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Receiving UWB antenna for wireless capsule endoscopy communications

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Progress In Electromagnetics Research C 2020年 101卷 53-69页

作者： Kissi, Chaïmaâ Särestöniemi, Mariella Kumpuniemi, Timo Myllymäki, Sami Sonkki, Marko Mäkelä, Juha-Pekka Srifi, Mohamed Nabil Jantunen, Heli Pomalaza-Raez, Carlos Ibn Tofail University Kenitra Morocco Centre for Wireless Communications Faculty of Information Technology and Electrical Engineering University of Oulu Finland Microelectronics Research Unit Faculty of Information Technology and Electrical Engineering University of Oulu Finland Department of Electrical and Computer Engineering Purdue University Fort WayneIN46805 United States

Wireless capsule endoscopy systems utilize a combination of hardware and software devices to ensure the healthcare of a human being. In praise of involved antennas in the overall medical system design, UWB (Ultra-Wideband) range occupies the highest ranks in the literature. The low-band of UWB is regarded as the best frequency range, within the approved standards, to realize the better transmission of captured medical images by the capsule inside the SI tract, in terms of high resolution and low-path loss. A variety of passive capsules have been designed and made available in the literature, while the accurate design of the corresponding on-body antenna is lagging. For this purpose, this paper provides an extended study of a recently published on-body antenna operating at 3.75–4.25 GHz band. The measured antenna realizes good directivity of 5.78 dBi and 9.50 dBi towards the body without and with the cavity, respectively. The direction of the proposed on-body antenna beam is targeted to be mounted on the body surface. On-body simulations were run with CST Microwave Studio by involving an abdominal multi-layer model, and followed by navel and back areas of the voxel model to predict the antenna behavior close to different lossy body environments. Later, the antenna structure was measured next to a real human abdomen. Simulation results reveal that the proposed antenna with or without the cavity enables enhanced in-body communication when mounted on the abdomen with less path loss. This is supported by the low power totaling 20 dB at the SI (Small Intestine) tract. Furthermore, on-body measurements confirm the good antenna performance. Consequently, the planar compact antenna is regarded as a good on-body candidate for wireless capsule endoscopy systems. © 2020, Electromagnetics Academy. All rights reserved.

关键词： Microwave antennas

Constrained combinatorial optimization with reinforcement learning

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arXiv 2020年

作者： Solozabal, Ruben Ceberio, Josu Takáč, Martin Department of Communications Engineering University of the Basque Country Bilbao48013 Spain Department of Computer Science and Artificial Intelligence University of the Basque Country Donostia20018 Spain Lehigh University Industrial and Systems Engineering Department 200 West Packer Avenue BethlehemPA18015 United States

This paper presents a framework to tackle constrained combinatorial optimization problems using deep Reinforcement Learning (RL). To this end, we extend the Neural Combinatorial Optimization (NCO) theory in order to deal with constraints in its formulation. Notably, we propose defining constrained combinatorial problems as fully observable Constrained Markov Decision Processes (CMDP). In that context, the solution is iteratively constructed based on interactions with the environment. The model, in addition to the reward signal, relies on penalty signals generated from constraint dissatisfaction to infer a policy that acts as a heuristic algorithm. Moreover, having access to the complete state representation during the optimization process allows us to rely on memory-less architectures, enhancing the results obtained in previous sequence-to-sequence approaches. Conducted experiments on the constrained Job Shop and Resource Allocation problems prove the superiority of the proposal for computing rapid solutions when compared to classical heuristic, metaheuristic, and Constraint Programming (CP) solvers. Copyright © 2020, The Authors. All rights reserved.

关键词： Heuristic algorithms

Hamilton–jacobi deep Q-learning for deterministic continuous-time systems with lipschitz continuous controls

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arXiv 2020年

作者： Kim, Jeongho Shin, Jaeuk Yang, Insoon Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Automation and Systems Research Institute Seoul National University Seoul08826 Korea Republic of

In this paper, we propose Q-learning algorithms for continuous-time deterministic optimal control problems with Lipschitz continuous controls. Our method is based on a new class of Hamilton–Jacobi–Bellman (HJB) equations derived from applying the dynamic programming principle to continuous-time Q-functions. A novel semi-discrete version of the HJB equation is proposed to design a Q-learning algorithm that uses data collected in discrete time without discretizing or approximating the system dynamics. We identify the condition under which the Q-function estimated by this algorithm converges to the optimal Q-function. For practical implementation, we propose the Hamilton–Jacobi DQN, which extends the idea of deep Q-networks (DQN) to our continuous control setting. This approach does not require actor networks or numerical solutions to optimization problems for greedy actions since the HJB equation provides a simple characterization of optimal controls via ordinary differential equations. We empirically demonstrate the performance of our method through benchmark tasks and high-dimensional linear-quadratic problems. Copyright © 2020, The Authors. All rights reserved.

关键词： Continuous time systems

Blockchain-Based Wi-Fi Offloading Platform for 5G

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Blockchain-Based Wi-Fi Offloading Platform for 5G

IEEE International Conference on communications Workshops, ICC

作者： Pramitha Fernando Lasitha Gunawardhana Wishva Rajapakshe Mahesh Dananjaya Tharindu Gamage Madhusanka Liyanage Department of Electrical and Information Engineering University of Ruhuna Sri Lanka School of Informatics University of Edinburgh UK School of Computer Science University College Dublin Ireland Centre for Wireless Communications University of Oulu Finland

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

The advent of 5G has sparked interest in Wi-Fi offloading techniques that enable efficient resource sharing and congestion management of wireless communication spectrum. However, offloading data between multiple networks (i.e. service providers) requires costly inter-provider communication which has a substantial overhead as well as high offloading latency. Moreover, involvement of the profit-oriented decision making of service providers has an inherent weakness of unfair scheduling among users and networks. To overcome those problems, this research work proposes a holistic framework similar to an online data market place where existing infrastructure can be used to set up Wi-Fi zones that everyone can use from their own data plan irrespective of the network operators they belong to. First, our proposed architecture improves the efficacy of offloading by using decentralized nature of the emerging Software-Defined Networking (SDN) to set up an operator-assisted data offloading platform, resulting in efficient inter-provider communication. Second, our proposal strengthens the fair scheduling of offloading resources by using blockchain technology to initiate unbiased and independent decision making. The resulting service is a rating system for the sellers to make reliable transactions for payments.

关键词： Wireless fidelity Contracts Bandwidth Pricing Decision making

Mobility Dependent Hybrid RF/FSO Backhaul in UAV Assisted Cellular Networks

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Mobility Dependent Hybrid RF/FSO Backhaul in UAV Assisted Ce...

IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Muhammad Usman Saud Althunibat Khalid Qaraqe Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar Department of Communications Engineering Al-Hussein Bin Talal University Ma’an Jordan Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9781728163390

ISBN: (纸本)9781728163406

The increasing trend of employing unmanned air vehicles (UAVs) as movable base stations (MBSs) holds a great potential of enhancing the performance of a cellular network at a cell edge. The performance is generally enhanced to either accommodate more users or to optimize the throughput of existing ones. One of the paramount challenges of deploying an MSB-based cellular network is to design a stable backhaul connection of the MBS with the ground base station (BS). This paper proposes a hybrid backhaul based on radio frequency (RF) and free space optical (FSO) communication, where the decision to choose between RF and FSO depends on mobility of the MBS. In particular, an analytical framework to model the mobility of a MBS is proposed wherein the probability to fly or to stop is estimated. In addition, analytical expressions for the bit error rate (BER) of RF-only backhaul, FSO-only backhaul and mobility-dependent hybrid RF/FSO backhaul are derived and substantiated through Monte Carlo simulation results.

关键词： Radio frequency Base stations Cellular networks Fading channels Unmanned aerial vehicles Throughput Nakagami distribution

Cramér-rao bound optimization for joint radar-communication design

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arXiv 2021年

作者： Liu, Fan Liu, Ya-Feng Li, Ang Masouros, Christos Eldar, Yonina C. The Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Information and Communications Engineering Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’anShaanxi710049 China The Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom The Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramér-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the CRB of radar sensing while guaranteeing a pre-defined level of signal-to-interference-plus-noise ratio (SINR) for each communication user. For the single-user scenario, we derive a closed form for the optimal solution for both cases of point and extended targets. For the multi-user scenario, we show that both problems can be relaxed into semidefinite programming by using the semidefinite relaxation approach, and prove that the global optimum can always be obtained. Finally, we demonstrate numerically that the globally optimal solutions are reachable via the proposed methods, which provide significant gains in target estimation performance over state-of-the-art benchmarks. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal to noise ratio

AuthCODE: A privacy-preserving and multi-device continuous authentication architecture based on machine and deep learning

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arXiv 2020年

作者： Sánchez Sánchez, Pedro Miguel Huertas Celdrán, Alberto Fernández Maimó, Lorenzo Martínez Pérez, Gregorio Department of Information and Communications Engineering University of Murcia Murcia30100 Spain Telecommunication Software and Systems Group Waterford Institute of Technology WaterfordX91 P20H Ireland Department of Computer Engineering University of Murcia Murcia30100 Spain

The authentication field is evolving towards mechanisms able to keep users continuously authenticated without the necessity of remembering or possessing authentication credentials. While existing continuous authentication systems have demonstrated their suitability for single-device scenarios, the Internet of Things and next generation of mobile networks (5G) are enabling novel multi-device scenarios -such as Smart Offices-where continuous authentication is still an open challenge. The paper at hand, proposes an AI-based, privacy-preserving and multi-device continuous authentication architecture called AuthCODE. A realistic Smart Office scenario with several users, interacting with their mobile devices and personal computer, has been used to create a set of single- and multi-device behavioural datasets and validate AuthCODE. A pool of experiments with machine and deep learning classifiers measured the impact of time in authentication accuracy and improved the results of single-device approaches by considering multi-device behaviour profiles. The f1-score average reached for XGBoost on multidevice profiles based on 1-minute windows was 99.33%, while the best performance achieved for single devices was lower than 97.39%. The inclusion of temporal information in the form of vector sequences classified by a Long-Short Term Memory Network, allowed the identification of additional complex behaviour patterns associated to each user, resulting in an average f1-score of 99.02% on identification of long-term behaviours. Copyright © 2020, The Authors. All rights reserved.

关键词： Authentication

Multi-Antenna UAV Data Harvesting: Joint Trajectory and Communication Optimization

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arXiv 2020年

作者： Zhang, Jingwei Zeng, Yong Zhang, Rui Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

Unmanned aerial vehicle (UAV)-enabled communication is a promising technology to extend coverage and enhance throughput for traditional terrestrial wireless communication systems. In this paper, we consider a UAV-enabled wireless sensor network (WSN), where a multi-antenna UAV is dispatched to collect data from a group of sensor nodes (SNs). The objective is to maximize the minimum data collection rate from all SNs via jointly optimizing their transmission scheduling and power allocations as well as the trajectory of the UAV, subject to the practical constraints on the maximum transmit power of the SNs and the maximum speed of the UAV. The formulated optimization problem is challenging to solve as it involves non-convex constraints and discrete-value variables. To draw useful insight, we first consider the special case of the formulated problem by ignoring the UAV speed constraint and optimally solve it based on the Lagrange duality method. It is shown that for this relaxed problem, the UAV should hover above a finite number of optimal locations with different durations in general. Next, we address the general case of the formulated problem where the UAV speed constraint is considered and propose a traveling salesman problem (TSP)-based trajectory initialization, where the UAV sequentially visits the locations obtained in the relaxed problem with minimum flying time. Given this initial trajectory, we then find the corresponding transmission scheduling and power allocations of the SNs and further optimize the UAV trajectory by applying the block coordinate descent (BCD) and successive convex approximation (SCA) techniques. Finally, numerical results are provided to illustrate the spectrum and energy efficiency gains of the proposed scheme for multi-antenna UAV data harvesting, as compared to benchmark schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

Dual-hop Relaying Networks for Short-Packet URLLCs: Performance analysis and Optimization

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TechRxiv

TechRxiv 2021年

作者： Linh, Nguyen Thi Yen Tu, Ngo Hoang Son, Pham Ngoc Bao, Vo Nguyen Quoc Department of Electrical and Electronic Engineering Ho Chi Minh City University of Technology and Education Ho Chi Minh City710372 Viet Nam Wireless Communications Laboratory Post and Telecommunications Institute of Technology Ho Chi Minh City710372 Viet Nam Department of Smart Energy Systems Seoul National University of Science and Technology Seoul01811 Korea Republic of Department of Computer Engineering Ho Chi Minh City University of Transport Ho Chi Minh City710372 Viet Nam Department of Electrical and Electronic Engineering Ho Chi Minh City University of Technology and Education Ho Chi Minh City710372 Viet Nam Wireless Communications Department Posts and Telecommunications Institute of Technology Ho Chi Minh City710372 Viet Nam

This paper investigates short-packet communications for the dual-hop decode-and-forward relaying system to facilitate ultra-reliable and low-latency communications. In this system, based on the transmit antenna selection and partial relay selection techniques, a selected relay having the highest received signal-to-noise ratio (SNR) serves as a forwarder to support the unavailable direct link between the source and destination, whereas a maximum ratio combining technique is leveraged at the destination to achieve the highest diversity gain. Approximated expressions of end-to-end (e2e) block error rates (BLERs) are derived over quasi-static Rayleigh fading channels and the finite-blocklength regime. To gain more insights about the performance behavior in the high-SNR regime, we provide the asymptotic analysis with two approaches, from which the qualitative conclusion based on the diversity order is made. Furthermore, the power allocation and relay location optimization problems are also considered to minimize the asymptotic e2e BLER under the configuration constraints. Our analysis is verified through Monte-Carlo simulations, which yield the system parameters’ impact on the system performance. © 2021, CC BY.

关键词： Signal to noise ratio