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Long-term prediction for hierarchical-B-picture-based coding of video with repeated shots

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Frontiers of information Technology & Electronic Engineering 2018年第3期19卷 459-470页

作者： Xu-guang ZUO Lu YU Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking IPCANInstitute of Information and Communication Engineering Zhejiang University

The latest video coding standard High Efficiency Video Coding （HEVC） can achieve much higher coding efficiency than previous video coding standards. Particularly, by exploiting the hierarchical B-picture prediction structure, temporal redundancy among neighbor frarnes is eliminated remarkably well. In practice, videos available to consumers usually contain many repeated shots, such as TV series, movies, and talk shows. According to our observations, when these videos are encoded by HEVC with the hierarchical B-picture structure, the temporal correlation in each shot is well exploited. However, the long-term correlation between repeated shots has not been used. We propose a long-term prediction （LTP） scheme to use the long-term temporal correlation between correlated shots in a video. The long-term reference （LTR） frames of a source video are chosen by clustering similar shots and extracting the representative frames, and a modified hierarchical B-picture coding structure based on an LTR frame is introduced to support long-term temporal prediction. An adaptive quantization method is further designed for LTR frames to improve the overall video coding efficiency. Experimental results show that up to 22.86% coding gain can be achieved using the new coding scheme.

关键词： High Efficiency Video Coding（HEVC） Long-term temporal correlation Long-term prediction Hierarchical B-picture structure

Deep learning for spectrum sensing

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arXiv 2019年

作者： Gao, Jiabao Yi, Xuemei Zhong, Caijun Chen, Xiaoming Zhang, Zhaoyang College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Hangzhou

In cognitive radio systems, the ability to accurately detect primary user's signal is essential to secondary user in order to utilize idle licensed spectrum. Conventional energy detector is a good choice for blind signal detection, while it suffers from the well-known SNR-wall due to noise uncertainty. In this letter, we firstly propose a deep learning based signal detector which exploits the underlying structural information of the modulated signals, and is shown to achieve the state of the art detection performance, requiring no prior knowledge about channel state information or background noise. In addition, the impacts of modulation scheme and sample length on performance are investigated. Finally, a deep learning based cooperative detection system is proposed, which is shown to provide substantial performance gain over conventional cooperative sensing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel state information

Multi-hop RIS-Empowered Terahertz communications: A DRL-based Hybrid Beamforming Design

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arXiv 2021年

作者： Huang, Chongwen Yang, Zhaohui Alexandropoulos, George C. Xiong, Kai Wei, Li Yuen, Chau Zhang, Zhaoyang Debbah, Mérouane The College of Information Science and Electronic Engineering Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China The ZJU-UIUC Institute Zhejiang University Haining314400 China The Centre for Telecommunications Research Department of Engineering King's College London WC2R 2LS United Kingdom The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimiopolis Ilissia Athens15784 Greece School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The Singapore University of Technology and Design Singapore487372 Singapore CentraleSupélec University Paris-Saclay Gif-sur-Yvette 91192 France The Lagrange Mathematical and Computing Research Center Paris75007 France

Wireless communication in the TeraHertz band (0.1-10 THz) is envisioned as one of the key enabling technologies for the future sixth generation (6G) wireless communication systems scaled up beyond massive multiple input multiple output (Massive-MIMO) technology. However, very high propagation attenuations and molecular absorptions of THz frequencies often limit the signal transmission distance and coverage range. Benefited from the recent breakthrough on the reconfigurable intelligent surfaces (RIS) for realizing smart radio propagation environment, we propose a novel hybrid beamforming scheme for the multi-hop RIS-assisted communication networks to improve the coverage range at THz-band frequencies. Particularly, multiple passive and controllable RISs are deployed to assist the transmissions between the base station (BS) and multiple single-antenna users. We investigate the joint design of digital beamforming matrix at the BS and analog beamforming matrices at the RISs, by leveraging the recent advances in deep reinforcement learning (DRL) to combat the propagation loss. To improve the convergence of the proposed DRL-based algorithm, two algorithms are then designed to initialize the digital beamforming and the analog beamforming matrices utilizing the alternating optimization technique. Simulation results show that our proposed scheme is able to improve 50% more coverage range of THz communications compared with the benchmarks. Furthermore, it is also shown that our proposed DRL-based method is a state-of-the-art method to solve the NP-hard beamforming problem, especially when the signals at RIS-assisted THz communication networks experience multiple hops. Copyright © 2021, The Authors. All rights reserved.

关键词： Beamforming

Corrections to “Coverage Rate Analysis for Integrated Sensing and communication Networks”

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IEEE Journal on Selected Areas in communications 2024年第1期43卷 410-410页

作者： Xu Gan Chongwen Huang Zhaohui Yang Xiaoming Chen Jiguang He Zhaoyang Zhang Chau Yuen Yong Liang Guan Mérouane Debbah College of Information Science and Electronic Engineering Zhejiang University Hangzhou China State Key Laboratory of Integrated Service Networks Xidian University Xi’an China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking (IPCAN) Hangzhou China Technology Innovation Institute Abu Dhabi United Arab Emirates School of Electrical and Electronics Engineering Nanyang Technological University Jurong West Singapore KU 6G Research Center Khalifa University of Science and Technology Abu Dhabi United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette France

Presents corrections to the paper, Coverage Rate Analysis for Integrated Sensing and communication Networks.

关键词： Integrated sensing and communication

Reverberant Field Imaging of a Slope Sea Bottom

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Reverberant Field Imaging of a Slope Sea Bottom

作者： Yonghua Lu Hangfang Zhao Ting Zhang College of Information Science and Electronic Engineering Zhejiang University Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking

Reverberation is the most interference source of active sonar detection, and is closely related to the scattering strength of the sea bottom. To image the reverberant field, a mid-frequency-monostatic system is introduced in this paper. We made a simulation of the reverberant field of a slope sea bottom. Since the bottom reverberation is typically dominated by the incoherent intensity, the mean energy of the reverberant field over the resolution footprint is a integration about the variance of the scattered field. To verify our theory, in the Imaging Experiment at Qiandao Lake, we used a ten-element vertical source array(VLA),which can be steered to the angles where we need to ensonify, and a 96-element horizontal line array(HLA) to receive the *** adjusting the steering angle, multipath effect can be decreased to a great extent. By mapping the reverberation of the sea bottom, we can easily find out the location of the slope or other geological features by contrast to the reverberation of a flat seafloor. And we also discussed the performance of the temporal resolution of the system by studying the variance of the temporal reverberant field.

关键词： Monostatic System Bottom Scattering Reverberant Field Imaging Varied Emission Angle

Spectral efficiency of multipair massive MIMO two-way relaying with imperfect CSI

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Spectral efficiency of multipair massive MIMO two-way relayi...

作者： Kong, Chuili Zhong, Caijun Matthaiou, Michail Bjornson, Emil Zhang, Zhaoyang Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Institute of Information and Communication Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Integrated Services Networks Xidian University Xi'an710126 China Institute of Electronics Communications and Information Technology Queen's University Belfast BelfastBT39DT United Kingdom Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden

We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas M becomes sufficiently large. In addition, we study how the transmit power reduces with M to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to 1/Mα, 1/Mβ, and 1/Mγ for certain combinations of α, β, and γ, respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE. © 2019 IEEE.

关键词： Spectrum efficiency

Intelligent spectrum learning for wireless networks with reconfigurable intelligent surfaces

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arXiv 2021年

作者： Yang, Bo Cao, Xuelin Huang, Chongwen Yuen, Chau Qian, Lijun Renzo, Marco Di Engineering Product Development Pillar Singapore University of Technology and Design Singapore487372 Singapore Zhejiang Provincial Key Lab of information processing communication and networking Zhejiang University No.38 Zheda Road Hangzhou310007 China Department of Electrical and Computer Engineering CREDIT Center Prairie View A&M University Texas A&M University System Prairie ViewTX77446 United States Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France

Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired signals through appropriate phase shifts. However, the intended signals that impinge upon an RIS are often mixed with interfering signals, which are usually dynamic and unknown. In particular, the received signal-to-interference-plus-noise ratio (SINR) may be degraded by the signals reflected from the RISs that originate from non-intended users. To tackle this issue, we introduce the concept of intelligent spectrum learning (ISL), which uses an appropriately trained convolutional neural network (CNN) at the RIS controller to help the RISs infer the interfering signals directly from the incident signals. By capitalizing on the ISL, a distributed control algorithm is proposed to maximize the received SINR by dynamically configuring the active/inactive binary status of the RIS elements. Simulation results validate the performance improvement offered by deep learning and demonstrate the superiority of the proposed ISL-aided approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

AI-assisted MAC for reconfigurable intelligent surface-aided wireless networks: Challenges and opportunities

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arXiv 2021年

作者： Cao, Xuelin Yang, Bo Huang, Chongwen Yuen, Chau Renzo, Marco Di Han, Zhu Niyato, Dusit Poor, H. Vincent Hanzo, Lajos Engineering Product Development Pillar Singapore University of Technology and Design Singapore Singapore Zhejiang Provincial Key Lab of information processing Communication and networking Zhejiang University China Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France Department of Electrical and Computer Engineering University of Houston United States School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Department of Electrical Engineering Princeton University United States School of Electronics and Computer Science University of Southampton United Kingdom

Recently, significant research attention has been devoted to the study of reconfigurable intelligent surfaces (RISs), which are capable of reconfiguring the wireless propagation environment by exploiting the unique properties of metamaterials-based integrated large arrays of inexpensive antennas. Existing research demonstrates that RISs significantly improve the physical layer performance, including the wireless coverage, achievable data rate and energy efficiency. However, the medium access control (MAC) of multiple users accessing an RIS-enabled channel is still in its infancy, while many open issues remain to be addressed. In this article, we present four typical RIS-aided multi-user scenarios with special emphasis on the MAC schemes. We then propose and elaborate upon centralized, distributed and hybrid artificial-intelligence (AI)-assisted MAC architectures in RIS-aided multi-user communications systems. Finally, we discuss some challenges, perspectives and potential applications of RISs as they are related to MAC design. Copyright © 2021, The Authors. All rights reserved.

关键词： Medium access control