4.7 Article

Secure Cache-Aided Multi-Relay Networks in the Presence of Multiple Eavesdroppers

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 67, 期 11, 页码 7672-7685

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2019.2935047

关键词

Secure communication; relay selection; cache; secrecy diversity order; cache placement

资金

  1. NSFC [61871139/61871109/61971360, 61501382]
  2. Guangdong Natural Science Funds for Distinguished Young Scholar [2014A030306027]
  3. Innovation Team Project of Guangdong Province University [2016KCXTD017]
  4. Science and Technology Program of Guangzhou [201807010103]
  5. State's Key Project of Research and Development Plan [2017YFE0121300-6]
  6. Sichuan Science and Techology Program [2017HH0035]
  7. Fundamental Research Funds for the Central Universities [2682018CX27]

向作者/读者索取更多资源

In this paper, we investigate the security of a cache-aided multi-relay communication network in the presence of multiple eavesdroppers, where each relay can pre-store a part of the requested files in order to assist secure data transmission from source to destination. If the relays have cached the requested file, then they can directly send it to the destination; otherwise, traditional dual-hop data transmission is used. For both cases, relay selection is performed to assist the secure data transmission. We analyze the network secrecy performance in both scenarios of non-colluding and colluding eavesdroppers, and obtain a closed-form expression for the average secrecy outage probability (SOP), as well as an asymptotic expression for the high mainto-eaves-dropper ratio (MER). Through minimizing the network SOP, we further optimize the cache placement by proposing a stochastic sampling based cache learning (SacLe) strategy, which can be implemented in parallel and thus reduces the implementation latency substantially. Numerical and simulation results are finally presented to verify the proposed analysis, and show that the caching strategy has a significant impact on the network secrecy performance through affecting the caching diversity gain and signal cooperation gain at the relays. The proposed SacLe strategy is shown to be able to achieve the optimal performance obtained by the brute force (BF) algorithm.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Editorial Material Engineering, Electrical & Electronic

Guest Editorial Multi-Tier Computing for Next Generation Wireless Networks-Part I

Kunlun Wang, Yang Yang, Jiong Jin, Tao Zhang, Arumugam Nallanathan, Chintha Tellambura, Bijan Jabbari

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Deep Learning for Super-Resolution Channel Estimation in Reconfigurable Intelligent Surface Aided Systems

Wenhan Shen, Zhijin Qin, Arumugam Nallanathan

Summary: Reconfigurable intelligent surface (RIS) allows the configuration of the propagation environment. Channel estimation is essential in RIS-aided communication systems. In a RIS-aided multi-user MIMO-OFDM system, the channels involved are high-dimensional and have complex statistics. Implementing the optimal MMSE with integration computation is impractical, so a convolutional neural network called SRDnNet is proposed to accurately estimate channels by modeling channel state information (CSI) estimation as an image super-resolution problem.

IEEE TRANSACTIONS ON COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Deep Reinforcement Learning-Based Grant-Free NOMA Optimization for mURLLC

Yan Liu, Yansha Deng, Hui Zhou, Maged Elkashlan, Arumugam Nallanathan

Summary: This study proposes a learning framework for signature-based GF-NOMA in mURLLC service, considering multiple access signature collision, UE detection, and data decoding. The framework aims to maximize the number of successfully served UEs under latency constraint using a real-time DDQN for repetition value configuration and a CMA-DQN for optimizing repetition values and CTU numbers. The results show the superior performance of CMA-DQN over LE-URC in heavy traffic and its ability to dynamically configure mURLLC service in the long term.

IEEE TRANSACTIONS ON COMMUNICATIONS (2023)

Article Chemistry, Analytical

LoRa-Based IoT Network Assessment in Rural and Urban Scenarios

Aikaterini I. Griva, Achilles D. Boursianis, Shaohua Wan, Panagiotis Sarigiannidis, Konstantinos E. Psannis, George Karagiannidis, Sotirios K. Goudos

Summary: The implementation of smart networks has been greatly advanced by the development of IoT, with LoRa being a prominent technology due to its long-distance transmission capabilities with low power consumption. This study simulated various environments to assess network performance based on different factors and parameters. Path loss model, deployment area size, transmission power, spreading factor, number of nodes and gateways, and antenna gain significantly affect the energy consumption and data extraction rate of LoRa networks. The research performed simulations using the FLoRa framework in OMNeT++, investigating rural and urban environments, as well as a parking area model. The results emphasize the importance of optimizing key parameters for the deployment of smart networks.

SENSORS (2023)

Article Engineering, Electrical & Electronic

A Universal Framework of Superimposed RIS-Phase Modulation for MISO Communication

Jiacheng Yao, Jindan Xu, Wei Xu, Chau Yuen, Xiaohu You

Summary: To fully exploit the additional dimension brought by recon-figurable intelligent surface (RIS), information can be modulated upon RIS phases to send extra information with increased communication rate. In this paper, a novel superimposed RIS-phase modulation (SRPM) scheme is proposed, which transfers extra messages by superimposing information-bearing phase offsets to conventionally optimized RIS phases. The theoretical analysis shows that SRPM achieves reliable communication of more bits and has a diversity order of 21.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2023)

Article Engineering, Electrical & Electronic

RIS-Assisted Quasi-Static Broad Coverage for Wideband mmWave Massive MIMO Systems

Muxin He, Jindan Xu, Wei Xu, Hong Shen, Ning Wang, Chunming Zhao

Summary: Reconfigurable intelligent surfaces (RISs) can create favorable wireless environments for mmWave bands by combating attenuation and blockages. This paper presents a quasi-static broad coverage RIS design that reduces overhead by using statistical CSI. A design framework is proposed to synthesize the RIS's power pattern for customized broad coverage requirements. The proposed quasi-static broad coverage method outperforms the design method based on instantaneous CSI even when considering channel estimation overhead. Numerical simulations are conducted to validate the observations.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Task-Oriented Delay-Aware Multi-Tier Computing in Cell-Free Massive MIMO Systems

Kunlun Wang, Dusit Niyato, Wen Chen, Arumugam Nallanathan

Summary: This paper proposes a cell-free massive MIMO-aided computing system by deploying multi-tier computing nodes to improve computation performance. By investigating computational latency and energy consumption, we formulate a total cost minimization problem to design bandwidth and task allocation. Simulation results demonstrate that our proposed task offloading scheme outperforms benchmark schemes.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Channel Access Optimization in Unlicensed Spectrum for Downlink URLLC: Centralized and Federated DRL Approaches

Yan Liu, Hui Zhou, Yansha Deng, Arumugam Nallanathan

Summary: The research on 6G communication is still in its early stage and URLLC remains an important service. However, the severe spectrum scarcity in 6G networks poses challenges to achieving URLLC requirements, especially in NR-U networks where interference and collisions among multiple access technologies occur. This paper presents centralized deep reinforcement learning (CDRL) and federated DRL (FDRL) frameworks to optimize the downlink URLLC transmission in NR-U and WiFi coexistence systems by adjusting energy detection thresholds dynamically. The results show improved reliability in the NR-U system, but the CDRL approach sacrifices the reliability of the WiFi system. To address this, the fairness aspect is considered in the modified CDRL framework to ensure the reliability of both systems.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Performance Analysis of Optical Reflecting Surface-Assisted Optical Space Shift Keying-Based MIMO-FSO System

Narendra Vishwakarma, R. Swaminathan, Panagiotis D. D. Diamantoulakis, George K. K. Karagiannidis

Summary: The paper proposes an optical reflecting surface (ORS)-assisted free space optics (FSO) communication system based on optical space shift keying (OSSK) technique, which can provide improved link reliability and enhanced coverage area. The channel statistics and performance metrics such as average bit error rate (BER) and ergodic capacity are derived. Numerical results are provided to verify the theoretical analysis of the system.

IEEE TRANSACTIONS ON COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

DRL-Driven Dynamic Resource Allocation for Task-Oriented Semantic Communication

Haijun Zhang, Hongyu Wang, Yabo Li, Keping Long, Arumugam Nallanathan

Summary: This paper proposes a dynamic resource allocation scheme for task-oriented semantic communication networks based on deep reinforcement learning, which allows data with richer semantic information to preferentially occupy limited communication resources to improve long-term transmission efficiency.

IEEE TRANSACTIONS ON COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Energy Efficient Cooperative Communications in Aggregated VLC/RF Networks With NOMA

Konstantinos G. Rallis, Vasilis K. Papanikolaou, Panagiotis D. Diamantoulakis, Sotiris A. Tegos, Alexis A. Dowhuszko, Mohammad-Ali Khalighi, George K. Karagiannidis

Summary: This paper investigates an indoor wireless network that aggregates communication resources in visible light and radio-frequency bands. A non-orthogonal multiple access scheme is introduced for visible light communication downlink, enhancing the data rate of cell-edge users through cooperative communications over RF sidelinks. The optimal resource allocation strategy is derived for maximizing energy efficiency. Additionally, a weighted energy efficiency metric is proposed for assessing the performance of the aggregated VLC/RF network.

IEEE TRANSACTIONS ON COMMUNICATIONS (2023)

Article Engineering, Electrical & Electronic

Profit Maximization for Cache-Enabled Vehicular Mobile Edge Computing Networks

Wenqi Zhou, Junjuan Xia, Fasheng Zhou, Lisheng Fan, Xianfu Lei, Arumugam Nallanathan, George K. Karagiannidis

Summary: This paper investigates a multiuser cache-enabled vehicular mobile edge computing (MEC) network, and proposes a solution to the critical challenge of optimizing the system design and performance by maximizing the profit of the edge server (ES) and jointly exploiting caching and computing resources.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2023)

Article Computer Science, Information Systems

Multiplexing eMBB and URLLC in Wireless Powered Communication Networks: A Deep Reinforcement Learning-Based Approach

Xiaotian Jiang, Kai Liang, Xiaoli Chu, Cheng Li, George K. Karagiannidis

Summary: This letter investigates the multiplexing of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services in a wireless powered communication network. The proposed algorithm achieves a higher eMBB sum rate than the existing schemes by using preemptive puncturing to multiplex URLLC traffic onto eMBB transmission and a deep reinforcement learning-based approach to jointly allocate subcarriers, time, and energy.

IEEE WIRELESS COMMUNICATIONS LETTERS (2023)

Article Computer Science, Information Systems

Proactive Scheduling for Zero-Energy Device Networks With Fast Uplink Grant

Nikos A. A. Mitsiou, Sotiris A. A. Tegos, Panagiotis D. D. Diamantoulakis, Panagiotis G. G. Sarigiannidis, George K. K. Karagiannidis

Summary: To address the inefficiency in terms of resource utilization of grant-free (GF) protocols, the fast uplink (FU) grant medium-access protocol has been proposed. In this letter, we design a proactive wireless power transfer (WPT) framework for FU grant zero-energy massive machine-type communication. Specifically, zero-energy devices (ZEDs) first harvest energy during the WPT phase and then transmit data based on the FU grant protocol. Moreover, a multi-arm bandit traffic prediction scheme is adopted. Simulation results show that the proposed scheme outperforms GF access.

IEEE WIRELESS COMMUNICATIONS LETTERS (2023)

Article Computer Science, Theory & Methods

Secrecy Performance Evaluation of Scalable Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach

Xiangjun Ma, Xianfu Lei, Xiangyun Zhou, Xiaohu Tang

Summary: This paper presents the first performance analysis of physical layer downlink secure transmissions in a scalable cell-free massive MIMO (SCF-mMIMO) system. The locations of the access points (APs), user equipments (UEs), and eavesdroppers (Eves) are modeled as independent homogeneous Poisson point processes (HPPPs) using a stochastic geometry approach. Maximum ratio transmission (MRT) and null-space artificial noise are used for sending confidential messages and enhancing secrecy. The analytical characterization of secrecy performance provides insights on design and the benefits of artificial noise insertion.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2023)

暂无数据