Beam Based Stochastic Model of the Coverage Probability in 5G Millimeter Wave Systems

Communications using frequency bands in the millimeter-wave range can play a key role in future generations of mobile networks. By allowing large bandwidth allocations, high carrier frequencies will provide high data rates to support the ever-growing capacity demand. The prevailing challenge at high frequencies is the mitigation of large path loss and link blockage effects. Highly directional beams are expected to overcome this challenge. In this paper, we propose a stochastic model for characterizing beam coverage probability. The model takes into account both line-of-sight and first-order non-line-of-sight reflections. We model the scattering environment as a stochastic process and we derive an analytical expression of the coverage probability for any given beam. The results derived are validated numerically and compared with simulations to assess the accuracy of the model

Maximum Throughput Scheduling for Multi-connectivity in Millimeter-Wave Networks

Multi-connectivity is emerging as promising solution to provide reliable communications and seamless connectivity at the millimeter-wave frequency range. Due to the obstacles that cause frequent interruptions at such high frequency range, connectivity to multiple cells can drastically increase the network performance in terms of throughput and reliability by coordination among the network elements. In this paper, we propose an algorithm for the link scheduling optimization that maximizes the network throughput for multi-connectivity in millimeter-wave cellular networks. The considered approach exploits a centralized architecture, fast link switching, proactive context preparation and data forwarding between millimeter-wave access points and the users. The proposed algorithm is able to numerically approach the global optimum and to quantify the potential gain of multi-connectivity in millimeter-wave cellular networks

On the Benefits of Network-Level Cooperation in Millimeter-Wave Communications

Relaying techniques for millimeter-wave wireless networks represent a powerful solution for improving the transmission performance. In this work, we quantify the benefits in terms of delay and throughput for a random-access multi-user millimeter-wave wireless network, assisted by a full-duplex network cooperative relay. The relay is equipped with a queue for which we analyze the performance characteristics (e.g., arrival rate, service rate, average size, and stability condition). Moreover, we study two possible transmission schemes: fully directional and broadcast. In the former, the source nodes transmit a packet either to the relay or to the destination by using narrow beams, whereas, in the latter, the nodes transmit to both the destination and the relay in the same timeslot by using a wider beam, but with lower beamforming gain. In our analysis, we also take into account the beam alignment phase that occurs every time a transmitter node changes the destination node. We show how the beam alignment duration, as well as position and number of transmitting nodes, significantly affect the network performance. Moreover, we illustrate the optimal transmission scheme (i.e., broadcast or fully directional) for several system parameters and show that a fully directional transmission is not always beneficial, but, in some scenarios, broadcasting and relaying can improve the performance in terms of throughput and delay.Comment: arXiv admin note: text overlap with arXiv:1804.0945

Analysis and Optimization for Robust Millimeter-Wave Communications

Spectrum scarcity is a longstanding problem in mobile telecommunications networks. Specifically, accommodating the ever-growing data rate and communications demand in the extensively used spectrum between 800 MHz and 6 GHz is becoming more challenging. For this reason, in the last years, communications in the millimeterwave (mm-wave) frequency range (30-300 GHz) have attracted the interest of many researchers, who consider mm-wave communications a key enabler for upcoming generations of mobile communications, i.e., 5G and 6G. However, the signal propagation in the mm-wave frequency range is subject to more challenging conditions. High path loss and penetration loss may lead to short-range communications and frequent transmission interruptions when the signal path between the transmitter and the receiver is blocked.  In this dissertation, we analyze and optimize techniques that enhance the robustness and reliability of mm-wave communications. In the first part, we focus on approaches that allow user equipment (UE) to establish and maintain connections with multiple access points (APs) or relays, i.e., multi-connectivity (MC) and relaying techniques, to increase link failure robustness. In such scenarios, an inefficient link scheduling, i.e., over or under-provisioning of connections, can lead to either high interference and energy consumption or unsatisfied user’s quality of service (QoS) requirements. In the first paper, we propose a novel link scheduling algorithm for network throughput maximization with constrained resources and quantify the potential gain of MC. As a complementary approach, in the second paper, we solve the problem of minimizing allocated resources while satisfying users’ QoS requirements for mm-wave MC scenarios. To deal with the channel uncertainty and abrupt blockages, we propose a learning-based solution, of which the results highlight the tradeoff between reliability and allocated resource.  In the third paper, we perform throughput and delay analysis of a multi-user mm-wave wireless network assisted by a relay. We show the benefits of cooperative networking and the effects of directional communications on relay-aided mm-wave communications. These, as highlighted by the results, are characterized by a tradeoff between throughput and delay and are highly affected by the beam alignment duration and transmission strategy (directional or broadcast).  The second part of this dissertation focuses on problems related to mm-wave communications in industrial scenarios, where robots and new industrial applications require high data rates, and stringent reliability and latency requirements. In the fourth paper, we consider a multi-AP mm-wave wireless network covering an industrial plant where multiple moving robots need to be connected. We show how the joint optimization of robots’ paths and the robot-AP associations can increase mm-wave robustness by decreasing the number of handovers and avoiding coverage holes. Finally, the fifth paper considers scenarios where robot-AP communications are assisted by an intelligent reflective surface (IRS). We show that the joint optimization of beamforming and trajectory of the robot can minimize the motion energy consumption while satisfying time and communication QoS constraints. Moreover, the proposed solution exploits a radio map to prevent collisions with obstacles and to increase mm-wave communication robustness by avoiding poorly covered areas. Funding agency: European Union's Horizon 2020 researchand innovation programme under the Marie Sklodowska-Curie grantagreement No. 643002 (ACT5G).</p

QoS Aware Robot Trajectory Optimization With IRS-Assisted Millimeter-Wave Communications

This paper considers the motion energy minimization problem for a robot that uses millimeter-wave (mm-wave) communications assisted by an intelligent reflective surface (IRS). The robot must perform tasks within given deadlines, and it is subject to quality of service (QoS) constraints. This problem is crucial for fully automated factories governed by the binomial of autonomous robots and new generations of mobile communications, i.e., 5G and 6G. In this new context, robot energy efficiency and communication reliability remain fundamental problems that couple in optimizing robot trajectory and communication QoS. More precisely, to account for the mutual dependency between robot position and communication QoS, robot trajectory and beamforming at the IRS and access point all need to be optimized. We present a solution that can decouple the two problems by exploiting mm-wave channel characteristics. Then, a closed-form solution is obtained for the beamforming optimization problem, whereas the trajectory is optimized by a novel successive-convex optimization-based algorithm that can deal with abrupt line-of-sight (LOS) to non-line-of-sight (NLOS) transitions. Specifically, the algorithm uses a radio map to avoid obstacles and poorly covered areas. We prove that the algorithm can converge to a solution satisfying the Karush-Kuhn-Tucker conditions. The simulation results show a fast convergence rate of the algorithm and a dramatic reduction of the motion energy consumption with respect to methods that aim to find maximum-rate trajectories. Moreover, we show that passive IRSs represent a powerful solution to improve the radio coverage and motion energy efficiency of robots