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Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart

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Journal of communications and Information Networks 2019年第2期4卷 40-50页

作者： Ying-Chang Liang Ruizhe Long Qianqian Zhang Jie Chen Hei Victor Cheng Huayan Guo Center for Intelligent Networking and Communications(CINC) University of Electronic Science and Technology of China(UESTC)Chengdu 611731China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China The Edward S.Rogers Sr.Department of Electrical and Computer Engineering University of TorontoToronto ON M5S 3G4Canada

Large intelligent surface/antennas(LISA),a two-dimensional artificial structure with a large number of reflective-surface/antenna elements,is a promising reflective radio technology to construct programmable wireless environments in a smart ***,each element of the LISA adjusts the reflection of the incident electromagnetic waves with unnatural properties,such as negative refraction,perfect absorption,and anomalous reflection,thus the wireless environments can be software-defined according to various design *** this paper,we introduce the reflective radio basics,including backscattering principles,backscatter communication,reflective relay,the fundamentals and implementations of LISA ***,we present an overview of the state-of-the-art research on emerging applications of LISA-aided wireless ***,the limitations,challenges,and open issues associated with LISA for future wireless applications are discussed.

关键词： reflective radio technology backscatter communication ambient backscatter communication LISA,reflective relay intelligent reflective surface symbiotic radio

Closed-loop adaptation for weakly-supervised semantic segmentation

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arXiv 2019年

作者： Zhang, Zhengqiang Yu, Shujian Yin, Shi Peng, Qinmu You, Xinge School of Electronic Information and Communications Huazhong University of Science and Technology Department of Electrical and Computer Engineering University of Florida

Weakly-supervised semantic segmentation aims to assign each pixel a semantic category under weak supervisions, such as image-level tags. Most of existing weakly-supervised semantic seg-mentation methods do not use any feedback from segmentation output and can be considered as open-loop systems. They are prone to accumulated errors because of the static seeds and the sensitive structure information. In this paper, we propose a generic self-adaptation mecha-nism for existing weakly-supervised semantic segmentation methods by introducing two feedback chains, thus constituting a closed-loop system. Specifically, the first chain iteratively produces dynamic seeds by incorporating cross-image structure information, whereas the second chain fur-ther expands seed regions by a customized random walk process to reconcile inner-image structure information characterized by superpixels. Experiments on PASCAL VOC 2012 suggest that our network outperforms state-of-the-art methods with significantly less computational and memory burden. Copyright © 2019, The Authors. All rights reserved.

关键词： computer vision

Pinching-Antenna Systems (PASS)-enabled Secure Wireless communications

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arXiv 2025年

作者： Zhu, Guangyu Mu, Xidong Guo, Li Xu, Shibiao Liu, Yuanwei Al-Dhahir, Naofal Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing100876 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China National Engineering Research Center for Mobile Internet Security Technology Beijing University of Posts and Telecommunications Beijing100876 China Queen’s University Belfast BelfastBT3 9DT United Kingdom Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

A novel pinching-antenna systems (PASS)-enabled secure wireless communication framework is proposed. By dynamically adjusting the positions of dielectric particles, namely pinching antennas (PAs), along the waveguides, PASS introduces a novel concept of pinching beamforming to enhance the performance of physical layer security. A fundamental PASS-enabled secure communication system is considered with one legitimate user and one eavesdropper. Both single-waveguide and multiple-waveguide scenarios are studied. 1) For the single-waveguide scenario, the secrecy rate (SR) maximization is formulated to optimize the pinching beamforming. A PA-wise successive tuning (PAST) algorithm is proposed, which ensures constructive signal superposition at the legitimate user while inducing a destructive legitimate signal at the eavesdropper. 2) For the multiple-waveguide scenario, artificial noise (AN) is employed to further improve secrecy performance. A pair of practical transmission architectures are developed: waveguide division (WD) and waveguide multiplexing (WM). The key difference lies in whether each waveguide carries a single type of signal or a mixture of signals with baseband beamforming. For the SR maximization problem under the WD case, a two-stage algorithm is developed, where the pinching beamforming is designed with the PAST algorithm and the baseband power allocation among AN and legitimate signals is solved using successive convex approximation (SCA). For the WM case, an alternating optimization algorithm is developed, where the baseband beamforming is optimized with SCA and the pinching beamforming is designed employing particle swarm optimization. Numerical results demonstrate that i) PASS can significantly improve the secrecy performance over conventional antenna systems in both scenarios;ii) the proposed PAST algorithm for the single-waveguide scenario is efficient, especially when the number of PAs is even or large;iii) WM provides higher and more stable perfo

关键词： Particle swarm optimization (PSO)

Capacity of Wideband Multipath Fading Networks with Physically Degraded Broadcast

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Capacity of Wideband Multipath Fading Networks with Physical...

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Diana C. González Salman Salamatian Muriel Médard Michel Daoud Yacoub Massachusetts Institute of Technology Research Laboratory of Electronics Department of Communications University of Campinas School of Electrical and Computer Engineering

In this work we investigate the capacity of multilayer relaying networks operating over multipath fading channels under a non-coherent wideband regime and physically degraded broadcast stages. First, based on hyper-graph models and network equivalence techniques, we derive an upper bound on the network capacity. Then, by considering a peaky, frequency-shift keying signaling scheme, we establish a set of point-to-point achievable rates for each communication link in the network. Finally, by capitalizing on this set of rates we devise an achievable transmission scheme for the entire network via network coding. Remarkably, it turns out that this achievable rate for the network coincides with its upper bound capacity. In other words, these results give ultimately the capacity of the investigated network.

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MIMO Beamforming Schemes for Hybrid SIC FD Radios with Imperfect Hardware and CSI

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MIMO Beamforming Schemes for Hybrid SIC FD Radios with Imper...

作者： Iimori, Hiroki De Abreu, Giuseppe Thadeu Freitas Alexandropoulos, George C. University of Electro-Communications Tokyo182-8585 Japan Department of Computer Science and Electrical Engineering Focus Area Mobility Jacobs University Bremen Campus Ring 1 Bremen28759 Germany Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece

We study a multiple-input multiple-output (MIMO) full-duplex (FD) radio system, aiming to increase the feasibility of this technology in bi-directional communications. In particular, we consider that the FD radios are equipped with the State-of-the-Art (SotA) hybrid SI cancellation (SIC) capabilities, but must cope with hardware (HW) and channel state information (CSI) imperfections, contributing four new MIMO beamforming (BF) schemes for such systems. The first is a transmit (TX) beamforming scheme designed via a Fractional Programming (FP) approach, matched with a minimum mean square error (MMSE) beamformer at the receiver. In this benchmark, the FP-based method, the signal to interference-plus-noise ratio (SINR) constraints are relaxed via the quadratic transform (QT), which allows for the SINR-constrained TX-power minimization problem to be solved using interior point methods. Motivated by the high complexity of the latter, three low-complexity alternatives are then derived, in which power minimization is performed via the Perron-Frobenius (PF) approach, while the TX-BF vectors are obtained, respectively, via direct Gradient Projection (GP), QT-relaxation, and via a Double Rayleigh Quotient (DRQ) reformulation of the original optimization problem. The simulation results confirm the significant gains achieved by all four schemes over the SotA, revealing the GP and DRQ as the overall best alternatives depending on power limitation, and HW/CSI qualities. © 2002-2012 IEEE.

关键词： Channel state information

Deep neural network based active user detection for grant-free NOMA systems

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arXiv 2019年

作者： Kim, Wonjun Ahn, Yongjun Shim, Byonghyo Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

As a means to support the access of massive machine-type communication devices, grant-free access and non-orthogonal multiple access (NOMA) have received great deal of attention in recent years. In the grant-free transmission, each device transmits information without the granting process so that the basestation needs to identify the active devices among all potential devices. This process, called an active user detection (AUD), is a challenging problem in the NOMA-based systems since it is difficult to identify active devices from the superimposed received signal. An aim of this paper is to put forth a new type of AUD based on deep neural network (DNN). By applying the training data in the properly designed DNN, the proposed AUD scheme learns the nonlinear mapping between the received NOMA signal and indices of active devices. As a result, the trained DNN can handle the whole AUD process, achieving an accurate detection of the active users. Numerical results demonstrate that the proposed AUD scheme outperforms the conventional approaches in both AUD success probability and computational complexity. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

Applications of Raman Spectroscopy in Clinical Medicine

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arXiv 2023年

作者： Qi, Yaping Chen, Esther Xinyi Hu, Dan Yang, Ying Wu, Zhenping Zheng, Ming Sadi, Mohammad A. Jiang, Yucheng Zhang, Kang Chen, Zi Chen, Yong P. Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology Av. Wai Long China Tohoku University Sendai980-8577 Japan Faculty of Medicine Macau University of Science and Technology Av. Wai Long China State Key Laboratory of Information Photonics and Optical Communications School of Science Beijing University of Posts and Telecommunications Beijing100876 China School of Materials Science and Physics China University of Mining and Technology Xuzhou221116 China Department of Physics and Astronomy Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Physical Science and Technology Suzhou University of Science and Technology Jiangsu Suzhou215009 China Division of Thoracic Surgery Brigham and Women's Hospital Harvard Medical School 75 Francis Street BostonMA02115 United States Institute of Physics and Astronomy Villum Center for Hybrid Quantum Materials and Devices Aarhus University AarhusC 8000 Denmark

Raman spectroscopy provides spectral information related to the specific molecular structures of substances and has been well established as a powerful tool for studying biological tissues and diagnosing diseases. This article reviews recent advances in Raman spectroscopy and its applications in diagnosing various critical diseases, including cancers, infections, and neurodegenerative diseases, and in predicting surgical outcomes. These advances are explored through discussion of state-of-the-art forms of Raman spectroscopy, such as surface-enhanced Raman spectroscopy, resonance Raman spectroscopy, and tip-enhanced Raman spectroscopy employed in biomedical sciences. We discuss biomedical applications, including various aspects and methods of ex vivo and in vivo medical diagnosis, sample collection, data processing, and achievements in realizing the correlation between Raman spectra and biochemical information in certain diseases. Finally, we present the limitations of the current study and provide perspectives for future research. © 2023, CC BY.

关键词： COVID-19

UAV-assisted intelligent reflecting surface symbiotic radio system

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arXiv 2020年

作者： Hua, Meng Yang, Luxi Wu, Qingqing Pan, Cunhua Li, Chunguo Swindlehurst, A. Lee School of Information Science and Engineering Southeast University Nanjing210096 China State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering University of Macau Macao999078 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Center for Pervasive Communications and Computing University of California at Irvine IrvineCA92697 United States

This paper investigates a symbiotic unmanned aerial vehicle (UAV)-assisted intelligent reflecting surface (IRS) radio system, where the UAV is leveraged to help the IRS reflect its own signals to the base station, and meanwhile enhance the UAV transmission by passive beamforming at the IRS. First, we consider the weighted sum-rate maximization problem among all IRSs by jointly optimizing the UAV trajectory, IRS phase shift matrix, and IRS scheduling, subject to the minimum primary rate requirements. To tackle this complicated problem, a relaxation-based algorithm is proposed. We prove that the converged relaxation scheduling variables are binary, which means that no reconstruct strategy is needed, and thus the UAV rate constraints are automatically satisfied. Second, we consider the problem of maximizing the minimum rate of the IRSs. We find that the relaxation-based method cannot solve this max-min problem since the minimum primary rate requirements may not be satisfied by the binary reconstruction operation. To address this issue, we first transform the binary constraints into a series of equivalent equality constraints. Then, a penalty-based algorithm is proposed to obtain a suboptimal solution. Numerical results are provided to evaluate the performance of the proposed designs under different setups, as compared with benchmarks. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

An Upper Bound on the Capacity of the DNA Storage Channel

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An Upper Bound on the Capacity of the DNA Storage Channel

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Andreas Lenz Paul H. Siegel Antonia Wachter-Zeh Eitan Yaakobi Institute for Communications Engineering Technical University of Munich Germany Department of Electrical and Computer Engineering CMRR University of California San Diego California Computer Science Department Technion – Israel Institute of Technology Haifa Israel

Paved by recent advances in sequencing and synthesis technologies, DNA has evolved to a competitive medium for long-term data storage. In this paper we conduct an information theoretic study of the storage channel-the entity that formulates the relation between stored and sequenced strands. In particular, we derive an upper bound on the Shannon capacity of the channel. In our channel model, we incorporate the main attributes that characterize DNA-based data storage. That is, information is synthesized on many short DNA strands, and each strand is copied many times. Due to the storage and sequencing methods, the receiver draws strands from the original sequences in an uncontrollable manner, where it is possible that copies of the same sequence are drawn multiple times. Additionally, due to imperfections, the obtained strands can be perturbed by errors. We show that for a large range of parameters, the channel decomposes into sub-channels from each input sequence to multiple output sequences, so-called clusters. The cluster sizes hereby follow a Poisson distribution. Furthermore, the ordering of sub-channels is unknown to the receiver. Our results can be used to guide future experiments for DNA-based data storage by giving an upper bound on the achievable rate of any error-correcting code. We further give a detailed discussion and intuitive interpretation of the channel that provide insights about the nature of the channel and can inspire new ideas for error-correcting codes and decoding methods.

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