Empirical Analysis and Network-wide Optimization for Next Generation Wireless Communications

The 5th Generation (5G) wireless networks have already been deployed worldwide, providing a multi-fold Quality of Service (QoS) improvement, compared to 4G, by adopting new techniques, such as Millimeter Wave (mmWave) frequency bands, advanced spectrum management techniques, and the integration of licensed and unlicensed bands. The next-generation networks will be empowered by new technologies such as Reconfigurable Intelligent Surface (RIS), Unmanned Aerial Vehicle (UAV) communications, and Cell-free (CF) massive Multiple-Input, Multiple-Output (mMIMO) technologies to further improve over existing technologies. In this thesis, we investigate the paradigm of the future generation of wireless systems, their requirements and specifications, emerging applications, and their enabling technologies. We analyze the usage of mmWave frequencies in indoor and outdoor environments. We discuss the challenges related to the scheduling of IEEE 802.11ad/ay, which provides multi-gigabit service over mmWave links, in realistic scenarios. We also analyze the performance of outdoor mmWave transmissions by conducting a measurement campaign in an early deployed 5G mmWave cell. We study various environmental impacts such as the body and foliage blockage, rain, and over-water transmission on mmWave links. Comparing our results with the simulations, we observe a performance gap between current operational networks and the reference system modeled in simulations. The proposed tech- nologies for future wireless systems, i.e., RIS and UAVs, still need to be optimized before being functional. Hence, we propose some network-wide optimization schemes to increase the performance of such systems. We propose an energy-efficient design for joint RIS and UAV transmissions to provide sustainable communications in dense urban environments. We define a joint UAV trajectory and RIS phase optimization problem that minimizes the transmission power of UAV and Base Station (BS) while guaranteeing a certain level of data rate for users. Finally, we discuss CF mMIMO networks and propose pilot reuse strategies to optimize the system’s rate. We formulate the pilot assignment problem in CF mMIMO as a diverse clustering problem and propose an iterative optima search scheme to solve it.