Delay Performance of MISO Wireless Communications

Ultra-reliable, low latency communications (URLLC) are currently attracting significant attention due to the emergence of mission-critical applications and device-centric communication. URLLC will entail a fundamental paradigm shift from throughput-oriented system design towards holistic designs for guaranteed and reliable end-to-end latency. A deep understanding of the delay performance of wireless networks is essential for efficient URLLC systems. In this paper, we investigate the network layer performance of multiple-input, single-output (MISO) systems under statistical delay constraints. We provide closed-form expressions for MISO diversity-oriented service process and derive probabilistic delay bounds using tools from stochastic network calculus. In particular, we analyze transmit beamforming with perfect and imperfect channel knowledge and compare it with orthogonal space-time codes and antenna selection. The effect of transmit power, number of antennas, and finite blocklength channel coding on the delay distribution is also investigated. Our higher layer performance results reveal key insights of MISO channels and provide useful guidelines for the design of ultra-reliable communication systems that can guarantee the stringent URLLC latency requirements.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Delay QoS Provisioning and Optimal Resource Allocation for Wireless Networks

Recent years have witnessed a significant growth in wireless communication and networking due to the exponential growth in mobile applications and smart devices, fueling unprecedented increase in both mobile data traffic and energy demand. Among such data traffic, real-time data transmissions in wireless systems require certain quality of service (QoS) constraints e.g., in terms of delay, buffer overflow or packet drop/loss probabilities, so that acceptable performance levels can be guaranteed for the end-users, especially in delay sensitive scenarios, such as live video transmission, interactive video (e.g., teleconferencing), and mobile online gaming. With this motivation, statistical queuing constraints are considered in this thesis, imposed as limitations on the decay rate of buffer overflow probabilities. In particular, the throughput and energy efficiency of different types of wireless network models are analyzed under QoS constraints, and optimal resource allocation algorithms are proposed to maximize the throughput or minimize the delay. In the first part of the thesis, the throughput and energy efficiency analysis for hybrid automatic repeat request (HARQ) protocols are conducted under QoS constraints. Approximations are employed for small QoS exponent values in order to obtain closed-form expressions for the throughput and energy efficiency metrics. Also, the impact of random arrivals, deadline constraints, outage probability and QoS constraints are studied. For the same system setting, the throughput of HARQ system is also analyzed using a recurrence approach, which provides more accurate results for any value of the QoS exponent. Similarly, random arrival models and deadline constraints are considered, and these results are further extended to the finite-blocklength coding regime. Next, cooperative relay networks are considered under QoS constraints. Specifically, the throughput performance in the two-hop relay channel, two-way relay channel, and multi-source multi-destination relay networks is analyzed. Finite-blocklength codes are considered for the two-hop relay channel, and optimization over the error probabilities is investigated. For the multi-source multi-destination relay network model, the throughput for both cases of with and without CSI at the transmitter sides is studied. When there is perfect CSI at the transmitter, transmission rates can be varied according to instantaneous channel conditions. When CSI is not available at the transmitter side, transmissions are performed at fixed rates, and decoding failures lead to retransmission requests via an ARQ protocol. Following the analysis of cooperative networks, the performance of both half-duplex and full-duplex operations is studied for the two-way multiple input multiple output (MIMO) system under QoS constraints. In full-duplex mode, the self-interference inflicted on the reception of a user due to simultaneous transmissions from the same user is taken into account. In this setting, the system throughput is formulated by considering the sum of the effective capacities of the users in both half-duplex and full-duplex modes. The low signal to noise ratio (SNR) regime is considered and the optimal transmission/power-allocation strategies are characterized by identifying the optimal input covariance matrices. Next, mode selection and resource allocation for device-to-device (D2D) cellular networks are studied. As the starting point, ransmission mode selection and resource allocation are analyzed for a time-division multiplexed (TDM) cellular network with one cellular user, one base station, and a pair of D2D users under rate and QoS constraints. For a more complicated setting with multiple cellular and D2D users, two joint mode selection and resource allocation algorithms are proposed. In the first algorithm, the channel allocation problem is formulated as a maximum-weight matching problem, which can be solved by employing the Hungarian algorithm. In the second algorithm, the problem is divided into three subproblems, namely user partition, power allocation and channel assignment, and a novel three-step method is proposed by combining the algorithms designed for the three subproblems. In the final part of the thesis, resource allocation algorithms are investigated for content delivery over wireless networks. Three different systems are considered. Initially, a caching algorithm is designed, which minimizes the average delay of a single-cell network. The proposed algorithm is applicable in settings with very general popularity models, with no assumptions on how file popularity varies among different users, and this algorithm is further extended to a more general setting, in which the system parameters and the distributions of channel fading change over time. Next, for D2D cellular networks operating under deadline constraints, a scheduling algorithm is designed, which manages mode selection, channel allocation and power maximization with acceptable complexity. This proposed scheduling algorithm is designed based on the convex delay cost method for a D2D cellular network with deadline constraints in an OFDMA setting. Power optimization algorithms are proposed for all possible modes, based on our utility definition. Finally, a two-step intercell interference (ICI)-aware scheduling algorithm is proposed for cloud radio access networks (C-RANs), which performs user grouping and resource allocation with the goal of minimizing delay violation probability. A novel user grouping algorithm is developed for the user grouping step, which controls the interference among the users in the same group, and the channel assignment problem is formulated as a maximum-weight matching problem in the second step, which can be solved using standard algorithms in graph theory

Reliable Transmission of Short Packets through Queues and Noisy Channels under Latency and Peak-Age Violation Guarantees

This work investigates the probability that the delay and the peak-age of information exceed a desired threshold in a point-to-point communication system with short information packets. The packets are generated according to a stationary memoryless Bernoulli process, placed in a single-server queue and then transmitted over a wireless channel. A variable-length stop-feedback coding scheme---a general strategy that encompasses simple automatic repetition request (ARQ) and more sophisticated hybrid ARQ techniques as special cases---is used by the transmitter to convey the information packets to the receiver. By leveraging finite-blocklength results, the delay violation and the peak-age violation probabilities are characterized without resorting to approximations based on large-deviation theory as in previous literature. Numerical results illuminate the dependence of delay and peak-age violation probability on system parameters such as the frame size and the undetected error probability, and on the chosen packet-management policy. The guidelines provided by our analysis are particularly useful for the design of low-latency ultra-reliable communication systems.Comment: To appear in IEEE journal on selected areas of communication (IEEE JSAC

Joint Sum Rate And Error Probability Optimization: Finite Blocklength Analysis

We study the tradeoff between the sum rate and the error probability in downlink of wireless networks. Using the recent results on the achievable rates of finite-length codewords, the problem is cast as a joint optimization of the network sum rate and the per-user error probability. Moreover, we develop an efficient algorithm based on the divide-and-conquer technique to simultaneously maximize the network sum rate and minimize the maximum users' error probability and to evaluate the effect of the codewords length on the system performance. The results show that, in delay-constrained scenarios, optimizing the per-user error probability plays a key role in achieving high throughput.Comment: Accepted for publication in IEEE Wireless Communications Letter

Secure Short-Packet Communications via UAV-Enabled Mobile Relaying: Joint Resource Optimization and 3D Trajectory Design

Short-packet communication (SPC) and unmanned aerial vehicles (UAVs) are anticipated to play crucial roles in the development of 5G-and-beyond wireless networks and the Internet of Things (IoT). In this paper, we propose a secure SPC system, where a UAV serves as a mobile decode-and-forward (DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and UAV's trajectory. While the overall optimization problem is nonconvex, we tackle it by applying a block successive convex approximation (BSCA) approach to divide the original problem into three subproblems and solve them separately. Then, an overall iterative algorithm is proposed to obtain the final design with guaranteed convergence. Our proposed low-complexity algorithm incorporates 3D trajectory design and resource management to optimize the effective average secrecy throughput of the communication system over the course of UAV-relay's mission. Simulation results demonstrate significant performance improvements compared to various benchmark schemes and provide useful design insights on the coding blocklengths and transmit powers along the trajectory of the UAV

Link-Layer Rate of Multiple Access Technologies with Short-Packet Communications for uRLLC

Mission-critical applications such as autonomous vehicles, tactile Internet, and factory automation require seamless connectivity with stringent requirements of latency and reliability. These futuristic applications are supported with the service class of ultra reliable and low-latency communications (uRLLC). In this thesis, the performance of core enablers of the uRLLC, non-orthogonal multiple access (NOMA), and NOMA-random access (NOMA-RA) in conjunction with the short-packet communications regime is investigated. More specifically, the achievable effective capacity (EC) of two-user and multi-user NOMA and conditional throughput of the NOMA-RA with short-packet communications are derived. A closed-form expressions for the EC of two-user NOMA network in finite blocklength regime (short-packet communication) is derived, while considering transmissions over Rayleigh fading channels and adopting a practical path-loss model. While considering the multi-user NOMA network, the total EC of two-user NOMA subsets is derived, which shows that the NOMA set with users having distinct channel conditions achieve maximum aggregate EC. The comparison of link-layer rate of NOMA and orthogonal multiple access (OMA) shows that OMA with short-packet communications outperformed the NOMA at low SNR (20dB). However, at high SNR region (from 20dB to 40dB), the two-user NOMA performs much better than OMA. To further investigate the impact of the channel conditions on the link-layer rate of NOMA and OMA, the simulation results with generalized fading model, i.e., Nakagami-m are also presented. The NOMA-RA with short-packet communications is also regarded as the core enabler of uRLLC. How the NOMA-RA with short-packet communications access the link-layer resources is investigated in detail. The conditional throughput of NOMA-RA is derived and compared with the conventional multiple access scheme. It is clear that NOMA-RA with optimal access probability region (from 0.05 to 0.1) shows maximum performance. Finally, the thesis is concluded with future work, and impact of this research on the industrial practice are also highlighted

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