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The State of AI-Empowered Backscatter Communications: A Comprehensive Survey

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TechRxiv

TechRxiv 2023年

作者： Ahmed, Manzoor Hussain, Touseef Ali, Khurshed Mirza, Muhammad Ayzed Khan, Wali Ullah Ihsan, Asim Xu, Fang Han, Zhu The School of Computer and Information Science Institute for AI Industrial Technology Research Hubei Engineering University Xiaogan City432000 China The with College of Computer Science and Technology Qingdao University Qingdao266071 China The DTU Compute Technical University of Denmark Denmark The BUPT-QMUL EM Theory and Application International Research Lab Beijing University of Posts and Telecommunications Beijing100876 China University of Luxembourg Luxembourg City1855 Luxembourg The School of Computer Science and Electronic Engineering Bangor University BangorLL57 1UT United Kingdom The University of Houston TX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of

The Internet of Things (IoT) is undergoing significant advancements, driven by the emergence of Backscatter Communication (BC) and Artificial Intelligence (AI). BC is an energy-saving and cost-effective communication method where passive backscatter devices communicate by modulating ambient Radio-Frequency (RF) carriers. AI has the potential to transform our way of communicating and interacting and represents a powerful tool for enabling the next generation of IoT devices and networks. By integrating AI with BC, we can create new opportunities for energy-efficient and low-cost communication and open the door to a range of innovative applications that were previously not possible. This paper brings these two technologies together to investigate the current state of AI-powered BC. We begin with an introduction to BC and an overview of the AI algorithms employed in BC. Then, we delve into the recent advances in AI-based BC, covering key areas such as backscatter signal detection, channel estimation, and jammer control to ensure security, mitigate interference, and improve throughput and latency. We also explore the exciting frontiers of AI in BC using B5G/6G technologies, including backscatter-assisted relay and cognitive communication networks, backscatter-assisted MEC networks, and BC with RIS, UAV, and vehicular networks. Finally, we highlight the challenges and present new research opportunities in AI-powered BC. This survey provides a comprehensive overview of the potential of AI-powered BC and its insightful impact on the future of IoT. © 2023, CC BY.

关键词： Backscattering

Literature review: Virtual reality anatomy learning using selective visual attention method

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AIP Conference Proceedings 2023年第1期2654卷

作者： Denny Primanda Adhistya Erna Permanasari Lukito Edi Nugroho Junaedy Yunus 1Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia. 2Department of Anatomy Universitas Gadjah Mada Yogyakarta Indonesia.

Anatomy study in medical education has been considered as a fundamental foundation. The use of cadavers in the study of anatomy is regarded as the gold standard, but in the course of its use, the use of cadavers in modern medical education has become irrelevant due to the consideration of several factors. Thus, the use of cadavers in learning anatomy has decreased in quantity. Of course, this dramatically affects the quality of medical education. This condition has resulted in several countries implementing anatomy learning using the VR system. This study aims to reveal what can be maximized to improve VR systems’ experience in anatomy learning. We carried out a literature review by collecting several papers relevant to the topic of discussion. The results of this study are in the form of research gaps that will be used to conduct further research.

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Joint Program Partitioning and Resource Allocation for Completion Time Minimization in Multi-MEC Systems

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arXiv 2022年

作者： Yi, Taizhou Zhang, Guopeng Wang, Kezhi Yang, Kun School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China Department of Computer and Information Science Northumbria University NewcastleNE2 1XE United Kingdom Zhongshan528400 China Chengdu611731 China School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom

This paper considers a practical mobile edge computing (MEC) system, where edge server does not preinstall the program required to perform user offloaded computing tasks. A partial program offloading (PPO) scheme is proposed, which can divide a user program into two parts, where the first part is executed by the user itself and the second part is transferred to an edge server for remote execution. However, the execution of the latter part requires the results of the previous part (called intermediate result) as the input. We aim to minimize the overall time consumption of a multi-server MEC system to complete all user offloaded tasks. It is modeled as a mixed integer nonlinear programming (MINLP) problem which considers user-and-server association, program partitioning, and communication resource allocation in a joint manner. An effective algorithm is developed to solve the problem by exploiting its structural features. First, the task completion time of a single server is minimized given the computing workload and available resource. Then, the working time of the edge servers are balanced by updating user-and-server association and communication resource allocation. Numerical results show that significant performance improvement can be achieved by the proposed scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Mobile edge computing

Massive Unsourced Random Access: Exploiting Angular Domain Sparsity

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arXiv 2022年

作者： Xie, Xinyu Wu, Yongpeng An, Jianping Gao, Junyuan Zhang, Wenjun Xing, Chengwen Wong, Kai-Kit Xiao, Chengshan Department of Electronic Engineering Shanghai Jiao Tong University Minhang200240 China School of Information and Electronics Beijing Institute of Technology Beijing100081 China Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom Department of Electrical and Computer Engineering Lehigh University BethlehemPA18015 United States

This paper investigates the unsourced random access (URA) scheme to accommodate numerous machine-type users communicating to a base station equipped with multiple antennas. Existing works adopt a slotted transmission strategy to reduce system complexity;they operate under the framework of coupled compressed sensing (CCS) which concatenates an outer tree code to an inner compressed sensing code for slot-wise message stitching. We suggest that by exploiting the MIMO channel information in the angular domain, redundancies required by the tree encoder/decoder in CCS can be removed to improve spectral efficiency, thereby an uncoupled transmission protocol is devised. To perform activity detection and channel estimation, we propose an expectation-maximization-aided generalized approximate message passing algorithm with a Markov random field support structure, which captures the inherent clustered sparsity structure of the angular domain channel. Then, message reconstruction in the form of a clustering decoder is performed by recognizing slot-distributed channels of each active user based on similarity. We put forward the slot-balanced K-means algorithm as the kernel of the clustering decoder, resolving constraints and collisions specific to the application scene. Extensive simulations reveal that the proposed scheme achieves a better error performance at high spectral efficiency compared to the CCS-based URA schemes. © 2022, CC BY.

关键词： Channel estimation

Estimation of Correlation Matrices from Limited time series Data using Machine Learning

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arXiv 2022年

作者： Easaw, Nikhil Lee, Woo Seok Lohiya, Prashant Singh Jalan, Sarika Pradhan, Priodyuti Complex Systems Lab Department of Physics Indian Institute of Technology Indore Khandwa Road Indore Simrol453552 India Daejeon34126 Korea Republic of 1ST Biotherapeutics Inc. Seongnam13493 Korea Republic of Department of Computer Science and Engineering Indian Institute of Information Technology Karnataka Raichur584135 India

Correlation matrices contain a wide variety of spatio-temporal information about a dynamical system. Predicting correlation matrices from partial time series information of a few nodes characterizes the spatio-temporal dynamics of the entire underlying system. This information can help to predict the underlying network structure, e.g., inferring neuronal connections from spiking data, deducing causal dependencies between genes from expression data, and discovering long spatial range influences in climate variations. Traditional methods of predicting correlation matrices utilize time series data of all the nodes of the underlying networks. Here, we use a supervised machine learning technique to predict the correlation matrix of entire systems from finite time series information of a few randomly selected nodes. The accuracy of the prediction validates that only a limited time series of a subset of the entire system is enough to make good correlation matrix predictions. Furthermore, using an unsupervised learning algorithm, we furnish insights into the success of the predictions from our model. Finally, we employ the machine learning model developed here to real-world data sets. © 2022, CC BY.

关键词： Forecasting

Performance Evaluation of WMNs by WMN-PSOSA System Considering Chi-square and Exponential Client Distributions 33rd

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Performance Evaluation of WMNs by WMN-PSOSA System Consideri...

33rd International Conference on Advanced information Networking and Applications, AINA-2019

作者： Sakamoto, Shinji Barolli, Leonard Okamoto, Shusuke Department of Computer and Information Science Seikei University 3-3-1 Kichijoji-Kitamachi Musashino-shiTokyo180-8633 Japan Department of Information and Communication Engineering Fukuoka Institute of Technology 3-30-1 Wajiro-Higashi Higashi-KuFukuoka811-0295 Japan

ISBN: (纸本)9783030150310

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high-speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-SA. Then, we implemented a hybrid simulation system based on PSO and SA, called WMN-PSOSA. In this paper, we analyse the performance of WMNs by using WMN-PSOSA considering two types of mesh clients distributions. Simulation results show that a good performance is achieved for Exponential distribution compared with the case of Chi-square distribution. © 2020, Springer Nature Switzerland AG.

关键词： Simulated annealing

High bit rate modulation approach used by new generation mobile technology

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AIP Conference Proceedings 2023年第1期2591卷

作者： Zainab Faydhe Al-Azzawi Fatima Faydhe Al-Azzawi Wissam Fadhal Abid Batool Faydhe Al-Azzawi 1Department of Computer Technology Engineering AL-Mansour University College Baghdad Iraq 2Electronics Technical Department Institute of Technology/ Baghdad Middle Technical University (MTU) Baghdad Iraq

Every year there is improving in the connection speed of mobile communication technology. Due to market requirements the wireless communication improves in addition of speed the reliability and functionality improves too. For digital telecommunication systems QAM considered as a modulation scheme, such as in 802.11 Wi-Fi standards. Efficiencies with high spectral can be done with QAM with a size of constellation that are suitable for specific application, limitation occur only by linearity of the communications channel and the noise level. In this paper 64 QAM modulator design, implemented and waveform generated using MATLAB Simulink with binary and gray symbol mapping, PN9 and 15-bit source, with Normal Raised Cosine NRC and Root Raised Cosine RRC filter effect on both time and frequency domain.

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Controlling chaotic itinerancy in laser dynamics for reinforcement learning

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arXiv 2022年

作者： Iwami, Ryugo Mihana, Takatomo Kanno, Kazutaka Sunada, Satoshi Naruse, Makoto Uchida, Atsushi Department of Information and Computer Sciences Saitama University 255 Shimo-okubo Sakura-ku Saitama Saitama338-8570 Japan Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma-machi Ishikawa Kanazawa920-1192 Japan PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

Photonic artificial intelligence has attracted considerable interest in accelerating machine learning;however, the unique optical properties have not been fully utilized for achieving higher-order functionalities. Chaotic itinerancy, with its spontaneous transient dynamics among multiple quasi-attractors, can be employed to realize brain-like functionalities. In this paper, we propose a method for controlling the chaotic itinerancy in a multi-mode semiconductor laser to solve a machine learning task, known as the multi-armed bandit problem, which is fundamental to reinforcement learning. The proposed method utilizes ultrafast chaotic itinerant motion in mode competition dynamics controlled via optical injection. We found that the exploration mechanism is completely different from a conventional searching algorithm and is highly scalable, outperforming the conventional approaches for large-scale bandit problems. This study paves the way to utilize chaotic itinerancy for effectively solving complex machine learning tasks as photonic hardware accelerators. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamics

When Quantum information Technologies Meet Blockchain in Web 3.0

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arXiv 2022年

作者： Xu, Minrui Ren, Xiaoxu Niyato, Dusit Kang, Jiawen Qiu, Chao Xiong, Zehui Wang, Xiaofei Leung, Victor C.M. School of Computer Science and Engineering Nanyang Technological University Singapore College of Intelligence and Computing Tianjin University Tianjin300072 China Shenzhen518000 China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing-force networking, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with the advantages of quantum computing and communication. Therefore, in this paper, we introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. First, we present the framework of quantum blockchain-driven Web 3.0 with future-proof security during the transmission of data and transaction information. Next, we discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0. Finally, we describe a use case for quantum non-fungible tokens (NFTs) and propose a quantum deep learning-based optimal auction for NFT trading to maximize the achievable revenue for sufficient liquidity in Web 3.0. In this way, the proposed framework can achieve proven security and sustainability for the next-generation decentralized digital society. © 2022, CC BY.

关键词： Blockchain