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IEEE 25th International conference on High performance Switching and Routing (HPSR)

作者： Piscione, Pietro Abdulwahed, Ahmed K. Giardina, Pietro Landi, Giada Kalfas, George Vagionas, Chris Gatzianas, Marios Gavrilut, Voica Alsted, Christopher Theodoropoulou, Eleni Lyberopoulos, George Saliou, Fabienne Nextworks Pisa Italy Aristotle Univ Thessaloniki Thessaloniki Greece Comcores ApS Lyngby Denmark Hellen Telecommun Org SA Maroussi Greece Orange Paris France

ISBN: (纸本)9798350363869;9798350363852

The aim of this paper is to illustrate the control Plane functionalities, strategies, and procedures in the next generation Central Offices, which are crucial traffic aggregation points close to the subscribers. The next generation Central Offices are becoming integral part of the next generation networks and for this reason the management and control of its internal resources is essential. Initially, the paper explains the next generation Central Offices system architecture and its placement within an end-to-end network. Then, it details the use cases and their quantitative analysis, taking into consideration a dense urban area in Paris city, for estimating the downlink and uplink throughput and latency related requirements. Based on these estimations, the paper defines the next generation Central Office control Plane requirements, along with its functional architecture and its internal functional blocks, detailing their specific roles and interactions to meet the bandwidth and latency demands. Finally, the paper describes an early software prototype implementation based on ETSI TeraFlow SDN, highlighting the software extensions implemented for the support of the next generation Central Office control Plane functionalities, strategies, and procedures. The paper concludes with the next steps for the future work, consisting of the integration with an actual next generation Central Office and a field trial experiment in an end-to-end network.

关键词： Central Office ETSI TFS Software Defined Network control plane Time Sensitive Networking

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Effect of Channel Aging on beyond Diagonal Reconfigurable Intelligent Surfaces

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the communications Society 2024年 5卷 6303-6313页

作者： Papazafeiropoulos, Anastasios Kourtessis, Pandelis Chatzinotas, Symeon University of Hertfordshire Communications and Intelligent Systems Research Group HatfieldAL10 9AB United Kingdom University of Luxembourg SnT Luxembourg City1855 Luxembourg

Reconfigurable intelligent surface (RIS) has appeared as a revolutionary candidate technology for future sixth-generation (6G) networks, but most works have relied on single-connected reflective RISs, which are mathematically described by diagonal phase shift matrices. In this work, based on the recently presented research on beyond diagonal (BD) RIS unifying different RIS models and architectures towards enhanced advantages such as a greater coverage, we study the impact of channel aging due to user equipment (UE) movement. Especially, we evaluate how channel aging diminishes the system performance of multiple sector BD-RIS systems. Through a robust design, concerning the average sum-rate maximisation problem, we jointly design the BD-matrix and transmit precoder under the channel aging conditions. Numerical results show how channel aging affects performance with respect to fundamental system parameters and shed light on how general aging can be compensated. © 2020 IEEE.

关键词： Queueing networks

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INTEGRAN: Towards Vertical and Horizontal Integration for Programmable RAN performance Optimization

INTEGRAN: Towards Vertical and Horizontal Integration for Pr...

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IEEE conference on Computer communications (IEEE INFOCOM)

作者： Kak, Ahan Pham, Van-Quan Thieu, Huu-Trung Sheshadri, Ramanujan K. Choi, Nakjung Nokia Bell Labs Network Syst & Secur Res Murray Hill NJ 07974 USA

ISBN: (纸本)9798350384482;9798350384475

As radio access networks (RANs) evolve to incorporate new paradigms of programmability and control, the Open RAN (or O-RAN) architecture is rapidly becoming the de facto blueprint for designing next-generation cellular networks. While O-RAN has brought forth unprecedented flexibility to the RAN, it has also led to an increase in the management complexity due to the introduction of several new network functions and interfaces, ultimately leading to a disconnected RAN performance optimization (RPO) landscape. To that end, with a view to overcoming the limitations of O-RAN-driven RPO, this paper introduces IntegRAN, an enabling study that makes the case for holistic programmable RPO. Key highlights include a detailed component-level description of the IntegRAN architecture including a set of novel rApps and xApps, along with the implementation of IntegRAN in support of RAN slice lifecycle management, addressing key themes relating to end-to-end slice orchestration and application-specific RAN customization. Furthermore, the paper also includes a comprehensive experimental evaluation on an over-the-air testbed that showcases the operational efficacy of IntegRAN in improving RAN performance while seamlessly leveraging all possible O-RAN functions and interfaces in an integrated manner.

关键词： Radio access networks

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control Overhead Reduction using Length-based Same Destination Aggregation for Large Scale Software Defined networks in next generation Internet of Things 22

Control Overhead Reduction using Length-based Same Destinati...

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IEEE 22nd International conference on Trust, Security and Privacy in Computing and communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Shahzad, Mohammad Liu, Lu Belkout, Nacer Univ Leicester Sch Comp & Math Sci Leicester Leics England Univ Sci & Technol Algiers Dept Comp Sci Bab Ezzouar Algeria

ISBN: (纸本)9798350381993;9798350382006

The Software Defined Networking (SDN) paradigm is rapidly emerging as a viable alternative in the realm of next generation Internet of Things (NG-IoT) due to the inherent challenge posed by traditional computer networks. SDN is revolutionizing traditional network architecture by significantly reducing the reliance on hardware. One of the key challenges of implementing SDN in NG-IoT is the extensive communication that occurs between the switches and the controllers due to the bursty nature of the traffic. Therefore, it is crucial to explore solutions aimed at minimizing this control overhead caused by excessive communication. To alleviate the burden on SDN controllers caused by switches, we propose a new method, named LSDA, which can effectively reduce the flow of control information. To promote fairness within the network, packets heading towards the same controller are aggregated, thereby eliminating the need for complex disassembly in the case of different destination controllers. The simulation results demonstrate that LSDA can effectively reduce the packet loss ratio while simultaneously improving network delay and jitter.

关键词： control overhead Internet of Things Packet Aggregation SDN

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Secure Transmission of UAV control Information via NOMA

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IEEE TRANSACTIONS ON communications 2024年第8期72卷 4648-4660页

作者： Feng, Zhaoxin Lu, Huabing Zhao, Nan Shi, Zhaoyuan Chen, Yunfei Wang, Xianbin Dalian Univ Technol Sch Informat & Commun Engn Dalian 116024 Peoples R China Anqing Normal Univ Key Lab Intelligent Percept & Comp Anhui Prov Anqing 246011 Peoples R China Univ Durham Dept Engn Durham DH1 3LE England Western Univ Dept Elect & Comp Engn London ON N6A 5B9 Canada

Unmanned aerial vehicle (UAV) assisted wireless communication is a key component of the next-generation mobile networks. In coping with the increased dynamics in UAV networks, the transmission of control information is indispensable, requiring not only ultra reliability and low latency, but also high security. In this paper, we investigate the secrecy performance of the control information in a NOMA ground-air short-packet wireless network with an untrusted internal UAV or an external flying eavesdropper, respectively. Both the large-scale path loss and the Nakagami-m small-scale fading are considered. First, the closed-form expressions of the average secure block error rate (BLER) and the average achievable secrecy throughput in each scenario are derived. Then, the asymptotic performance in the high signal-to-noise ratio (SNR) regime is analyzed to get more insights from both scenarios. Specifically, analytical results show that error floors occur with the increase of SNR. Moreover, a one-dimensional search is applied to maximize the average achievable secrecy throughput by optimizing the blocklength. Simulation results are provided to verify the accuracy of analysis and the effectiveness of optimization.

关键词： Autonomous aerial vehicles NOMA Throughput Base stations Wireless networks Signal to noise ratio Resource management Non-orthogonal multiple access physical-layer security short-packet communications unmanned aerial vehicle ultra-reliable and low-latency communications

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Sparsity-Aware Intelligent Massive Random Access control for Massive MIMO networks: A Reinforcement Learning Based Approach

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IEEE TRANSACTIONS ON WIRELESS communications 2024年第8期23卷 9730-9744页

作者： Tang, Xiao Liu, Sicong Du, Xiaojiang Guizani, Mohsen Xiamen Univ Sch Informat Dept Informat & Commun Engn Xiamen 361005 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA Mohamed Bin Zayed Univ Artificial Intelligence Machine Learning Dept Abu Dhabi U Arab Emirates

Massive random access of devices brings great challenge to the management of radio access networks. Most of the time, the access requests in the network are sporadic. Exploiting the bursting nature, sparse active user detection (SAUD) is an efficient enabler towards efficient active user detection. However, the sparsity might be deteriorated in case of high concurrent request periods. To dynamically coordinate the access requests, a reinforcement-learning (RL)-assisted scheme of closed-loop access control utilizing the access class barring (ACB) technique is proposed, where the control policy is determined through continuous interaction between the RL agent and the environment. The proposed RL agent can be deployed at the next generation node base (gNB), supporting rapid switching between heterogeneous vertical applications, such as mMTC and uRLLC services. Moreover, a data-driven scheme of deep-RL-assisted SAUD is proposed to resolve highly complex environments with continuous and high-dimensional state and action spaces, where a replay buffer is applied for automatic large-scale data collection. An Actor-Critic framework is formulated to incorporate the strategy-learning modules into the intelligent control agent. Simulation results show that the proposed schemes can achieve superior performance in both access efficiency and user detection accuracy over the benchmark scheme for different heterogeneous services with massive access requests.

关键词： Access control next generation networking Massive MIMO Wireless communication Vectors Switches Sparse matrices Massive random access active user detection massive MIMO compressed sensing reinforcement learning

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Secrecy Analysis of UAV control Information Transmission via NOMA 25

Secrecy Analysis of UAV Control Information Transmission via...

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IEEE Wireless communications and Networking conference (IEEE WCNC)

作者： Feng, Zhaoxin Lu, Huabing Zhao, Nan Shi, Zhaoyuan Chen, Yunfei Wang, Xianbin Dalian Univ Technol Sch Informat & Commun Engn Dalian 116024 Peoples R China Anqing Normal Univ Key Lab Intelligent Percept & Comp Anhui Prov Anqing 246011 Peoples R China Univ Durham Dept Engn South Rd Durham DH1 3LE England Western Univ Dept Elect & Comp Engn London ON Canada

ISBN: (纸本)9798350303582;9798350303599

Unmanned aerial vehicle (UAV) assisted wireless communication is essential for the next-generation mobile networks. In coping with the increased dynamics in UAV networks, the design of control information transmission is essential, requiring ultra reliability, low latency, and high security. In this paper, considering both the large-scale path loss and the Nakagamim small-scale fading, we investigate the secrecy performance of UAV control information transmission in a NOMA ground-air network with an external flying eavesdropper. A spherical secrecy protection zone is set, and the closed-form expressions for average secure BLER and average achievable secrecy throughput are derived. After that, the asymptotic performance in the high SNR regime is analyzed to get more insights. Ultimately, simulation results verify the accuracy of analysis.

关键词： Non-orthogonal multiple access physical-layer security short-packet communications unmanned aerial vehicle ultra-reliable and low-latency communications

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MEGATRON: Machine Learning in 5G with Analysis of Traffic in Open Radio Access networks

MEGATRON: Machine Learning in 5G with Analysis of Traffic in...

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International conference on Computing, Networking and communications (ICNC)

作者： Belgiovine, Mauro Gu, Jerry Groen, Joshua Sirera, Miquel Demir, Utku Chowdhury, Kaushik Northeastern Univ Inst Wireless Internet Things Boston MA 02115 USA

ISBN: (纸本)9798350371000;9798350370997

With the advent of SG and next-generation cellular networks and the increasing complexity of assigning users traffic types for efficient resource allocation, Open Radio Access networks (O-RAN) offer intelligent virtualized frameworks for optimizing network operations related to supporting diverse types of traffic. In this paper, we utilize the native support for machine learning in O-RAN to develop a transformer-based SG traffic classification system that identifies, with high accuracy, conditions when broadband, machine-to-machine type communication, and ultra-reliable low-latency communication are present. By utilizing distinct temporal slices of O-RAN-defined key performance indicators generated from traffic captures as inputs (as opposed to directly accessing user-plane data) and filtering for non-critical control traffic, we ensure user confidentiality while maintaining a high degree of classification performance. Our transformer model is able to achieve an average offline accuracy of 99%+ for the longest traffic slice length, with the online deployment achieving an average of similar to 90% accuracy across all slice lengths.

关键词： O-RAN 5G Transformers Traffic Classification Network Slicing

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Privacy-Preserving Decentralized Inference With Graph Neural networks in Wireless networks

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IEEE TRANSACTIONS ON WIRELESS communications 2024年第1期23卷 543-558页

作者： Lee, Mengyuan Yu, Guanding Dai, Huaiyu Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

As an efficient neural network model for graph data, graph neural networks (GNNs) recently find successful applications for various wireless optimization problems. Given that the inference stage of GNNs can be naturally implemented in a decentralized manner, GNN is a potential enabler for decentralized control/management in the next-generation wireless communications. Privacy leakage, however, may occur due to the information exchanges among neighbors during decentralized inference with GNNs. To deal with this issue, in this paper, we analyze and enhance the privacy of decentralized inference with GNNs in wireless networks. Specifically, we adopt local differential privacy as the metric, and design novel privacy-preserving signals as well as privacy-guaranteed training algorithms to achieve privacy-preserving inference. We also define the SNR-privacy trade-off function to analyze the performance upper bound of decentralized inference with GNNs in wireless networks. To further enhance the communication and computation efficiency, we adopt the over-the-air computation technique and theoretically demonstrate its advantage in privacy preservation. Through extensive simulations on the synthetic graph data, we validate our theoretical analysis, verify the effectiveness of proposed privacy-preserving wireless signaling and privacy-guaranteed training algorithm, and offer some guidance on practical implementation.

关键词： Artificial intelligence graph neural network decentralized inference differential privacy over-the-air computation

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Integrated Sensing, communications, and Powering for Statistical-QoS Provisioning Over next-generation Massive-MIMO Mobile networks 58

Integrated Sensing, Communications, and Powering for Statist...

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58th Annual conference on Information Sciences and Systems (CISS)

作者： Zhang, Xi Zhu, Qixuan Texas A&M Univ Dept Elect & Comp Engn Networking & Informat Syst Lab College Stn TX 77843 USA

ISBN: (纸本)9798350369298;9798350369304

The integrated sensing and communication (ISAC) has been proposed as a key technique to support the next generation traffic with stringent quality-of-service (QoS) requirements through sensing and communicating using the same radio frequency and hardware. Simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. However, how to integrate ISAC with SWIPT to support the stringent QoS traffic has imposed many new challenges not encountered before. To overcome these challenges, in this paper we propose an integrated sensing, communications, and powering (ISACP) technique for supporting both sensing and communication QoS provisioning while delivering the power over the next-generation wireless networks using massive multiple-input and multiple-output (massive MIMO) communications. First, we develop the system models for the ISACP scheme to simultaneously sense the targeted mobile users (MUs), transmit the information, and deliver the power. Second, we propose a hypothesis testing based scheme to estimate the MU's angle-of-arrival using the sensing signal. Third, we employ the Cram ' er-Rao bound (CRB) to measure the performance of sensing and maximize the energy-efficiency with satisfying requirements of both sensing and communication performances. Finally, we use numerical analyses to validate and evaluate our proposed ISACP scheme.

关键词： next generation wireless networks integrated sensing and communication (ISAC) energy-harvesting ISACP massive MIMO hypothesis testing Cramer-Rao bound (CRB).

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