Coverage Analysis and Cooperative Hybrid Precoding for 5G Cellular Networks

5G innovations have been made in both the network deployment and the transceiver architectures in order to increase coverage, energy- and spectrum-efficiency. Future base stations (BSs) are expected to be densely deployed in places such as walls and lamp posts and cover a smaller area compared to current macro BS systems. Using large spectrum at millimeter-wave (mmWave) frequency bands and highly directional beamforming with large antenna arrays, 5G will bring gigabit-per-second data rate and low-latency communications and enable many novel services such as high-speed mmWave wireless interconnections between devices, vehicular communications, etc.. Moreover, mmWave communication systems will be based on novel hybrid beamforming architectures which have reduced hardware power consumption and cost. Thus, for better understanding of 5G performance and limitations, one of the main goals in this thesis is to analyze new models that give tractable performance metrics for dense small BS networks. Another goal in this thesis is to study mmWave hybrid beamforming schemes which enable joint transmissions in multi-cell multi-user systems. In the thesis, we show the advantages of small cells in increasing the coverage probability and reducing the path loss and shadowing, and we show the value of cooperation in terms of power consumption and outage. In [Paper A] we derive analytical expressions for the successful reception probability of the equal gain combining receiver in a network where interfering transmitters are distributed according to a Poisson point process and interfering signals are spatially correlated. The results show that the spatial correlation reduces the successful reception probability and the effect of the spatial correlation increases with the number of antennas.\ua0[Paper B] follows to study the performance of a partial zero forcing receiver. The results are simulated in an environment with blockages and are analyzed under both Rayleigh and Rician channels. The coverage probability is shown to be maximized when using a subset of antennas\u27 degree-of-freedom for useful signal enhancement and using the remaining degrees of freedom for canceling the interference from strongest interferers. Finally, in [Paper C], we propose a hybrid beamforming scheme which minimizes the total power consumption of a multi-cell multi-user network, subject to per-user quality-of-service constraints. The proposed scheme is based on decoupling the analog precoding and digital precoding. The analog precoders are only dependent on the local channel state information at each BS. Then, the digital precoders are obtained by solving a relaxed convex optimization for given analog precoders. Simulation results show that the proposed algorithm leads to almost the same RF transmit power as that of fully digital precoding, while saving considerable hardware power due to the reduced number of RF chains and digital-to-analog converters

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

On the Fundamentals of Stochastic Spatial Modeling and Analysis of Wireless Networks and its Impact to Channel Losses

With the rapid evolution of wireless networking, it becomes vital to ensure transmission reliability, enhanced connectivity, and efficient resource utilization. One possible pathway for gaining insight into these critical requirements would be to explore the spatial geometry of the network. However, tractably characterizing the actual position of nodes for large wireless networks (LWNs) is technically unfeasible. Thus, stochastical spatial modeling is commonly considered for emulating the random pattern of mobile users. As a result, the concept of random geometry is gaining attention in the field of cellular systems in order to analytically extract hidden features and properties useful for assessing the performance of networks. Meanwhile, the large-scale fading between interacting nodes is the most fundamental element in radio communications, responsible for weakening the propagation, and thus worsening the service quality. Given the importance of channel losses in general, and the inevitability of random networks in real-life situations, it was then natural to merge these two paradigms together in order to obtain an improved stochastical model for the large-scale fading. Therefore, in exact closed-form notation, we generically derived the large-scale fading distributions between a reference base-station and an arbitrary node for uni-cellular (UCN), multi-cellular (MCN), and Gaussian random network models. In fact, we for the first time provided explicit formulations that considered at once: the lattice profile, the users’ random geometry, the spatial intensity, the effect of the far-field phenomenon, the path-loss behavior, and the stochastic impact of channel scatters. Overall, the results can be useful for analyzing and designing LWNs through the evaluation of performance indicators. Moreover, we conceptualized a straightforward and flexible approach for random spatial inhomogeneity by proposing the area-specific deployment (ASD) principle, which takes into account the clustering tendency of users. In fact, the ASD method has the advantage of achieving a more realistic deployment based on limited planning inputs, while still preserving the stochastic character of users’ position. We then applied this inhomogeneous technique to different circumstances, and thus developed three spatial-level network simulator algorithms for: controlled/uncontrolled UCN, and MCN deployments