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

A Caching Strategy Towards Maximal D2D Assisted Offloading Gain

Device-to-Device (D2D) communications incorporated with content caching have been regarded as a promising way to offload the cellular traffic data. In this paper, the caching strategy is investigated to maximize the D2D offloading gain with the comprehensive consideration of user collaborative characteristics as well as the physical transmission conditions. Specifically, for a given content, the number of interested users in different groups is different, and users always ask the most trustworthy user in proximity for D2D transmissions. An analytical expression of the D2D success probability is first derived, which represents the probability that the received signal to interference ratio is no less than a given threshold. As the formulated problem is non-convex, the optimal caching strategy for the special unbiased case is derived in a closed form, and a numerical searching algorithm is proposed to obtain the globally optimal solution for the general case. To reduce the computational complexity, an iterative algorithm based on the asymptotic approximation of the D2D success probability is proposed to obtain the solution that satisfies the Karush-Kuhn-Tucker conditions. The simulation results verify the effectiveness of the analytical results and show that the proposed algorithm outperforms the existing schemes in terms of offloading gain.Comment: Accepted in IEEE Transactions on Mobile Computin

Secrecy-Optimized Resource Allocation for Device-to-Device Communication Undelaying Cellular Networks

L’objectif principal de l’introduction de la communication de périphérique-à-périphérique «device-to-device» (D2D) sous-jacente aux systèmes de communication sans fil de cinquième génération (5G), est d’augmenter l’efficacité spectrale (ES). Cependant, la communication D2D sous-jacente aux réseaux cellulaires peut entraîner une dégradation des performances causée par des co-interférences de canal sévères entre les liaisons cellulaires et D2D. De plus, en raison de la complexité du contrôle et de la gestion, les connexions directes entre les appareils à proximité sont vulnérables. En conséquence, la communication D2D n’est pas robuste contre les menaces de sécurité et l’écoute clandestine. Pourtant, les co-interférences de canal peuvent être adoptées pour aider les utilisateurs cellulaires (UC) et les paires D2D afin d’empêcher l’écoute clandestine. Dans cette thèse, nous étudions différents scénarios de problèmes d’allocation de ressources en utilisant le concept de sécurité de couche physique «physical layer security» (PLS) pour la communication D2D sous-jacente aux réseaux cellulaires, tout en satisfaisant les exigences minimales de qualité de service (QoS) des liaisons cellulaires et D2D. Dans le cas où PLS est pris en compte, l’interférence peut aider à réduire l’écoute clandestine. Premièrement, nous formulons un scénario d’allocation de ressources dans lequel chaque bloc de ressources (RB) temps-fréquence de multiplexage par répartition orthogonale en fréquence (OFDM) peut être partagé par une seule CU et une paire D2D dans un réseau unicellulaire. Le problème formulé est réduit au problème de correspondance tridimensionnelle, qui est généralement NP-difficile, et la solution optimale peut être obtenue par des méthodes compliquées, telles que la recherche par force brute et/ou l’algorithme de branchement et de liaison qui ont une complexité de calcul exponentielle. Nous proposons donc une méta-heuristique basée sur l’algorithme de recherche tabou «Tabu Search» (TS) avec une complexité de calcul réduite pour trouver globalement la solution d’allocation de ressources radio quasi-optimale.----------ABSTRACT: The primary goal of introducing device-to-device (D2D) communication underlying fifthgeneration (5G) wireless communication systems is to increase spectral efficiency (ES). However, D2D communication underlying cellular networks can lead to performance degradation caused by severe co-channel interference between cellular and D2D links. In addition, due to the complexity of control and management, direct connections between nearby devices are vulnerable. Thus, D2D communication is not robust against security threats and eavesdropping. On the other hand, the co-channel interference can be adopted to help cellular users (CUs) and D2D pairs to prevent eavesdropping. In this thesis, we investigate different resource allocation problem scenarios using the physical layer security (PLS) concept for the D2D communication underlying cellular networks, while satisfying the minimum quality of service (QoS) requirements of cellular and D2D link. If the PLS is taken into account, the interference can help reduce eavesdropping. First, we formulate a resource allocation scenario in which each orthogonal frequency-division multiplexing (OFDM) time-frequency resource block (RB) can be shared by one single CU and one D2D pair in a single-cell network. The formulated problem is reduced to the threedimensional matching problem, which is generally NP-hard, and the optimal solution can be obtained through the complicated methods, such as brute-force search and/or branch-andbound algorithm that have exponential computational complexity. We, therefore, propose a meta-heuristic based on Tabu Search (TS) algorithm with a reduced computational complexity to globally find the near-optimal radio resource allocation solution

Investigation on Evolving Single-Carrier NOMA into Multi-Carrier NOMA in 5G

© 2013 IEEE. Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA

Energy-Efficient Resource Allocation for Industrial Cyber-Physical IoT Systems in 5G Era

Cyber-physical Internet of things system (CPIoTS), as an evolution of Internet of things (IoT), plays a significant role in industrial area to support the interoperability and interaction of various machines (e.g. sensors, actuators, and controllers) by providing seamless connectivity with low bandwidth requirement. The fifth generation (5G) is a key enabling technology to revolutionize the future of industrial CPIoTS. In this paper, a communication framework based on 5G is presented to support the deployment of CPIoTS with a central controller. Based on this framework, multiple sensors and actuators can exchange information with the central controller in full-duplex mode. To accommodate the signal data in the available channel band, a resource allocation problem is formulated as a mixed integer non-convex programming problem, aiming to maximize the sum energy efficiency of CPIoTS. By introducing the transformation, we decompose the resource allocation problem into power allocation and channel allocation. Moreover, we consider an energy-efficient power allocation algorithm based on game theory and Dinkelbach's algorithm. Finally, to reduce the computational complexity, the channel allocation is modeled as a 3-dimensional matching problem, and solved by iterative Hungarian method with virtual devices (IHM-VD). A comparison is completed with well-known existing algorithms to demonstrate the performance of the proposed one. Simulation results confirm the efficiency of the proposed model, which significantly outperforms other benchmark algorithms in terms of meeting the energy efficiency and the QoS requirements