which is a key practical factor that has been largely ignored in previous work. We show that, although increasing power beacon's density or transmit power is not always beneficial for channel outage probability, it improves the overall network performance