A Comprehensive Review of D2D Communication in 5G and B5G Networks

The evolution of Device-to-device (D2D) communication represents a significant breakthrough within the realm of mobile technology, particularly in the context of 5G and beyond 5G (B5G) networks. This innovation streamlines the process of data transfer between devices that are in close physical proximity to each other. D2D communication capitalizes on the capabilities of nearby devices to communicate directly with one another, thereby optimizing the efficient utilization of available network resources, reducing latency, enhancing data transmission speed, and increasing the overall network capacity. In essence, it empowers more effective and rapid data sharing among neighboring devices, which is especially advantageous within the advanced landscape of mobile networks such as 5G and B5G. The development of D2D communication is largely driven by mobile operators who gather and leverage short-range communications data to propel this technology forward. This data is vital for maintaining proximity-based services and enhancing network performance. The primary objective of this research is to provide a comprehensive overview of recent progress in different aspects of D2D communication, including the discovery process, mode selection methods, interference management, power allocation, and how D2D is employed in 5G technologies. Furthermore, the study also underscores the unresolved issues and identifies the challenges associated with D2D communication, shedding light on areas that need further exploration and developmen

Security for 5G Mobile Wireless Networks

The advanced features of 5G mobile wireless network systems yield new security requirements and challenges. This paper presents a comprehensive survey on security of 5G wireless network systems compared to the traditional cellular networks. The paper starts with a review on 5G wireless networks particularities as well as on the new requirements and motivations of 5G wireless security. The potential attacks and security services with the consideration of new service requirements and new use cases in 5G wireless networks are then summarized. The recent development and the existing schemes for the 5G wireless security are presented based on the corresponding security services including authentication, availability, data confidentiality, key management and privacy. The paper further discusses the new security features involving different technologies applied to 5G such as heterogeneous networks, device-to-device communications, massive multiple-input multiple-output, software defined networks and Internet of Things. Motivated by these security research and development activities, we propose a new 5G wireless security architecture, based on which the analysis of identity management and flexible authentication is provided. As a case study, we explore a handover procedure as well as a signaling load scheme to show the advantage of the proposed security architecture. The challenges and future directions of 5G wireless security are finally summarized

Wireless Device Authentication Techniques Using Physical-Layer Device Fingerprint

Due to the open nature of the radio signal propagation medium, wireless communication is inherently more vulnerable to various attacks than wired communication. Consequently, communication security is always one of the critical concerns in wireless networks. Given that the sophisticated adversaries may cover up their malicious behaviors through impersonation of legitimate devices, reliable wireless authentication is becoming indispensable to prevent such impersonation-based attacks through verification of the claimed identities of wireless devices. Conventional wireless authentication is achieved above the physical layer using upper-layer identities and key-based cryptography. As a result, user authenticity can even be validated for the malicious attackers using compromised security key. Recently, many studies have proven that wireless devices can be authenticated by exploiting unique physical-layer characteristics. Compared to the key-based approach, the possession of such physical-layer characteristics is directly associated with the transceiver\u27s unique radio-frequency hardware and corresponding communication environment, which are extremely difficult to forge in practice. However, the reliability of physical-layer authentication is not always high enough. Due to the popularity of cooperative communications, effective implementation of physical-layer authentication in wireless relay systems is urgently needed. On the other hand, the integration with existing upper-layer authentication protocols still has many challenges, e.g., end-to-end authentication. This dissertation is motivated to develop novel physical-layer authentication techniques in addressing the aforementioned challenges. In achieving enhanced wireless authentication, we first specifically identify the technique challenges in authenticating cooperative amplify-and-forward (AF) relay. Since AF relay only works at the physical layer, all of the existing upper-layer authentication protocols are ineffective in identifying AF relay nodes. To solve this problem, a novel device fingerprint of AF relay consisting of wireless channel gains and in-phase and quadrature imbalances (IQI) is proposed. Using this device fingerprint, satisfactory authentication accuracy is achieved when the signal-to-noise ratio is high enough. Besides, the optimal AF relay identification system is studied to maximize the performance of identifying multiple AF relays in the low signal-to-noise regime and small IQI. The optimal signals for quadrature amplitude modulation and phase shift keying modulations are derived to defend against the repeated access attempts made by some attackers with specific IQIs. Exploring effective authentication enhancement technique is another key objective of this dissertation. Due to the fast variation of channel-based fingerprints as well as the limited range of device-specific fingerprints, the performance of physical-layer authentication is not always reliable. In light of this, the physical-layer authentication is enhanced in two aspects. On the one hand, the device fingerprinting can be strengthened by considering multiple characteristics. The proper characteristics selection strategy, measurement method and optimal weighted combination of the selected characteristics are investigated. On the other hand, the accuracy of fingerprint estimation and differentiation can be improved by exploiting diversity techniques. To be specific, cooperative diversity in the form of involving multiple collaborative receivers is used in differentiating both frequency-dependent and frequency-independent device fingerprints. As a typical combining method of the space diversity techniques, the maximal-ratio combining is also applied in the receiver side to combat the channel degeneration effect and increase the fingerprint-to-noise ratio. Given the inherent weaknesses of the widely utilized upper-layer authentication protocols, it is straightforward to consider physical-layer authentication as an effective complement to reinforce existing authentication schemes. To this end, a cross-layer authentication is designed to seamlessly integrate the physical-layer authentication with existing infrastructures and protocols. The specific problems such as physical-layer key generation as well as the end-to-end authentication in networks are investigated. In addition, the authentication complexity reduction is also studied. Through prediction, pre-sharing and reusing the physical-layer information, the authentication processing time can be significantly shortened

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

A Neighborhood-Based Trust Protocol for Secure Collaborative Routing in Wireless Mobile D2D HetNets

Heterogeneous Device-to-Device mobile networks are characterised by frequent network disruption and unreliability of peers delivering messages to destinations. Trust-based protocols has been widely used to mitigate the security and performance problems in D2D networks. Despite several efforts made by previous researchers in the design of trust-based routing for efficient collaborative networks, there are fewer related studies that focus on the peers’ neighbourhood as a routing metrics’ element for a secure and efficient trust-based protocol. In this paper, we propose and validate a trust-based protocol that takes into account the similarity of peers’ neighbourhood coefficients to improve routing performance in mobile HetNets environments. The results of this study demonstrate that peers’ neighborhood connectivity in the network is a characteristic that can influence peers’ routing performance. Furthermore, our analysis shows that our proposed protocol only forwards the message to the companions with a higher probability of delivering the packets, thus improving the delivery ratio and minimizing latency and mitigating the problem of malicious peers ( using packet dropping strategy)

Enable Reliable and Secure Data Transmission in Resource-Constrained Emerging Networks

The increasing deployment of wireless devices has connected humans and objects all around the world, benefiting our daily life and the entire society in many aspects. Achieving those connectivity motivates the emergence of different types of paradigms, such as cellular networks, large-scale Internet of Things (IoT), cognitive networks, etc. Among these networks, enabling reliable and secure data transmission requires various resources including spectrum, energy, and computational capability. However, these resources are usually limited in many scenarios, especially when the number of devices is considerably large, bringing catastrophic consequences to data transmission. For example, given the fact that most of IoT devices have limited computational abilities and inadequate security protocols, data transmission is vulnerable to various attacks such as eavesdropping and replay attacks, for which traditional security approaches are unable to address. On the other hand, in the cellular network, the ever-increasing data traffic has exacerbated the depletion of spectrum along with the energy consumption. As a result, mobile users experience significant congestion and delays when they request data from the cellular service provider, especially in many crowded areas. In this dissertation, we target on reliable and secure data transmission in resource-constrained emerging networks. The first two works investigate new security challenges in the current heterogeneous IoT environment, and then provide certain countermeasures for reliable data communication. To be specific, we identify a new physical-layer attack, the signal emulation attack, in the heterogeneous environment, such as smart home IoT. To defend against the attack, we propose two defense strategies with the help of a commonly found wireless device. In addition, to enable secure data transmission in large-scale IoT network, e.g., the industrial IoT, we apply the amply-and-forward cooperative communication to increase the secrecy capacity by incentivizing relay IoT devices. Besides security concerns in IoT network, we seek data traffic alleviation approaches to achieve reliable and energy-efficient data transmission for a group of users in the cellular network. The concept of mobile participation is introduced to assist data offloading from the base station to users in the group by leveraging the mobility of users and the social features among a group of users. Following with that, we deploy device-to-device data offloading within the group to achieve the energy efficiency at the user side while adapting to their increasing traffic demands. In the end, we consider a perpendicular topic - dynamic spectrum access (DSA) - to alleviate the spectrum scarcity issue in cognitive radio network, where the spectrum resource is limited to users. Specifically, we focus on the security concerns and further propose two physical-layer schemes to prevent spectrum misuse in DSA in both additive white Gaussian noise and fading environments