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. 

Multi-connectivity is emerging as a promising solution to provide reliable communications and seamless connectivity for the millimeter-wave frequency range. Due to the blockage sensitivity at such high frequencies, connectivity with multiple cells can drastically increase the network performance in terms of throughput and reliability. However, an inefficient link scheduling, i.e., over and under-provisioning of connections, can lead either to high interference and energy consumption or to unsatisfied user's quality of service (QoS) requirements. In this work, we present a learning-based solution that is able to learn and then to predict the optimal link scheduling to satisfy users' QoS requirements while avoiding communication interruptions. Moreover, we compare the proposed approach with two base line methods and the genie-aided link scheduling that assumes perfect channel knowledge. We show that the learning-based solution approaches the optimum and outperforms the base line methods.

The massive exploitation of robots for Industry 4.0 needs advanced wireless solutions that replace more costly wired networks. In this regard, millimeter-waves (mm-waves) can provide high data rates, but they are characterized by a spotty coverage requiring dense radio deployments. In such scenarios, coverage holes and numerous handovers may decrease the communication throughput and reliability. In contrast to conventional multi-robot path planning (MPP), we define a type of multi-robot association-path planning (MAPP) problems aiming to jointly optimize the robots’ paths and the robots-access points (APs) associations. In MAPP, we focus on minimizing the path lengths as well as the number of handovers while sustaining the wireless connectivity of the robots. We propose an algorithm that can solve MAPP in polynomial time presenting results close to the global optimum. The proposed solution is able to guarantee the robots’ connectivity and to dramatically reduce the number of handovers in comparison to minimizing only the path lengths.

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 coordi- nation 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. 

The ever-growing data rate and comunications demand pose more challenges for the upcoming generations of mobile communications, i.e., fifth generation (5G) and beyond. To deal with these challenges, several solutions can be deployed, e.g., the use of massive amount of antennas at the transmitter and receiver nodes, the increase of cell density and the increase of the spectrum resources. More precisely, most of the current mobile networks and telecom operators mainly operate from 800 MHz to 6 GHz, however, this frequency range is probably not enough to face the growing traffic demand. 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 promising solution to deal with the longstanding problem of spectrum scarcity. However, in comparison to lower frequency communications, the signal propagation in the mm-wave frequency range is subject to more challenging conditions. The latter lead to frequent transmission interruptions when the signal path between the transmitter and the receiver, usually line-of-sight (LOS), is blocked. In this thesis, we present three papers that study several aspects of the mm-wave wireless networks and potential solutions to overcome the blockage issue and increase the reliability for the mm-wave communications. The first work studies the contribution of the reected beams for the communications in non line-of-sight (NLOS). This work provides a stochastic model that is able to evaluate the coverage probability not only considering the direct beam, but also including first order reections, which may contribute to the coverage probability in NLOS.

The second paper analyzes a possible solution to overcome the blockage issue that is the multi-connectivity (MC). This technique allows the user equipments (UEs) to establish and maintain connections with multiple cells/access points at the same time and it increases the number of possible available links per UE. In this scenario, we propose a novel link scheduling algorithm for network throughput maximization, and quantify the potential gain of MC for mm-wave cellular networks. The proposed algorithm is able to numerically approach the global optimum and overtakes the single connectivity schema in terms of network throughput.

Finally, in the third paper, we study a complementary approach to the multi-connectivity schema, i.e., the relying technique. In this work, we perform a throughput analysis of a relay-aided mm-wave wireless network. We consider two possible transmission strategies, by which the source nodes transmit either a packet to both the destination and the relay in the same timeslot (broadcast) or to only one of these two (destination or relay) by using directional transmissions. We analyze and show the optimal transmission strategy with respect to several system parameters, e.g., positions and number of the nodes, by taking into account the different beamforming gains and interference levels of the possible transmission strategies.