Integrated cellular and device-to-device networks

textDevice-to-device (D2D) networking enables direct discovery and communication between cellular subscribers that are in proximity, thus bypassing the base stations (BSs). In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled broadband communication technology is also required by public safety networks that must function when cellular networks are not available. Integrating D2D into cellular networks, however, poses many challenges and risks to the long-standing cellular architecture, which is centered around the BSs. This dissertation identifies outstanding technical challenges in D2D-enabled cellular networks and addresses them with novel models and fundamental analysis. First, this dissertation develops a baseline hybrid network model consisting of both ad hoc nodes and cellular infrastructure. This model uses Poisson point processes to model the random and unpredictable locations of mobile users. It also captures key features of multicast D2D including multicast receiver heterogeneity and retransmissions while being tractable for analytical purpose. Several important multicast D2D metrics including coverage probability, mean number of covered receivers per multicast session, and multicast throughput are analytically characterized under the proposed model. Second, D2D mode selection which means that a potential D2D pair can switch between direct and cellular modes is incorporated into the hybrid network model. The extended model is applied to study spectrum sharing between cellular and D2D communications. Two spectrum sharing models, overlay and underlay, are investigated under a unified analytical framework. Analytical rate expressions are derived and applied to optimize the design of spectrum sharing. It is found that, from an overall mean-rate perspective, both overlay and underlay bring performance improvements (vs. pure cellular). Third, the single-antenna hybrid network model is extended to multi-antenna transmission to study the interplay between massive MIMO (multi-input multiple-output) and underlaid D2D networking. The spectral efficiency of such multi-antenna hybrid networks is investigated under both perfect and imperfect channel state information (CSI) assumptions. Compared to the case without D2D, there is a loss in cellular spectral efficiency due to D2D underlay. With perfect CSI, the loss can be completely overcome if the number of canceled D2D interfering signals is scaled appropriately. With imperfect CSI, in addition to pilot contamination, a new asymptotic underlay contamination effect arises. Finally, motivated by the fact that transmissions in D2D discovery are usually not or imperfectly synchronized, this dissertation studies the effect of asynchronous multicarrier transmission and proposes a tractable signal-to-interference-plus-noise ratio (SINR) model. The proposed model is used to analytically characterize system-level performance of asynchronous wireless networks. The loss from lack of synchronization is quantified, and several solutions are proposed and compared to mitigate the loss.Electrical and Computer Engineerin

Analysis of millimeter wave and massive MIMO cellular networks

Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional cellular systems do not directly apply to analyze mmWave or massive MIMO networks, as (i) mmWave cellular networks differ in the different propagation conditions and hardware constraints; and (ii) with a order of magnitude more antennas than conventional multi-user MIMO systems, massive MIMO systems will be operated in time-division duplex (TDD) mode, which renders pilot contamination a primary limiting factor. In this dissertation, I develop stochastic geometry frameworks to analyze the system-level performance of mmWave, sub-6 GHz massive MIMO, and mmWave massive MIMO cellular networks. The proposed models capture the key features of each technique, and allow for tractable signal-to-interference-plus-noise ratio (SINR) and rate analyses. In the first contribution, I develop an mmWave cellular network model that incorporates the blockage effect and directional beamforming, and analyze the SINR and rate distributions as functions of the base station density, blockage parameters, and antenna geometry. The analytical results demonstrate that with a sufficiently dense base station deployment, mmWave cellular networks are capable to achieve comparable SINR coverage and much higher rates than conventional networks. In my second contribution, I analyze the uplink SINR and rate in sub-6 GHz massive MIMO networks with the incorporation of pilot contamination and fractional power control. Based on the analysis, I show scaling laws between the number of antennas and scheduled users per cell that maintain the uplink signal-to-interference ratio (SIR) distributions are different for maximum ratio combining (MRC) and zero-forcing (ZF) receivers. In my third contribution, I extend the sub-6 GHz massive MIMO model to mmWave frequencies, by incorporating key mmWave features. I leverage the proposed model to investigate the asymptotic SINR performance, when the number of antennas goes to infinity. Numerical results show that mmWave massive MIMO outperforms its sub-6 GHz counterpart in cell throughput with a dense base station deployment, while the reverse can be true with a low base station density.Electrical and Computer Engineerin

Short-Packet Communications: Transmission Strategies and Power Control Policies Design

Ultra-reliable and low-latency communications (URLLC) has been envisaged as the enabling paradigm to support real-time communications with stringent requirements on latency and reliability. The realization of URLLC will bring life-changing applications, e.g., smart manufacturing for Industrial 4.0, autonomous networked vehicles, and remote surgery, to human society. Notably, these applications typically require a target decoding error probability to be less than $10^{-7}$ within a latency being lower than 1 ms. Such strictly low latency imposes an unprecedented restriction on the size of packets. As such, short-packet communications (SPC) has been proposed as the fundamental method to reduce the latency for URLLC. This thesis aims to gain a comprehensive understanding of SPC for URLLC. Specifically, this thesis investigates and addresses the following issues: 1) how to design SPC with limited channel estimation overhead in SPC (Chapters 2 and 3), 2) how to improve the design of SPC to reduce the communication latency for URLLC (Chapter 4), and 3) how to design secure SPC for URLLC under statistical quality-of-service (QoS) constraints (Chapter 5). The contributions made in this thesis are summarized as follows: First, we investigate two different channel training strategies for SPC in Chapter 2. We study the requirement on channel reciprocity to activate uplink channel training, instead of downlink channel training, to achieve a higher data rate for the downlink transmission from a multi-antenna base station to a single-antenna user. We show the necessity and benefits of activating uplink channel training for SPC with multiple transmit antennas. Then, we further study the optimal SPC strategy in a multiple-input single-output system in Chapter 3. To maximize the average achievable data rate, we determine the optimal allocation of the finite resource (e.g., the total transmit power and a finite number of symbol periods) for downlink training, uplink feedback, and data transmission. Second, to reduce communication latency, in Chapter 4, we propose to use channel inversion power control (CIPC) with channel reciprocity to eliminate the overhead of channel state information (CSI) feedback, as well as achieve one-way URLLC where only the transmission in one direction requires ultra reliability and low latency. Based on channel reciprocity, the proposed CIPC schemes guarantee that the power of the received signal used to decode the information is a constant value \emph{Q}, by varying the transmit signal and power, which relaxes the assumption of knowing CSI at the user. We derive new analytical expressions for the packet loss probability of the proposed CIPC schemes, based on which we determine a closed interval and a convex set for optimizing \emph{Q} in CIPC with imperfect and perfect channel reciprocities, respectively. Finally, we study how to realize secure SPC subject to a statistical QoS requirement and an average power constraint in Chapter 5. We compare the secure transmission rates of short packets in different scenarios (i.e., with/without eavesdropper's instantaneous CSI and with/without channel estimation errors). To find the optimal power control policy that maximizes the effective secrecy throughout under QoS and power constraints, we apply an unsupervised deep learning method with low complexity to address constrained functional optimization problems, which do not have a closed-form solution in general. To provide more insights and demonstrate the effectiveness of unsupervised deep learning, we derive the closed-form expression for the optimal policy in a special case. This thesis advances our understanding of the fundamental performance of SPC for URLLC. It also provides guidelines to assist URLLC designers to solve important problems on how to fully explore the advantages of SPC in practical wireless URLLC systems

Mathematical Modelling and Analysis of Spatially Correlated Heterogeneous and Vehicular Networks - A Stochastic Geometry Approach

Heterogeneous Cellular Networks (HCNs) and vehicular communications are two key ingredients of future 5G communication networks, which aim at providing high data rates on the one former case and high reliability on the latter one. Nevertheless, in these two scenarios, interference is the main limiting factor, which makes achieving the required performance, i.e., data rate or reliability, a challenging task. Hence, in order to cope with such issue, concepts like uplink/downlink (UL/DL) decoupling, Interference-Aware (IA) strategies or cooperative communications with Cloud Radio Access Networks (CRANs) has been introduced for new releases of 4G and future 5G networks. Additionally, for the sake of increasing the data rates, new multiple access schemes like Non-Orthogonal Multiple Access (NOMA) has been proposed for 5G networks. All these techniques and concepts require accurate and tractable mathematical modelling for performance analysis. This analysis allows us to obtain theoretical insights about key performance indicators leading to a deep understanding about the considered techniques. Due to the random and irregular nature that exhibits HCNs, as well as vehicular networks, stochastic geometry has appeared recently as a promising tool for system-level modelling and analysis. Nevertheless, some features of HCNs and vehicular networks, like power control, scheduling or frequency planning, impose spatial correlations over the underlying point process that complicates significantly the mathematical analysis. In this thesis, it has been used stochastic geometry and point process theories to investigate the performance of these aforementioned techniques. Firstly, it is derived a mathematical framework for the analysis of an Interference-Aware Fractional Power Control (IAFPC) for interference mitigation in the UL of HCNs. The analysis reveals that IAFPC outperforms the classical FPC in terms of Spectral Efficiency (SE), average transmitted power, and mean and variance of the interference. Then, it is investigated the performance of a scheduling algorithm where the Mobile Terminals (MTs) may be turned off if they cause a level of interference greater than a given threshold. Secondly, a multi-user UL model to assess the coverage probability of different MTs in each cell is proposed. Then, the coverage probability of cellular systems under Hoyt fading (Nakagami-q) is studied. This fading model, allows us to consider more severe fading conditions than Rayleigh, which is normally the considered fading model for the sake of tractability. Thirdly, a novel NOMA-based scheme for CRANs is proposed, modelled and analyzed. In this scheme, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinated beamforming. Finally, the performance of a decentralized Medium Access Control (MAC) algorithm for vehicular communications is investigated. With this strategy, the cellular network provides frequency and time synchronization for direct Vehicle to Vehicle (V2V) communication, which is based on its geographical information. The analysis demonstrates that there exists an operation regime where the performance is noise-limited. Then, the optimal transmit power that maximizes the Energy Efficiency (EE) of the system subject to a minimum capture probability constraint is derived

Scalable coexistence of eMBB, URLLC and mMTC enabled by non-orthogonal multiple access and network slicing

Abstract. The 5G systems feature three use cases: enhanced Mobile BroadBand (eMBB), massive Machine-Type Communications (mMTC) and Ultra-Reliable and Low-Latency Communications (URLLC). The diverse requirements of the corresponding services in terms of achievable data-rate, number of connected devices, latency and reliability can lead to sub-optimal use of the 5G resources, thus network slicing emerges as a promising alternative that customizes slices of the network specifically designed to meet specific requirements. By employing network slicing, the radio resources can be shared via orthogonal and non-orthogonal schemes. Motivated by the Industrial Internet of Things (IIoT) paradigm where a large number of sensors may require connectivity with stringent requirements of latency and reliability, we propose and evaluate the joint use of network slicing and Non-Orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC) in two different uplink scenarios. In the first scenario, eMBB coexists with URLLC in the same Radio Access Network (RAN) and, in order to improve the number of concurrent URLLC connections to the same base station (BS), they transmit simultaneously and across multiple frequency channels. In the second scenario, eMBB coexists with mMTC and, to provide connectivity to a massive number of devices, the BS has multiple receive antennas. In both cases, we set the reliability requirements for the services and compare the performance of both orthogonal and non-orthogonal network slicing schemes in terms of maximum achievable data rates and connected users. Our results show that, even with overlapping transmissions from multiple devices, network slicing, NOMA and SIC techniques allow us simultaneously satisfy all the heterogeneous requirements of the 5G services

Large System Analysis of Power Normalization Techniques in Massive MIMO

Linear precoding has been widely studied in the context of Massive multiple-input-multiple-output (MIMO) together with two common power normalization techniques, namely, matrix normalization (MN) and vector normalization (VN). Despite this, their effect on the performance of Massive MIMO systems has not been thoroughly studied yet. The aim of this paper is to fulfill this gap by using large system analysis. Considering a system model that accounts for channel estimation, pilot contamination, arbitrary pathloss, and per-user channel correlation, we compute tight approximations for the signal-to-interference-plus-noise ratio and the rate of each user equipment in the system while employing maximum ratio transmission (MRT), zero forcing (ZF), and regularized ZF precoding under both MN and VN techniques. Such approximations are used to analytically reveal how the choice of power normalization affects the performance of MRT and ZF under uncorrelated fading channels. It turns out that ZF with VN resembles a sum rate maximizer while it provides a notion of fairness under MN. Numerical results are used to validate the accuracy of the asymptotic analysis and to show that in Massive MIMO, non-coherent interference and noise, rather than pilot contamination, are often the major limiting factors of the considered precoding schemes.Comment: 12 pages, 3 figures, Accepted for publication in the IEEE Transactions on Vehicular Technolog