Reconfigurable Intelligent Surfaces: A Physical Layer Security Perspective

Lipps, Christoph; Herbst, Jan; Reddy, Rekha; Franke, Lars; Becker, Sven; Rahm, Marco; Schotten, Hans D.

doi:10.1109/icdis55630.2022.00034

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…ULBC applies the requirements for dependability and low latency to broadband communication services. Researchers are investigating AI-based methods to improve the performance of ULBC, such as traffic prediction, network slicing, and intelligent beamforming [139]. ULBC can dynamically adapt to network conditions, predict user demand patterns, and optimally allocate resources by employing AI-RAN to ensure smooth broadband access with high reliability and low latency.…”

Section: ) Ultra-reliable Low Latency Broadband Communication (Ulbc)mentioning

confidence: 99%

AI-RAN in 6G Networks: State-of-the-Art and Challenges

Khan,

Schmid

2024

IEEE Open J. Commun. Soc.

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6G is a next-generation cellular communication technology that builds up on existing 5G networks which are currently rolled out worldwide. Through incorporation of artificial intelligence (AI) and machine learning (ML), the core 5G network is advanced into an intelligent 6G network. The 6G Artificial Intelligence Radio Access Network (AI-RAN) is anticipated to offer advanced features like reduced latency, improved bandwidth, data rates and coverage. Furthermore, AI-RAN is expected to support complex use cases such as extreme connectivity, multi-user communications and dynamic spectrum access. This paper provides a detailed survey and thorough assessment of AI-RAN's vision and state-of-the-art challenges. We first present a concise introduction to 6G AI-RAN followed by background information on the current 5G RAN and its challenges that must be overcome to implement 6G AI-RAN. The paper then examines trending research issues in AI-RAN, i.e., challenges related to spectrum allocation, network architecture, and resource management. We discuss the methods to overcome these challenges which include the adoption of advanced machine learning and edge computing technologies to boost the performance of 6G AI-RAN. We conclude by stating open research directions.

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Section: ) Ultra-reliable Low Latency Broadband Communication (Ulbc)mentioning

confidence: 99%

AI-RAN in 6G Networks: State-of-the-Art and Challenges

Khan,

Schmid

2024

IEEE Open J. Commun. Soc.

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“…These attributed features of being able to manipulate a channel have a direct influence on security, therefore Lipps et al (2022) specified conceivable scenarios in which RIS can be used to increase this security: i) RISenabled beamforming and -splitting, which can mitigate the risk of eavesdropping through the possibility of steered communication towards legitimate users. Besides, tighter beams up to pencil-sharp beamforming can chance the overall properties of a radio link from a broadcast medium to a targeted communication.…”

Section: Reconfigurable Intelligent Surfacesmentioning

confidence: 99%

Designing Security for the Sixth Generation: About Necessity, Concepts and Opportunities

Lipps,

Tjabben,

Rüb

et al. 2023

eccws

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Intelligent, comprehensive and, above all, secure wireless interconnection is the driving force behind technological progress. To ensure this, the development towards Sixth Generation (6G) Wireless Systems has been launched and is scheduled to be operational by 2030. This data technology of the future turns 6G into the infrastructure of a new generation of mobile, intelligent, and context-sensitive services, available everywhere and featuring high trustworthiness and performance, relying on both, network-side and off-network context sources. In addition, the networks themselves ought to become intelligent and thus more efficient and resource-saving, which requires a high degree of automated utilization of Artificial Intelligence (AI). Building upon the principles of information and communication theory for both the physical (bit)-transmission layer (PHY) and media access, new communication concepts for 6G will be developed providing the foundations for research into new single and multi-user operation, access and core networks. The flip side of this coin of opportunities: Sophisticated technology inevitably leads to additional security vulnerabilities, open access systems and Open-Radio Access Network (O-RAN) approaches imply new attack vectors. The holistic interconnection of everything renders it ever more attractive to attackers to harm systems, and create damage. Furthermore, enhanced computational power along with quantum computers make conventional systems more vulnerable than ever, and the value of the transmitted data increases tremendously: It is not only machine and sensor data, but also very personal and healthcare data transmitted with 6G. Therefore, the aim is to build a resilient and secure 6G system capable of recognizing attacks and uncertainties, flexibly absorbing them, recovering in a timely and sustainable manner, and compensating for impaired functionality through transformation. This holistic resilience-by-design approach is based, among other things, on technology such as Quantum Key Distribution (QKD) and Post Quantum-Crypto to achieve end-to-end security, Reconfigurable Intelligent Surfaces (RISs) to rely, control and manipulate the wireless transmission channel, Wireless Optical Communication (WOC), Physical Layer Security (PhySec), but also Body Area Networks (BANs), the integration of the human body relying on biometrics and the Tactile Internet (TI). These concepts will be discussed and shed light on in the scope of this work.

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“…MIMO and millimeter waves are dual new technologies that 5G uses to give wireless networks greater flexibility and efficiency, 4 although many serious obstacles still need to be overcome 5 . Despite the fact that 5G has brought cellular communication systems to a new level, they will still not able to meet each future requirements by 2030 6 . For this reason, researchers are now concentrating on sixth generation (6G) wireless communication networks 7 .…”

Section: Introductionmentioning

confidence: 99%

Optimized wireless communication for 6G signal processing using memory‐augmented deep unfolding network

Eswaramoorthi,

Prasad,

et al. 2024

Int J Communication

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SummaryIn this manuscript, optimized wireless communication for 6G signals processing using memory‐augmented deep unfolding network (WC‐6G‐SP‐MADUN) is proposed. The aim of this work is to give a memory‐augmented deep unfolding network approach with a focus on belief propagation decoding of error correction codes and multiple‐input multiple‐output (MIMO) wireless systems. In contrast, compares and tabulates the performance of memory‐augmented deep unfolding methodologies with classic principled procedures, which could potentially enable 6G. Here, the wireless communication for 6G signal processing methods was used for a variety of receiver functions, including self‐interference cancelation, signal estimation and detection using memory‐augmented deep unfolding Network (MADUN), and advanced error correction by clouded leopard optimization algorithm (CLOA). Furthermore, outline the general framework of memory‐augmented deep unfolding method for any kind of signal processing application and talk about cutting edge research paths that will make it possible to build communication networks in the future. The proposed approach is implemented in MATLAB; the performance is analyzed with performance metrics such as reliability, complexity, SNR gain, convergence rate, hardware efficiency, and quantization bit width. The proposed approach attains higher SNR gain 17.96%, 24.75%, and 30.09%; lower complexity 17.92%, 23.41%, and 30.13%; and higher convergence 18.01%, 25.41%, and 31.39% when analyzed with existing techniques such as redefined wireless communication for 6G: signal processing meets deep learning and deep unfolding (RWC‐6G‐SP‐DU), lower complication deep unfolded neural network receiver for MIMO under probability data association detector (LC‐DUNN‐MIMO‐PDAD), and deep learning in physical layer communications: evolution with prospects on 5G and 6G networks (DL‐PLC‐6G), respectively.

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Reconfigurable Intelligent Surfaces: A Physical Layer Security Perspective

Cited by 9 publications

References 22 publications

AI-RAN in 6G Networks: State-of-the-Art and Challenges

AI-RAN in 6G Networks: State-of-the-Art and Challenges

Designing Security for the Sixth Generation: About Necessity, Concepts and Opportunities

Optimized wireless communication for 6G signal processing using memory‐augmented deep unfolding network

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