2023 57th Annual Conference on Information Sciences and Systems (CISS)最新文献

{"title":"Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mURLLC Wireless Networks","authors":"Xi Zhang, Qixuan Zhu, H. Poor","doi":"10.1109/CISS56502.2023.10089741","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089741","url":null,"abstract":"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.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115006781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous Statistical QoS Provisioning for Scalable Software-Defined 6G Mobile Networks","authors":"Xi Zhang, Qixuan Zhu, H. Poor","doi":"10.1109/CISS56502.2023.10089641","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089641","url":null,"abstract":"Due to the explosively increasing number of mobile users and the new types of data demands in the fifth generation (5G) mobile wireless network, research in wireless networks has shifted toward the development of the sixth-generation (6G) wireless network. Although the research for software-defined network (SDN) architectures in 5G mainly focuses on the dynamic programming for the internet backbone, these software programming techniques can be also applied at the network edge to support the exponentially increasing demands from mobile users under constrained wireless resources. In order to study the interference problem resulted by massive mobile users, the scaling law is a powerful tool to show how fast the levels of network imperfections can be tolerated as the number of mobile users increases. In this paper, we investigate the scaling behavior of software-defined architectures over 6G wireless networks. We consider the wireless channel in three scenarios: single-input-single-output (SISO), multiple-input-single-output (MISO), and multiple-input-multiple-output (MIMO), where we derive the corresponding scaling law for each scenario, respectively. Our derived scaling law shows how the network performance scales with the number of mobile users in a wireless network. Then, we propose a software-defined network slicing scheme to select the optimal mobile users and derive their optimal resource allocations, according to our derived scaling law, under SISO, MISO, and MIMO wireless channel, respectively. Finally, we validate and evaluate the derived scaling behavior of the software-defined architecture over 6G wireless networks through numerical analyses.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121979263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Analysis and Optimization for Urban Energy Systems Equitable Resilience","authors":"Gabrielle Ebbrecht, Juntao Chen","doi":"10.1109/CISS56502.2023.10089717","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089717","url":null,"abstract":"Electric vehicles (EVs) can be leveraged as power resources to support the grid operation in challenging scenarios, e.g., natural disasters or health crises such as the COVID-19 pandemic. This paper aims to enhance equity of power resilience in urban energy systems by means of strategic allocation of EV charging infrastructure. We first use data-driven approaches to infer the relationships between communities' power resilience equity and available EV charging infrastructure as well as other prominent social-demographic factors. This inference leads to the development of a machine learning model for power resilience inequity prediction. We further develop an optimization frame-work that jointly considers equitable resiliency and resource utilization to guide the optimized EV charging infrastructure allocation across the city. Case studies demonstrate the capability of the devised approach in enhancing power resilience equity in marginalized communities.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129363243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Detection with Unreliable Reporting Channels: Quantize or Not Quantize?","authors":"Lei Cao, R. Viswanathan","doi":"10.1109/CISS56502.2023.10089620","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089620","url":null,"abstract":"It is known that reporting the raw data observed at sensors to the fusion center completely and without any channel distortion always performs better than reporting the quantized data. However, when channel noise exists as it is always in practice, we show whether it is optimal to send the unquantized raw data or quantized data is a very interesting question that requires more research efforts. We compare these two schemes under the constraints of using the same transmission power and the bandwidth where analog modulation is assumed per channel use. The detection performance with one sensor and two sensors is presented in terms of the Bayes error. The performance of using asymptotically many sensors is compared with the Chernoff information. What presented in the paper could open up a new perspective in the design of the optimal distributed detection systems.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122362912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Output Reachability of Chen-Fliess series: A Newton-Raphson Approach","authors":"Ivan Perez Avellaneda, L. A. D. Espinosa","doi":"10.1109/CISS56502.2023.10089740","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089740","url":null,"abstract":"The optimization of Chen-Fliess series allows addressing the problem of the computation of reachable sets of nonlinear affine control systems. This provides an input-output approach to reachability analysis. The Newton-Raphson method is one of the most important line search numerical algorithms. The method is based on the computation of the Hessian and the second-order Taylor approximation of the function of interest. Currently, only first-order optimization methods, such as gradient descent, exist for Chen-Fliess series. In this paper, the framework of differential languages is introduced to allow a systematic description of higher-order derivatives of Chen-Fliess series. This is achieved by defining the derivative operation of a word in a monoid that coincides with the Gâteaux derivative of a Chen-Fliess series. In this context, the Hessian of a Chen-Fliess series, its second-order Taylor approximation, and the second-order optimization condition are provided for Chen-Fliess series. Then the Newton-Raphson algorithm is adapted to Chen-Fliess series optimization to compute reachable sets. Illustrative examples and simulations are presented throughout the paper.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130450746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospect Theoretic Contract Design in a Stackelberg Game via Bayesian Inference","authors":"Elham Jamalinia, P. Venkitasubramaniam","doi":"10.1109/CISS56502.2023.10089699","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089699","url":null,"abstract":"Dynamic contract design with a cognitively biased principal is studied in this work using a Stackelberg game framework. Prospect theory is used to model the decision making of the cognitively biased principal. The goal of the principal is to design a sequence of contracts when faced with adverse selection-lack of knowledge of agent's private information- and moral hazard- noisy observation of agent's effort. The principal observes the noisy output of the agent's effort and using the prior probabilities of the agent's private information, performs a Bayesian inference of the agent's type taking into account Prospect theoretic probability weighting. The prospect theoretic decision making of principal is studied for a static game (one shot) and a dynamic game (finite number of rounds). It is demonstrated that the agent will benefit from principal's irrationality by extracting higher rent than the game with a rational principal. Theoretical results are derived for the binary type games, and the investigation is expanded to an $M$ -ary hypothesis testing framework through numerical simulation results. The results demonstrate that in estimating the agent's type, a cognitively biased principal becomes more conservative to ensure agent's participation in the game than a rational principal thus allowing increased rent for the agent.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123756180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Body-mounted MR-HIFU Robotic System: Mechanical Design and Accuracy Evaluation","authors":"Ayush Nankani, P. Yarmolenko, Karun Sharma, K. Cleary, R. Monfaredi","doi":"10.1109/CISS56502.2023.10089665","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089665","url":null,"abstract":"Magnetic Resonance Image-Guided High-Intensity Focused Ultrasound (MR-HIFU) is a technology that enables non-invasive MRI-guided ablation of anatomy, such as benign and malignant tumors and pain-causing nerves. In recent years, MR-HIFU has been widely used for various applications, such as treating uterine fibroids, bone metastases, and prostate and brain cancer, among other diseases. However, the current clinical MR-HIFU systems have shortcomings, such as limited or impossible patient positioning options for targets in the extremities, torso, and neck areas. These shortcomings stem from integrating the ultrasound transducer into the MRI table. This study aims to develop a body-mounted, MRI-compatible robotic positioning system for in-bore procedures for treating musculoskeletal lesions in the extremities. The proposed system aims to improve patient positioning options and increase the accuracy of MR-HIFU for these procedures. A 5-DOF (degrees of freedom) body-mounted MRI-compatible robotic system was designed, and its workspace and kinematics were analyzed using MATLAB and Simulink. A mechanical prototype was fabricated using 3D printers and other manufacturing tools using non-ferromagnetic materials. The targeting accuracy of the prototype was measured using an optical tracker in two benchtop studies. The proposed body-mounted MRI-compatible robotic positioning system has the potential to address the limitations of current clinical MR-HIFU body systems. We propose improving patient positioning and accuracy by using a novel vacuum-pad-based mounting system that conforms to the local body shape and stabilizes both the target anatomy and the robot. The system's high modularity also allows using various probes or needle-based MRI-guided percutaneous interventions by removing the HIFU probe and placing a needle guide tool. As opposed to a table-integrated robot, our proposed robot is patient-mounted and can potentially be integrated with different MRI scanners from different manufacturers.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131541856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning of Doppler Tolerant Radar Detectors for Noise Waveforms","authors":"Kyle P. Wensell, James Zhou, A. Haimovich, Evan A. Young, Lam T. Vo","doi":"10.1109/CISS56502.2023.10089751","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089751","url":null,"abstract":"This work analyzes neural network learning as it pertains to noise waveform radar detectors. The concept of noise waveform radar is explored, and the core issue of Doppler tolerance is addressed. In order for the network to successfully learn the noise waveform, a pre-processing step of phase alignment is performed on the data to allow the neural network to establish a pattern. The training data is then augmented with Dopplershifted waveforms, such that this Doppler shift appears in the phase-aligned data. We demonstrate that this pre-processing and training scheme successfully allows for the detector to learn Doppler intolerant waveforms such as the noise waveforms.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132526940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Machine Learning to Quantum Cascade Laser Design","authors":"A. Hernandez, C. Gmachl","doi":"10.1109/CISS56502.2023.10089756","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089756","url":null,"abstract":"A framework to innovate quantum cascade laser design was developed using machine learning. An 8.2 μm laser with an operating field of 51 kV/cm and 131.7 eV ps Å2for the figure of merit was chosen as the starting design. A dataset of 13200 different designs was generated from the original, each design consisting of 22 well/barrier thicknesses with random well/barrier changes in the [−5, +5] Å range and an applied electric field from 20–70 kV/cm, for a total of 23 inputs. A second completely random dataset with 22 well/barrier thicknesses in the [9], [57] Å range was also developed, with 13200 designs and the same electric field sweep. The lasing transition figure of merit, gain coefficient, dipole matrix element, scattering times, and electronic state-pair energy difference were identified for each of these designs and were the outputs to be predicted. Single-output regression and multi-output regression were used to predict the figure of merit. Single-output regression was able to give root-mean-square error of 16 to 24 for the figure of merit in a matter of seconds. Multi-output regression predicts the root-mean-square error from 17 to 19 when trained for 10 to 30 minutes, sweeping through neural network parameters of interest. Both types of algorithms predicted data that was similar to training data very well but did not perform as well when new data was introduced.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134007977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perspicuity of Evacuation Behavior in Communities during Hurricanes using Large-scale Mobility Patterns and Communal Characteristics","authors":"Harsh Anand, M. Shafiee-Jood, Negin Alemazkoor","doi":"10.1109/CISS56502.2023.10089754","DOIUrl":"https://doi.org/10.1109/CISS56502.2023.10089754","url":null,"abstract":"The announcement of evacuation orders during hurricanes is an integral part of an emergency preparedness and response plan, specifically for reducing social and economic distress. Although such orders are generally assumed to be followed in theory, in practice, evacuation rates in response to an evacuation order vary widely among communities. The purpose of this study is to examine how socioeconomic and demographic factors affect the evacuation decisions of communities in response to government-issued evacuation orders. Particularly, we harness passively collected high-fidelity mobility data in conjunction with the community characteristics to analyze the disparate evacuation pattern of 2, 617 census block groups (CBGs) in Florida during Hurricane Dorian. Our finding suggests that the lead time of evacuation orders, median age, and a racial minority percentage of CBGs affect the shift in evacuation rate once orders are issued. The study results, along with the comprehensive discussion, contribute to a deeper understanding of the factors that influence evacuation behavior during hurricanes. This can assist emergency management stakeholders in making strategic decisions to maximize community response to evacuation orders.","PeriodicalId":243775,"journal":{"name":"2023 57th Annual Conference on Information Sciences and Systems (CISS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123251119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}