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

An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT.

Social Edge Service (SES) is an emerging mechanism in the Social Internet of Things (SIoT) orchestration for effective user-centric reliable communication and computation. The services are affected by active and/or passive attacks such as replay attacks, message tampering because of sharing the same spectrum, as well as inadequate trust measurement methods among intelligent devices (roadside units, mobile edge devices, servers) during computing and content-sharing. These issues lead to computation and communication overhead of servers and computation nodes. To address this issue, we propose the HybridgrAph-Deep-learning (HAD) approach in two stages for secure communication and computation. First, the Adaptive Trust Weight (ATW) model with relation-based feedback fusion analysis to estimate the fitness-priority of every node based on directed graph theory to detect malicious nodes and reduce computation and communication overhead. Second, a Quotient User-centric Coeval-Learning (QUCL) mechanism to formulate secure channel selection, and Nash equilibrium method for optimizing the communication to share data over edge devices. The simulation results confirm that our proposed approach has achieved effective communication and computation performance, and enhanced Social Edge Services (SES) reliability than state-of-the-art approaches

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors