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Transmission Energy Allocation for Over-the-Air Computation with Energy Harvesting

Journal of Communications and Information Networks 2024年第2期9卷 126-136页

作者： Siyao Zhang Zixiang Ren Xinmin Li Yin Long Jie Xu Shuguang Cui School of Computer Science and Technology Southwest University of Science and TechnologyMianyang 621010China shenzhen Future Network of Intelligence Institute(fnii-shenzhen) The Chinese University of Hong KongShenzhenGuangdong 518172China School of Information Science and Technology University of Science and Technology of ChinaHefei 230027China fnii-shenzhen The Chinese University of Hong KongShenzhenGuangdong 518172China College of Computer Science Chengdu UniversityChengdu 610100China School of Science and Engineering FNii-Shenzhenand Guangdong Provincial Key Laboratory of Future Networks of IntelligenceThe Chinese University of Hong KongShenzhenGuangdong 518172China

Over-the-air computation(AirComp)has recently emerged as a promising multiple-access technique for fast wireless data aggregation(WDA)from distributed wireless devices(WDs). This paper investigates an energy harvesting (EH) AirComp system, in which multiple EH-powered single-antenna WDs simultaneously send wireless signals to a single-antenna access point (AP) with conventional energy supply for WDA via AirComp. Under this setup, we minimize the average computation mean square error(MSE)over a particular time period, by jointly optimizing the transmit energy allocation at the WDs and the AirComp denoising factors at the AP over time, subject to the energy causality constraints at individual WDs. First, we consider the offline scenario by assuming that the energy state information(ESI)and channel state information (CSI) are non-causally known at the beginning of the period, in which the formulated average MSE minimization corresponds to a non-convex optimization problem. We present a high-quality converged solution by using the techniques of alternating optimization and convex optimization. It is shown that for each WD,if the EH rate is sufficiently high,then the channel inversion power allocation is adopted;while if the EH rate is low, then all the harvested energy should be used up for transmission with proper energy allocation over time. Next, we consider the online scenario with causal ESI and CSI,in which the MSE minimization becomes a stochastic optimization *** this scenario, we present an offline-inspired online algorithm to obtain efficient online energy allocation designs by utilizing the obtained offline solutions. Finally,numerical results show that the proposed designs significantly outperform two benchmark schemes with power-halving and full-power transmission,respectively.

关键词： over-the-air computation(AirComp) power allocation energy harvesting(EH) optimization

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Air interface design for edge intelligence

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The Journal of China Universities of Posts and Telecommunications 2022年第1期29卷 13-26,124页

作者： Zhang Zezhong Chen Mingzhe Xu Jie Cui Shuguang Future Network of Intelligence Institute(fnii) The Chinese University of Hong Kong(Shenzhen)Shenzhen 518172China Department of Electrical Engineering Princeton UniversityPrincetonNJ 08544USA

Recent breakthroughs in artificial intelligence(AI) give rise to a plethora of intelligent applications and services based on machine learning algorithms such as deep neural networks(DNNs). With the proliferation of Internet of things(IoT) and mobile edge computing, these applications are being pushed to the network edge, thus enabling a new paradigm termed as edge intelligence. This provokes the demand for decentralized implementation of learning algorithms over edge networks to distill the intelligence from distributed data, and also calls for new communication-efficient designs in air interfaces to improve the privacy by avoiding raw data exchange. This paper provides a comprehensive overview on edge intelligence, by particularly focusing on two paradigms named edge learning and edge inference, as well as the corresponding communication-efficient solutions for their implementations in wireless systems. Several insightful theoretical results and design guidelines are also provided.

关键词： artificial intelligence air interface edge intelligence edge inference federated learning

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Online search for UAV relay placement for free-space optical communication under shadowing

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Intelligent and Converged Networks 2023年第1期4卷 28-40页

作者： Yuanshuai Zheng Yinjun Wang Junting Chen School of Science and Engineering and the Future Network of Intelligence Institute(fnii) The Chinese University of Hong KongShenzhen 518172China

Unmanned aerial vehicle(UAV)relaying is promising to overcome the challenge of signal blockage in free-space optical(FSO)communications for users in dense urban *** works on UAV relay placement are mostly based on simplified line-of-sight(LOS)channel models or probabilistic channel models,and thus fail to capture the actual LOS status of the optical communication *** contrast,this paper studies three-dimensional(3D)online placement for a UAV to construct relay links to two ground users in deep shadow with LOS *** analyzing the properties of the UAV relay placement problem,it is found that searching on a plane that approximates the equipotential surface can achieve a good performance and complexity trade-off for a good placement of the UAV relay in *** on these insights,a two-stage online search algorithm on an equipotential plane(TOSEP)is developed for a special case where the equipotential surface turns out to be an equipotential *** the general case,a strategy called gradient projected online search algorithm on an approximated equipotential plane(GOSAEP)is developed,which approximates the equipotential surface with a perpendicular plane using the gradient projection *** experiments are conducted over a real-world city topology,and it is shown that the GOSAEP achieves over 95%of the performance of the exhaustive 3D search scheme within a 300-m search length.

关键词： free-space optical communication relay communication unmanned aerial vehicle(UAV) trajectory design capacity maximization

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Channel Knowledge Map(CKM)-Assisted Multi-UAV Wireless Network:CKM Construction and UAV Placement

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Journal of Communications and Information Networks 2023年第3期8卷 256-270页

作者： Haoyun Li Peiming Li Gaoyuan Cheng Jie Xu Junting Chen Yong Zeng School of Science and Engineering and the Future Network of Intelligence Institute(FNii)the Chinese University of Hong KongShenzhenShenzhen 518172China National Mobile Communications Research Laboratory and Frontiers Science Center for Mobile Information Communication and Security the Southeast UniversityNanjing 210096the Purple Mountain LaboratoriesNanjing 211111China

Channel knowledge map(CKM)has recently emerged as a viable new solution to facilitate the placement and trajectory optimization for unmanned aerial vehicle(UAV)communications,by exploiting the siteand location-specific radio propagation *** paper investigates a CKM-assisted multi-UAV wireless network,by focusing on the construction and utilization of CKMs for multi-UAV placement ***,we consider the CKM construction problem when data measurements for only a limited number of points are *** this end,we exploit a data-driven interpolation technique,namely the Kriging method,to construct CKMs to characterize the signal propagation ***,we study the multi-UAV placement optimization problem by utilizing the constructed CKMs,in which the multiple UAVs aim to optimize their placement locations to maximize the weighted sum rate with their respectively associated ground base stations(GBSs).However,the weighted sum rate function based on the CKMs is generally non-differentiable,which renders the conventional optimization techniques relying on function derivatives *** tackle this issue,we propose a novel iterative algorithm based on derivative-free optimization,in which a series of quadratic functions are iteratively constructed to approximate the objective function under a set of interpolation conditions,and accordingly,the UAVs’placement locations are updated by maximizing the approximate function subject to a trust region ***,numerical results are presented to validate the performance of the proposed *** is shown that the Kriging method can construct accurate CKMs for ***,the proposed derivative-free placement optimization design based on the Kriging-constructed CKMs achieves a weighted sum rate that is close to the optimal exhaustive search design based on ground-truth CKMs,but with much lower implementation *** addition,the proposed design is shown to significant

关键词： UAV communications CKM CKM construction UAV placement derivative-free optimization

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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Science China(Information Sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG shenzhen Research Institute of Big Data Future Network of Intelligence Institute (fnii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey

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China Communications 2022年第1期19卷 218-237页

作者： Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui School of Science and Engineering The Chinese University of Hong KongShenzhen 518172China Future Network of Intelligence Institute(fnii) The Chinese University of Hong KongShenzhen 518172China School of Information Science and Technology University of Science and Technology of ChinaHefei 230026China Research Institute China United Network Communications CorporationBeijing 100048China Alibaba Group Hangzhou 310052China

Data-driven paradigms are well-known and salient demands of future wireless communication. Empowered by big data and machine learning techniques,next-generation data-driven communication systems will be intelligent with unique characteristics of expressiveness, scalability, interpretability, and uncertainty awareness, which can confidently involve diversified latent demands and personalized services in the foreseeable future. In this paper, we review a promising family of nonparametric Bayesian machine learning models,i.e., Gaussian processes(GPs), and their applications in wireless communication. Since GP models demonstrate outstanding expressive and interpretable learning ability with uncertainty, they are particularly suitable for wireless communication. Moreover, they provide a natural framework for collaborating data and empirical models(DEM). Specifically, we first envision three-level motivations of data-driven wireless communication using GP models. Then, we present the background of the GPs in terms of covariance structure and model inference. The expressiveness of the GP model using various interpretable kernels, including stationary, non-stationary, deep and multi-task kernels,is showcased. Furthermore, we review the distributed GP models with promising scalability, which is suitable for applications in wireless networks with a large number of distributed edge devices. Finally, we list representative solutions and promising techniques that adopt GP models in various wireless communication applications.

关键词： wireless communication Gaussian process machine learning kernel interpretability uncertainty

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Spectrum Usage Anomaly Detection from Sub-Sampled Data Stream via Deep Neural Network

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Journal of Communications and Information Networks 2023年第1期8卷 13-23页

作者： Han Zhang Jian Yang Junting Chen Yue Gao Institute for Communication Systems the University of SurreyGuildford GU27XHUK Mobile Communications Innovation Center China Academy of Information and Communications TechnologyBeijing 100191China Future Network Intelligence Institute(fnii)and School of Science and Engineering the Chinese University of Hong KongShenzhen 518172China School of Computer Science Fudan UniversityShanghai 200433China.Institute for Communication Systemsthe University of SurreyGuildford GU27XHUK

Anomaly detection is an essential part of any practical system in order to remedy any malfunction and accident early to create a secure and robust *** users and malfunctioning cognitive radio(CR)devices may cause severe interference to legitimate ***,there are no effective methods to detect spontaneous and irregular anomaly behaviors in sub-sampling data stream from wideband compressive spectrum sensing as an important function of a CR *** this article,to detect anomaly utilization of spectrum from sub-sampled data stream,a multiple layer perceptron/feed-forward neural network(FFNN)based solution is *** proposed solution would learn the pattern of legitimate and anomalous usages autonomously without expert's *** proposed neural network(NN)framework has also shown benefits such as more than 80%faster detection speed and lower detection error rate.

关键词： compressive sensing(CS) machine learning(ML) multicoset sampling anomaly detection

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A survey of prototype and experiment for UAV communications

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Science China(Information Sciences) 2021年第4期64卷 5-25页

作者： Qingheng SONG Yong ZENG Jie XU Shi JIN College of Electrical and Information Engineeing Huaihua University Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province National Mobile Communications Research Laboratory Southeast University Future Network of Intelligence Institute (fnii) and School of Science and Engineering The Chinese University of Hong Kong (Shenzhen)

Unmanned aerial vehicle(UAV) communications have attracted significant attention from both academia and industry. To facilitate the large-scale usage of UAVs for various applications in practice,we provide a comprehensive survey on the prototype and experiment for UAV communications. To this end, we first provide an overview on the general architecture of the prototype and experiment for UAV communications, and then present experimental verification for air-to-ground channel models and UAV energy consumption models. Next, we discuss measurement experiments on two promising paradigms of UAV communications, namely cellular-connected UAVs and UAV-enabled aerial communication platforms. For the former, we focus on the feasibility study and address the interference mitigation issue. For UAV-enabled aerial communication platforms, we present three scenarios, namely UAV-enabled aerial base stations, UAVenabled aerial relays and UAV-enabled aerial data collection/dissemination. Finally, we point out some promising future directions for prototype and experimental measurements of UAV communications.

关键词： UAV communications prototype development channel model energy efficiency UAV-enabled communications platforms cellular-connected UAVs

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