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Annual Conference on Information Sciences and systems (CISS)

作者： Xi Zhang Qixuan Zhu H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

The sixth generation (6G) mobile wireless networks are expected to provide massive ultra-reliable and low-latency communications (mURLLC) for data services, which require extremely stringent quality-of-services (QoS) with massive connectivity. Rate splitting (RS) multiple access schemes have been proposed recently for tackling the difficulty of the massive access yielded by a large number of mobile users (MUs) requesting to connect to a single base station. Massive multiple-input and multiple-output (massive-MIMO) communication is considered a promising solution to serve massive MUs in 6G wireless networks. However, how to apply RS schemes into massive-MIMO techniques to support the massive access has not been sufficiently studied. In this paper, we propose to integrate RS schemes with massive-MIMO techniques to achieve mURLLC transmissions under a Nakagamir $m$ fading wireless channel. First, we establish the system model for the integrated RS and massive-MIMO schemes. Then, we derive closed-form expressions for the signal-to-interference-plus-noise ratios (SINRs) under a Nakagami- $-m$ fading channel and obtain the channel capacity. Finally, we use numerical analyses to validate and evaluate our proposed RS and massive-MIMO integrated schemes.

关键词： 6G mobile communication Fading channels Closed-form solutions Channel capacity Wireless networks Interference Quality of service

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The ε-Effective Capacity for Statistical Delay and Error-Rate Bounded QoS Provisioning Over 6G CF M-MIMO Wireless Networks Using HARQ-IR

The ε-Effective Capacity for Statistical Delay and Error-Ra...

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Annual Conference on Information Sciences and systems (CISS)

作者： Xi Zhang Jingqing Wang H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

Significant effort has been devoted to the problem of guaranteeing stringent ultra-reliable and low-latency communications (URLLC) while introducing new requirements for better quality-of-services (QoS) over next generation wireless networks. One of the major design issues raised by URLLC is how to support explosively growing demands for delay-sensitive multimedia applications while guaranteeing ultra-reliability. Towards this end, there have been a wide spectrum of promising techniques, including statistical delay and error rate-bounded QoS provisioning, cell-free (CF) massive multiple-input-multiple-output (m-MIMO), finite blocklength coding (FBC), hybrid automatic repeat request with incremental redundancy (HARQ-IR) protocol, etc. However, when being integrated with FBC, how to rigorously and efficiently characterize the dynamics of mobile wireless networks in terms of statistical delay and error-rate bounded QoS provisioning for CF m-MIMO has imposed many new challenges not encountered before. To overcome these challenges, in this paper we develop statistical delay and error-rate bounded QoS analytical modeling schemes to characterize the FBC-based $\epsilon$ -effective capacity over 6G CF m-MIMO wireless networks using HARQ-IR. In particular, first we establish CF m-MIMO based system architecture models. Second, we apply a HARQ-IR protocol for deriving the channel coding rate, outage probability, and FBC based $\epsilon$ -effective capacity function using the Mellin transform. Finally, we conduct a set of simulations to validate and evaluate our proposed schemes.

关键词： 6G mobile communication Analytical models Protocols Wireless networks systems architecture Quality of service Transforms

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Information Geometry Approach for Ultra-Massive MIMO Signal Detection 15

Information Geometry Approach for Ultra-Massive MIMO Signal ...

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Chen, Yan Yang, Jiyuan Gao, Xiqi Slock, Dirk Xia, Xiang-Gen Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Eurecom Department of Communication Systems Biot06410 France University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States

ISBN: (纸本)9798350324662

In this paper, we propose an information geometry approach (IGA) for signal detection in ultra-massive multiple-input multiple-output (MIMO) systems. We formulate the signal detection as obtaining the marginals of the a posteriori probability distribution of the transmitted symbol vector. Then, a maximization of the a posteriori marginals (MPM) for signal detection can be performed. With the information geometry theory, we calculate the approximations of the a posteriori marginals. It is formulated as an iterative m-projection process. We then apply the central-limit-theorem (CLT) to simplify the calculation of the m-projection since the direct calculation of the m-projection is of exponential-complexity. With the CLT, we obtain an approximate solution of the m-projection, which is asymptotically accurate. Simulation results demonstrate that the proposed IGA is a promising and efficient method to implement the signal detector in ultra-massive MIMO systems. © 2023 IEEE.

关键词： Bayesian inference information geometry signal detection Ultra-massive MIMO

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Sub-micron Ultracold Neutron Position Resolution using Chip Based Optical Neural Network

Sub-micron Ultracold Neutron Position Resolution using Chip ...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Lin, S. Zhu, H. Clayton, S. Morris, C.L. Tang, Z. Wang, Z. Chen, R.T. Los Alamos National Laboratory Los AlamosNM87545 United States Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78705 United States Microelectronics Research Center The University of Texas at Austin AustinTX78758 United States Omega Optics Inc. AustinTX78757 United States

High spatial resolution of ultracold neutron (UCN) measurements of 1 µm or less is highly desired for many UCN experiments. Optical neural networks are potential radiation-hard hardware platforms for real-time, e... 详细信息

ISBN: (纸本)9781957171395

关键词： Semiconductor lasers

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An AOP-Based Security Verification Environment for KECCAK Hash Algorithm

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computers, Materials & Continua 2022年第11期73卷 4051-4066页

作者： Hassen Mestiri Imen Barraj Mohsen Machhout Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj 11942Saudi Arabia Higher Institute of Applied Sciences and Technology of Sousse University of SousseTunisia Electronics and Micro-Electronics Laboratory Faculty of Sciences of MonastirUniversity of MonastirTunisia Electrical Engineering Department Systems Integration&Emerging Energies(SI2E)National Engineers School of SfaxUniversity of SfaxTunisia Higher Institute of Computer Science and Multimedia of Gabes University of GabesTunisia

Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure *** to significant resource constraints,these devices are limited in their *** increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection *** is a good choice for Electronic System Level(ESL)modeling since it enables models to run at a faster *** enable fault injection and detection inside a SystemC cryptographic model,however,the model’s source code must be *** altering the source code,Aspect-Oriented Programming(AOP)may be used to evaluate the robustness of cryptographic *** might replace conventional cryptanalysis methods in the real *** the ESL,we discuss a unique technique for simulating security fault attacks on cryptographic *** current study presents a fault injection/detection environment for assessing the KECCAK SystemC model’s resistance against fault injection *** approach of injecting faults into KECCAK SystemC model is accomplished via the use of weaving faults in AspectC++based on AOP programming *** confirm our technique by applying it to two scenarios using a SystemC KECCAK hash algorithm case study:The first concerns discuss the effect of the AOP on fault detection capabilities,while the second concerns discuss the effect of the AOP on simulation time and executable file *** simulation results demonstrate that this technique is fully capable of evaluating the fault injection resistance of a KECCAK *** demonstrate that AOP has a negligible effect on simulation time and executable file size.

关键词： Aspect-Oriented Programming SystemC AspectC++ cryptographic circuits KECCAK fault detection fault attacks

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Broadband and repetition rate tunable frequency comb based on electro-optic time lens with AlGaAsOl waveguide 49

Broadband and repetition rate tunable frequency comb based o...

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49th European Conference on Optical Communications, ECOC 2023

作者： Ma, Chunyang Wang, Chaopeng Pi, Yazhi Wang, Lei He, Zhixue Bowers, John E. Chnag, Lin Zizheng Cao, Lin Yu, Shaohua Research Center of Circuits and Systems Peng Cheng Laboratory Guangdong Shenzhen518055 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States State Key Laboratory of Advanced Optical Communications System and Networks Peking University Beijing100871 China

ISBN: (纸本)9781839539954

We present a tunable repetition rate frequency comb realized by cascaded electro-optical modulators with a high nonlinear AlGaAs-on-isolator waveguide. 18-26.5 GHz comb spacing tunability with broadband spectra was achieved. All the devices can be integrated onto a single chip, which makes this work useful for many applications. © The Institution of engineering & Technology 2023.

关键词： Aluminum gallium arsenide

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Electrooculogram Compression based on Wavelet Packet Decomposition

Electrooculogram Compression based on Wavelet Packet Decompo...

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IEEE Instrumentation and Measurement Technology Conference

作者： Alberto López Saeed Mian Qaisar Francisco Ferrero Réda Yahiaoui Department of Electrical Electronic Communications and Systems Engineering University of Oviedo Gijón Spain Electrical and Computer Engineering Department Effat University Jeddah Saudi Arabia SINERGIE Laboratory University of Franche-Comte Besancon France

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

The electrooculogram (EOG) represents the electrical activity of the eye. Since most EOG-based applications need a large amount of data to be stored and transmitted, compression is required. A study on the use of discrete wavelet packet decomposition (DWPD) for compressing EOG signals is presented in this paper. The EOG signals are recorded using a commercial bioamplifier. The compression algorithm is implemented using the MATLAB software. The performance of the compression was evaluated using three parameters: compression ratio (CR), energy retention, and percent root-mean-square difference (PRD). The experimental results show that the DWPD allows for CRs of 82% while retaining almost 100% of the signal energy with a PRD of only 7%.

关键词： Wavelet transforms Electrooculography Extraterrestrial measurements Distortion Wavelet packets Software High frequency

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FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures 4

FedMonitor: An Implementation Architecture for Monitoring of...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Nnaji, Uche Wejin, John S. Ojesanmi, Festus Akanle, Matthew B. Ajayi, Priscilla O. Sweetwiliams, Faith O. Thakur, Surendra C. Adebiyi, Ezekiel F. Department of Electrical and Information Engineering and Covenant Applied Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Covenant University Department of Computer and Information Science & CApIC-ACE Ota Nigeria Covenant University Department of Electrical and Information Engineering & CApIC-ACE Jalingo Nigeria Tareba State University Department of Computer Science Jalingo Nigeria Ota Nigeria Covenant University & CApIC-ACE Covenant University Department of Electrical and Information Engineering Ota Nigeria Covenant University Center for Systems and Information Services & CApIC-ACE Ota Nigeria Durban University of Technology e-Skills Co-Laboratory Department of Information Technology and KZN Durban4001 South Africa Covenant University Ogun State Ota Nigeria Makerere University African Center of Excellence in Bioinformatics & Data Intensive Science Kampala10218 Uganda

ISBN: (纸本)9798350353266

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments. © 2024 IEEE.

关键词： Cloud platforms

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Bridging the Artificial Intelligence Knowledge and Skill Gaps in Africa: a Case of the 3rdGoogle Tensorflow Bootcamp and FEDGEN Mini-Workshop

Bridging the Artificial Intelligence Knowledge and Skill Gap...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Adetiba, Emmanuel Wejin, John S. Oshin, Oluwadamilola Ifijeh, Ayodele H. Lawal, Comfort Thakur, Surendra Colin Awelewa, Ayokunle A. Kala, Raymond Jules Ajayi, Priscilla O. Akanle, Matthew B. Sweetwiliams, Faith O. Nnaji, Uche Owolabi, Emmanuel Idowu-Bismark, Olabode Sobola, Gabriel Ota Nigeria Durban University of Technology HRA Institute for Systems Science Durban South Africa Covenant University Department of Electrical and Information Engineering CApIC-ACE Jalingo Nigeria Taraba State University Department of Computer Science Jalingo Nigeria Covenant University Department of Electrical and Information Engineering CApIC-ACE Ota Nigeria Durban University of Technology Department of Information Technology Kzn E-Skills Co-Laboratory Durban4001 South Africa Covenant University Department of Electrical and Information Engineering Ota Nigeria International University of Grand Bassam Grand Bassam Ivory Coast Covenant University Center for Systems and Information Services CApIC-ACE Ota Nigeria Covenant University Department of Computer and Information Science CApIC-ACE Ota Nigeria Ltd 405 Justice Mahomed St. Gauteng Pretoria0002 South Africa

ISBN: (纸本)9798350358155

In transiting from one civilization to another, technology has played a vital and positive role. In the 21st century, one of the digital developments that is paving ways for human life improvement is machine-assisted technology using Artificial Intelligence (AI). Artificial Intelligence has successfully enhanced man's capacity in solving complex problems and processes. However, as developed nations continue to reap from the adoption of AI in various fields of human endeavors, the continent of Africa has remained behind, especially in AI-based skills and research. Various governments in developing nations have encouraged the adoption of AI, especially in institutions of learning. However, theoretical adoption without practical experience has remained an ineffective way of bridging the digital divide. In this paper we present the outcome of a practical approach to bridging the AI divide among students and researchers in Africa through funding support from the Google TensorFlow College Outreach Award. A 3-day hybrid bootcamp was organized (11th to 13th December, 2023) using the Google funding in order to equip postgraduate students and researchers with AI and collaborative research skills. A pre-survey method was employed to ascertain the knowledge level of the bootcamp participants. From the pre-surveyed feedback, training sessions on various AI domains were presented, and participant equipped with practical AI skills using a deployed AI-based cloud programming platform running on the private Federated Genomic Cloud (FEDGEN) infrastructure at Covenant University. A post-survey feedback was used to ascertain the effectiveness of this approach. A comparative analysis of the pre-survey and post-survey reveals a 70% improvement of AI skills among participants. This shows that having continuous training session for students and researchers is an effective method in closing the AI skills gap between developed and developing nations. © 2024 IEEE.

关键词： Federated learning

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Joint Optimization for Cooperative Service-Caching, Computation-Offloading, and Resource-Allocations Over EH/MEC 6G Ultra-Dense Mobile Networks

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IEEE Transactions on Wireless Communications 2025年

作者： Chen, Zhian Wang, Fei Zhang, Xi Southwest University College of Electronic and Information Engineering Chongqing400715 China Texas A&M University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States

Service-caching, computation-offloading, and mobile edge-computing (MEC) have been widely recognized as three key 6G wireless technologies which can efficiently support implementing the ultra-dense networks (UDNs) with massive small-cell base stations (SBSs). But, these impose the new challenges for the UDNs to solely rely on grid power for energy supplying and to jointly optimize service-caching, computation-offloading, and resource-allocations. To overcome the above described difficulties, integrating energy-harvesting (EH) techniques with MEC-enabled 6G UDNs, we propose to develop the joint optimization schemes for cooperative service-caching, computation-offloading, and resource-allocations. In our considered UDNs, there exist a large number of EH-based stationary users (SUs) or mobile users (MUs), and a mixture of on-grid SBSs powered by electric grid and off-grid SBSs power-supplied by solar, radio frequency (RF) energy, etc. Specifically, first we formulate an energy minimization problem under a non-linear RF-energy EH model to minimize the sum of weighted energy consumption of users and off-grid SBSs. Second, for scenarios with SUs, we develop a two-timescale based joint cooperative service-caching, computation-offloading, and resource-allocations scheme using the hierarchical multi-agent deep reinforcement learning. We derive cooperative service-caching in each time frame, and then derive computation-offloading and resource-allocations in each time slot. Third, we extend our work to scenarios with MUs, where MUs can move with certain trajectories at low speeds. Finally, we validate and evaluate the performances of our proposed schemes through the extensive simulations. © 2002-2012 IEEE.

关键词： Energy utilization

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