570 research outputs found

    Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

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    The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

    Design and Real-World Evaluation of Dependable Wireless Cyber-Physical Systems

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    The ongoing effort for an efficient, sustainable, and automated interaction between humans, machines, and our environment will make cyber-physical systems (CPS) an integral part of the industry and our daily lives. At their core, CPS integrate computing elements, communication networks, and physical processes that are monitored and controlled through sensors and actuators. New and innovative applications become possible by extending or replacing static and expensive cable-based communication infrastructures with wireless technology. The flexibility of wireless CPS is a key enabler for many envisioned scenarios, such as intelligent factories, smart farming, personalized healthcare systems, autonomous search and rescue, and smart cities. High dependability, efficiency, and adaptivity requirements complement the demand for wireless and low-cost solutions in such applications. For instance, industrial and medical systems should work reliably and predictably with performance guarantees, even if parts of the system fail. Because emerging CPS will feature mobile and battery-driven devices that can execute various tasks, the systems must also quickly adapt to frequently changing conditions. Moreover, as applications become ever more sophisticated, featuring compact embedded devices that are deployed densely and at scale, efficient designs are indispensable to achieve desired operational lifetimes and satisfy high bandwidth demands. Meeting these partly conflicting requirements, however, is challenging due to imperfections of wireless communication and resource constraints along several dimensions, for example, computing, memory, and power constraints of the devices. More precisely, frequent and correlated message losses paired with very limited bandwidth and varying delays for the message exchange significantly complicate the control design. In addition, since communication ranges are limited, messages must be relayed over multiple hops to cover larger distances, such as an entire factory. Although the resulting mesh networks are more robust against interference, efficient communication is a major challenge as wireless imperfections get amplified, and significant coordination effort is needed, especially if the networks are dynamic. CPS combine various research disciplines, which are often investigated in isolation, ignoring their complex interaction. However, to address this interaction and build trust in the proposed solutions, evaluating CPS using real physical systems and wireless networks paired with formal guarantees of a system’s end-to-end behavior is necessary. Existing works that take this step can only satisfy a few of the abovementioned requirements. Most notably, multi-hop communication has only been used to control slow physical processes while providing no guarantees. One of the reasons is that the current communication protocols are not suited for dynamic multi-hop networks. This thesis closes the gap between existing works and the diverse needs of emerging wireless CPS. The contributions address different research directions and are split into two parts. In the first part, we specifically address the shortcomings of existing communication protocols and make the following contributions to provide a solid networking foundation: • We present Mixer, a communication primitive for the reliable many-to-all message exchange in dynamic wireless multi-hop networks. Mixer runs on resource-constrained low-power embedded devices and combines synchronous transmissions and network coding for a highly scalable and topology-agnostic message exchange. As a result, it supports mobile nodes and can serve any possible traffic patterns, for example, to efficiently realize distributed control, as required by emerging CPS applications. • We present Butler, a lightweight and distributed synchronization mechanism with formally guaranteed correctness properties to improve the dependability of synchronous transmissions-based protocols. These protocols require precise time synchronization provided by a specific node. Upon failure of this node, the entire network cannot communicate. Butler removes this single point of failure by quickly synchronizing all nodes in the network without affecting the protocols’ performance. In the second part, we focus on the challenges of integrating communication and various control concepts using classical time-triggered and modern event-based approaches. Based on the design, implementation, and evaluation of the proposed solutions using real systems and networks, we make the following contributions, which in many ways push the boundaries of previous approaches: • We are the first to demonstrate and evaluate fast feedback control over low-power wireless multi-hop networks. Essential for this achievement is a novel co-design and integration of communication and control. Our wireless embedded platform tames the imperfections impairing control, for example, message loss and varying delays, and considers the resulting key properties in the control design. Furthermore, the careful orchestration of control and communication tasks enables real-time operation and makes our system amenable to an end-to-end analysis. Due to this, we can provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics. • We propose control-guided communication, a novel co-design for distributed self-triggered control over wireless multi-hop networks. Self-triggered control can save energy by transmitting data only when needed. However, there are no solutions that bring those savings to multi-hop networks and that can reallocate freed-up resources, for example, to other agents. Our control system informs the communication system of its transmission demands ahead of time so that communication resources can be allocated accordingly. Thus, we can transfer the energy savings from the control to the communication side and achieve an end-to-end benefit. • We present a novel co-design of distributed control and wireless communication that resolves overload situations in which the communication demand exceeds the available bandwidth. As systems scale up, featuring more agents and higher bandwidth demands, the available bandwidth will be quickly exceeded, resulting in overload. While event-triggered control and self-triggered control approaches reduce the communication demand on average, they cannot prevent that potentially all agents want to communicate simultaneously. We address this limitation by dynamically allocating the available bandwidth to the agents with the highest need. Thus, we can formally prove that our co-design guarantees closed-loop stability for physical systems with stochastic linear time-invariant dynamics.:Abstract Acknowledgements List of Abbreviations List of Figures List of Tables 1 Introduction 1.1 Motivation 1.2 Application Requirements 1.3 Challenges 1.4 State of the Art 1.5 Contributions and Road Map 2 Mixer: Efficient Many-to-All Broadcast in Dynamic Wireless Mesh Networks 2.1 Introduction 2.2 Overview 2.3 Design 2.4 Implementation 2.5 Evaluation 2.6 Discussion 2.7 Related Work 3 Butler: Increasing the Availability of Low-Power Wireless Communication Protocols 3.1 Introduction 3.2 Motivation and Background 3.3 Design 3.4 Analysis 3.5 Implementation 3.6 Evaluation 3.7 Related Work 4 Feedback Control Goes Wireless: Guaranteed Stability over Low-Power Multi-Hop Networks 4.1 Introduction 4.2 Related Work 4.3 Problem Setting and Approach 4.4 Wireless Embedded System Design 4.5 Control Design and Analysis 4.6 Experimental Evaluation 4.A Control Details 5 Control-Guided Communication: Efficient Resource Arbitration and Allocation in Multi-Hop Wireless Control Systems 5.1 Introduction 5.2 Problem Setting 5.3 Co-Design Approach 5.4 Wireless Communication System Design 5.5 Self-Triggered Control Design 5.6 Experimental Evaluation 6 Scaling Beyond Bandwidth Limitations: Wireless Control With Stability Guarantees Under Overload 6.1 Introduction 6.2 Problem and Related Work 6.3 Overview of Co-Design Approach 6.4 Predictive Triggering and Control System 6.5 Adaptive Communication System 6.6 Integration and Stability Analysis 6.7 Testbed Experiments 6.A Proof of Theorem 4 6.B Usage of the Network Bandwidth for Control 7 Conclusion and Outlook 7.1 Contributions 7.2 Future Directions Bibliography List of Publication

    Multi-sinusoidal waveform shaping for integrated data and energy transfer in aging channels

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    Integrated data and energy transfer (IDET) is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything (IoE) devices. We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer (WET) and orthogonal-frequency-division-multiplexing (OFDM) signals for wireless data transfer (WDT). The outdated channel state information (CSI) in aging channels is employed by the transmitter to shape IDET waveforms. With the constraints of transmission power and WDT requirement, the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average direct-current (DC) among a limited number of transmission frames with the existence of carrier-frequency-offset (CFO). For the amplitude optimisation, the original non-convex problem can be transformed into a reversed geometric programming problem, then it can be effectively solved with existing tools. As for the phase optimisation, the artificial bee colony (ABC) algorithm is invoked in order to deal with the non-convexity. Iteration between the amplitude optimisation and phase optimisation yields our joint design. Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI

    Distributed consensus in wireless network

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    Connected autonomous systems, which are powered by the synergistic integration of the Internet of Things (IoT), Artificial Intelligence (AI), and 5G technologies, predominantly rely on a central node for making mission-critical decisions. This reliance poses a significant challenge that the condition and capability of the central node largely determine the reliability and effectiveness of decision-making. Maintaining such a centralized system, especially in large-scale wireless networks, can be prohibitively expensive and encounters scalability challenges. In light of these limitations, there’s a compelling need for innovative methods to address the increasing demands of reliability and latency, especially in mission-critical networks where cooperative decision-making is paramount. One promising avenue lies in the distributed consensus protocol, a mechanism intrinsic to distributed computing systems. These protocols offer enhanced robustness, ensuring continued functionality and responsiveness in decision-making even in the face of potential node or communication failures. This thesis pivots on the idea of leveraging distributed consensus to bolster the reliability of mission-critical decision-making within wireless networks, which delves deep into the performance characteristics of wireless distributed consensus, analyzing and subsequently optimizing its attributes, specifically focusing on reliability and latency. The research begins with a fundamental model of consensus reliability in an crash fault tolerance protocol Raft. A novel metric termed ReliabilityGain is introduced to analyze the performance of distributed consensus in wireless network. This innovative concept elucidates the linear correlation between the reliability inherent to consensus-driven decision-making and the reliability of communication link transmission. An intriguing discovery made in my study is the inherent trade-off between the time latency of achieving consensus and its reliability. These two variables appear to be in contradiction, which brings further performance optimization issues. The performance of the Crash and Byzantine fault tolerance protocol is scrutinized and they are compared with original centralized consensus. This exploration becomes particularly pertinent when communication failures occur in wireless distributed consensus. The analytical results are juxtaposed with performance metrics derived from a centralized consensus mechanism. This comparative analysis illuminates the relative merits and demerits of these consensus strategies, evaluated from the dual perspectives of comprehensive consensus reliability and communication latency. In light of the insights gained from the detailed analysis of the Raft and Hotstuff BFT protocols, my thesis further ventures into the realm of optimization strategies for wireless distributed consensus. A central facet of this exploration is the introduction of a tailored communication resource allocation scheme. This scheme, rooted in maximizing the performance of consensus mechanisms, dynamically assesses the network conditions and allocates communication resources such as transmit power and bandwidth to ensure efficient and timely decision-making, which ensures that even in varied and unpredictable network conditions, consensus can be achieved with minimized latency and maximized reliability. The research introduces an adaptive protocol of distributed consensus in wireless network. This proposed adaptive protocol’s strength lies in its ability to autonomously construct consensus-enabled network even if node failures or communication disruptions occur, which ensures that the network’s decision-making process remains uninterrupted and efficient, irrespective of external challenges. The sharding mechanism, which is regarded as an effective solution to scalability issues in distributed system, does not only aid in managing vast networks more efficiently but also ensure that any disruption in one shard cannot compromise the functionality of the entire network. Therefore, this thesis shows the reliability and security analysis of sharding that implemented in wireless distributed system. In essence, these intertwined strategies, rooted in the intricate dance of communication resource allocation, adaptability, and sharding, together form the bedrock of my contributions to enhancing the performance of wireless distributed consensus

    Wireless networks QoS optimization using coded caching and machine learning algorithms

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    Proactive caching shows great potential to minimize peak traffic rates by storing popular data, in advance, at different nodes in the network. We study three new angles of proactive caching that were not covered before in the literature. We develop more practical algorithms that bring proactive caching closer to practical wireless networks. The first angle is where the popularities of the cached files are changing over time and the file delivery is asynchronous. We provide an algorithm that minimizes files’ delivery rate under this setting. We show that we can use the file delivery messages to proactively and constantly update the receiver finite caches. We show that this mechanism reduces the downloaded traffic of the network. The proposed scheme uses index coding [1], and app. A to jointly encodes the delivery of different demanded files with the cache updates to other receivers to follow the changes in the file popularities. An offline and online (dynamic) versions of the scheme are proposed, where the offline version requires knowledge of the file popularities across the whole transmission period in advance and the online one requires the file popularities for one succeeding time slot only. The optimal caching for both the offline and online schemes is obtained numerically. The second angle is the study of segmented caching for delay minimization in networks with congested backhaul. Studies have mainly focused on proactively storing popular whole files. For certain categories of files like videos, this is not the best strategy. As videos can be segmented, sending later segments of videos can be less time-critical. Video is expected to constitute 82% of internet traffic by 2020 [2]. We study the effect of segmenting video caching decisions under the assumption that the backhaul is congested. We provide an algorithm for proactive segmented caching that optimizes the choice of segments to be cached to minimize delay and compare the performance to the whole file proactive caching. The third angle focuses on using reinforcement learning for coded caching in networks with changing file popularities. For such a dynamic environment, reinforcement learning has the flexibility to learn the environment and adapt accordingly. We develop a reinforcement learning-based coded caching algorithm and compare its performance to rule-based coded caching

    Security and Privacy for Modern Wireless Communication Systems

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    The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

    Single-Frequency Network Terrestrial Broadcasting with 5GNR Numerology

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    L'abstract è presente nell'allegato / the abstract is in the attachmen
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