Efficient Traffic Management Algorithms for the Core Network using Device-to-Device Communication and Edge Caching

Exponentially growing number of communicating devices and the need for faster, more reliable and secure communication are becoming major challenges for current mobile communication architecture. More number of connected devices means more bandwidth and a need for higher Quality of Service (QoS) requirements, which bring new challenges in terms of resource and traffic management. Traffic offload to the edge has been introduced to tackle this demand-explosion that let the core network offload some of the contents to the edge to reduce the traffic congestion. Device-to-Device (D2D) communication and edge caching, has been proposed as promising solutions for offloading data. D2D communication refers to the communication infrastructure where the users in proximity communicate with each other directly. D2D communication improves overall spectral efficiency, however, it introduces additional interference in the system. To enable D2D communication, efficient resource allocation must be introduced in order to minimize the interference in the system and this benefits the system in terms of bandwidth efficiency. In the first part of this thesis, low complexity resource allocation algorithm using stable matching is proposed to optimally assign appropriate uplink resources to the devices in order to minimize interference among D2D and cellular users. Edge caching has recently been introduced as a modification of the caching scheme in the core network, which enables a cellular Base Station (BS) to keep copies of the contents in order to better serve users and enhance Quality of Experience (QoE). However, enabling BSs to cache data on the edge of the network brings new challenges especially on deciding on which and how the contents should be cached. Since users in the same cell may share similar content-needs, we can exploit this temporal-spatial correlation in the favor of caching system which is referred to local content popularity. Content popularity is the most important factor in the caching scheme which helps the BSs to cache appropriate data in order to serve the users more efficiently. In the edge caching scheme, the BS does not know the users request-pattern in advance. To overcome this bottleneck, a content popularity prediction using Markov Decision Process (MDP) is proposed in the second part of this thesis to let the BS know which data should be cached in each time-slot. By using the proposed scheme, core network access request can be significantly reduced and it works better than caching based on historical data in both stable and unstable content popularity

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

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.Comment: 10 pages,9 figure

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Power-spectrum trading for full-duplex D2D communications in cellular networks

Device-to-device (D2D) communications allows two adjacent mobile terminals transmit signal directly without going through base stations, which has been considered as one of the key technologies for future mobile networks. As full-duplex (FD) communications can improve the performance (i.e., throughput, energy efficiency (EE)) of communications systems, it is commonly used in practical D2D communications scenarios. However, FD-enabled D2D communications also results in self-interference. To fully realize the potential benefits of FD-enabled D2D communications, an effective resource allocation mechanism is critical to avoid not only the self-interference of FD-enabled D2D communications but also the interference between D2D users (DUs) and cellular users (CUs). In this paper, we investigate the resource allocation issue for FD-enabled DUs and traditional CUs. Considering the asymmetry of energy and spectrum resources of DUs and CUs, we propose a power-spectrum trading mechanism to achieve mutual benefits for both types of users. A concave-convex procedure algorithm is employed to solve the optimization problem of power allocation, and then a maximum weighted bipartite matching based method is proposed to select proper D2D pairs to maximize the overall system throughput. Numerical results show that the proposed scheme can remarkably improve the overall throughput and EE of FD-enabled D2D communications system

The Coexistence of D2D Communication under Heterogeneous Cellular Networks (HetNets)

Device-to-Device (D2D) communication is a promising technique for supporting the stringent requirements of the fifth-generation cellular network (5G). This new technique has garnered significant attention in cellular network standards for proximity communication as a means to improve cellular spectrum utilization, to decrease user equipment energy consumption, and to reduce end-to-end delay. This dissertation reports an investigation of D2D communication coexistence under 5G heterogeneous cellular network (HetNets) in terms of spectrum allocation and energy efficiency. The work reported herein describes a low-complexity D2D resource allocation algorithm for downlink (DL) resource reuse that can be leveraged to improve network throughput. Notably, cross-tier interference was considered when establishing D2D communication (e.g., macro base station to D2D links; small base station to D2D links; and D2D communication to cellular links served by the macro and small base stations). An allocation algorithm was introduced to reduce interference from D2D to cellular when a single D2D link is sharing cellular resources. Performance of the proposed algorithm was evaluated and compared to various resource allocations. Simulation results demonstrated that the proposed algorithm improves overall system throughput. This allocation algorithm achieved a near-optimal solution when compared with a brute force approach. This dissertation also presents a novel framework for optimizing the energy efficiency of D2D communication coexistence with HetNets in DL transmission. This optimization problem was mathematically formulated in terms of mode selection, power control, and resources allocation (i.e., NP-hard problem). The optimization fraction problem was simplified based on network load and was solved using various optimization methods. An innovative dynamic mode selection based on Fuzzy clustering was also introduced. Proposed scheme performance was evaluated and compared to the standard algorithm. Simulation validated the advantage of the proposed framework in terms of performance gain in both energy efficiency and the number of successfully connected D2D users. Moreover, the energy efficiency of HetNets with D2D compatibility was improved. Finally, this dissertation details a stochastic analytical model for an LTE scheduler with D2D communication. By assuming exponential distributions for users scheduling time, a throughput estimation model was developed using two-dimensional Continuous Time Markov chains (2D-CTMC) of birth-death type. The proposed model will predict the expected number of D2D operated in dedicated and reuse mode, as well as the systems long-term throughput