Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

Maritime coverage enhancement using UAVs coordinated with hybrid satellite-terrestrial networks

Due to the agile maneuverability, unmanned aerial vehicles (UAVs) have shown great promise for on-demand communications. In practice, UAV-aided aerial base stations are not separate. Instead, they rely on existing satellites/terrestrial systems for spectrum sharing and efficient backhaul. In this case, how to coordinate satellites, UAVs and terrestrial systems is still an open issue. In this paper, we deploy UAVs for coverage enhancement of a hybrid satellite-terrestrial maritime communication network. Using a typical composite channel model including both large-scale and small-scale fading, the UAV trajectory and in-flight transmit power are jointly optimized, subject to constraints on UAV kinematics, tolerable interference, backhaul, and the total energy of the UAV for communications. Different from existing studies, only the location-dependent large-scale channel state information (CSI) is assumed available, because it is difficult to obtain the small-scale CSI before takeoff in practice and the ship positions can be obtained via the dedicated maritime Automatic Identification System. The optimization problem is non-convex. We solve it by using problem decomposition, successive convex optimization and bisection searching tools. Simulation results demonstrate that the UAV fits well with existing satellite and terrestrial systems, using the proposed optimization framework

Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030

The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment

Empowering the 6G Cellular Architecture with Open RAN

Innovation and standardization in 5G have brought advancements to every facet of the cellular architecture. This ranges from the introduction of new frequency bands and signaling technologies for the radio access network (RAN), to a core network underpinned by micro-services and network function virtualization (NFV). However, like any emerging technology, the pace of real-world deployments does not instantly match the pace of innovation. To address this discrepancy, one of the key aspects under continuous development is the RAN with the aim of making it more open, adaptive, functional, and easy to manage. In this paper, we highlight the transformative potential of embracing novel cellular architectures by transitioning from conventional systems to the progressive principles of Open RAN. This promises to make 6G networks more agile, cost-effective, energy-efficient, and resilient. It opens up a plethora of novel use cases, ranging from ubiquitous support for autonomous devices to cost-effective expansions in regions previously underserved. The principles of Open RAN encompass: (i) a disaggregated architecture with modular and standardized interfaces; (ii) cloudification, programmability and orchestration; and (iii) AI-enabled data-centric closed-loop control and automation. We first discuss the transformative role Open RAN principles have played in the 5G era. Then, we adopt a system-level approach and describe how these Open RAN principles will support 6G RAN and architecture innovation. We qualitatively discuss potential performance gains that Open RAN principles yield for specific 6G use cases. For each principle, we outline the steps that research, development and standardization communities ought to take to make Open RAN principles central to next-generation cellular network designs.Comment: This paper is part of the IEEE JSAC SI on Open RAN. Please cite as: M. Polese, M. Dohler, F. Dressler, M. Erol-Kantarci, R. Jana, R. Knopp, T. Melodia, "Empowering the 6G Cellular Architecture with Open RAN," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2023.333461

ieee access special section editorial intelligent systems for the internet of things

The underlying concept of the Internet of Things (IoT) is simply to connect all devices and systems together via the Internet so that more suitable services can be provided to users. Many infrastructures, systems, and devices of the IoT have matured while some are still being developed. This is why several recent studies have claimed that IoT will dramatically change our lives. Today, we can find research topics driven by IoT technologies and can imagine that the era of smart homes and cities will be coming in the foreseeable future. The development of the IoT has reached a crossroad. One of the current research trends is to make this kind of system smarter, by using intelligent technologies to provide a much more convenient environment for humans. Among the intelligent technologies, how to handle the massive amount of data generated by the systems and devices of the IoT has been widely considered. Many other technologies, such as data mining, big data analytics, statistical and other analysis technologies, have also been used for analyzing data generated from the IoT. In addition to the analysis technologies, intelligent system technologies also provide many possibilities for the IoT because they can be used to enhance not only the performance of a system and its devices, but they can also be aware of events that have occurred

Performance Optimization Over Wireless Links With Operating Constraints

Wireless communication is one of the most active areas of technological innovations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabilities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and networks depend on their adaptation capability which in turn presents many new technical challenges in hardware and protocol design, power management, interference metrics, distributed algorithms, Quality of Service (QoS) requirements arid security issues. Transmitter adaptation methods have gained importance, and numerous transmitter optimization algorithms have been proposed in recent years. The main idea behind these algorithms is to optimize the transmitted signals according to the patterns of interference in the operating environment such that some specific criterion is optimized. In this context, the objective of this dissertation is to propose transmitter adaptation algorithms in conjunction with power control for wireless systems focusing on performance optimization based on operating constraints. Specifically, this dissertation achieves joint transmitter adaptation and power control in the uplink and downlink of wireless systems with applications to Multiple-Input-Multiple-Output (MIMO) wireless systems and cognitive radio networks. In addition, performance of the proposed algorithms are evaluated in the context of fading channels, taking into consideration the time-varying nature of wireless channels