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Joint Optimization of Uplink Spectrum Efficiency and UAV Trajectory in Cell-Free UAV Networks

Joint Optimization of Uplink Spectrum Efficiency and UAV Tra...

IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and communications (GreenCom)

作者： Jian He Chunyu Pan Qian Chen The Key Laboratory of Information and Communication Systems Ministry of Information Industry and the Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin China

The flexible mobility characteristics of unmanned aerial vehicle (UAV) lead to frequent handover and inter cell interference issues in traditional cellular based UAV assisted communication systems. Establishing cell-free UAV (CF-UAV) networks without cell boundaries will effectively alleviate this problem and has been an important research. However, the movement of the UAV results in time-varying channels. Therefore, the joint dynamic and reasonable UAV trajectory optimization and power allocation are very important for in CF-UAV networks. The expression of pilot transmission, channel estimation, uplink transmission spectrum efficiency (SE) have been derived based on the assumption of Rician channel between UAVs and access point (AP). SE optimization algorithm for CF-UAV networks combined with the Angle search and multi-UAV trajectory optimization strategy has been proposed in this paper. Simulation results show that the proposed algorithm performs better performance than comparison schemes, which SE improves by 37% compared with Angle search.

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Smart Supply Chain Management using Big Data Analysis and Machine Learning

Smart Supply Chain Management using Big Data Analysis and Ma...

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2022 International Conference on Edge Computing and Applications, ICECAA 2022

作者： Raviteja, Bhamidipati Pandya, Kartik A. Khan, Falak Khan, Zoheib Tufail Prajwal, R. Kekatpure, Atharva Department of Information Technolgy Gayatri Vidya Parishad College of Engineering Kommadi Visakhapatnam India Department of Mechanical Engineering Sardar Vallabhbhai Patel Institute of Technology Gujarat India Department of Business Administration Aligarh Muslim University Aligarh India Department of Mechanical Engineering Zakir Husain College of Engineering and Technology Aligarh India Department of Electronics and Communication Engineering JSS Academy of Technical Education Bengaluru India Department of Instrumentation and Control Engineering Sarvajanik College of Engineering and Technology Surat India

ISBN: (数字)9781665482325

ISBN: (纸本)9781665482325

Supply chain management (SCM) is concerned with the movement of products, services, and information from points of origin to consumers via a network of interconnected organizations and activities. It is believed that capacity, demand, and cost are well-known variables in typical SCM challenges. In practice, however, there are uncertainties brought on by changes in client demand, supply chain management, organizational risks, and lead times. Demand uncertainty in particular has a significant impact on SC performance with wide-ranging implications for scheduling production, planning inventories, and organizing transportation. In this regard, demand forecasting is a crucial strategy for tackling supply chain uncertainty. Forecasting supply chain demand using big data analytics has been published in the supervised and unsupervised learning categories. In supervised learning, the inputs and outputs are known because the data are tagged with labels. Given a fresh unlabeled dataset, the supervised learning algorithms attempt to map the inputs to matching outputs by identifying the underlying connections between the inputs and outputs. The main motive for the authors is to prove that supply chain can be managed through machine learning and to get a novel accuracy along with comparison of the machine learning models. © 2022 IEEE.

关键词： Supply chain management

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Intelligent Clustering Based Active Power Allocation Strategy for Wind Turbines

Intelligent Clustering Based Active Power Allocation Strateg...

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Smart Grids and Energy Systems (SGES), International Conference on

作者： Zhihong Jiang Kangnan Song Guiyuan Liu Han Wu Han Li Hao Yang School of Electrical Engineering and Information Technology Changchun Institute of Technology Changchun China National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control With Safety Operation Technology Changchun China International Joint Research Center for New Energy Power Generation and Network Control Technology of Jilin Province Changchun China

Aiming at the problem of uneven distribution of active power of each unit in a wind farm, an artificial intelligence clustering method based active power distribution strategy of wind turbine is proposed. Firstly, according to the actual operation data of the wind farm, the Pearson correlation coefficient is used to select the clustering data. Then, the Gaussian mixture model is used for clustering experiments. Finally, according to the clustering results, the distribution method of weight proportional coefficient is adopted to evenly distribute power to all units. The simulation results show that the proposed clustering method has a good evaluation score, and the power allocation strategy based on this can fully meet the scheduling criterias. All units can realize the smooth and orderly power rise and fall in the safe operation state, and avoid the problem of frequent start-stop and overload operation of some units caused by uneven power distribution.

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A Signal Demodulation Algorithm Based on Generative Adversarial Networks 3

A Signal Demodulation Algorithm Based on Generative Adversar...

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3rd IEEE International Conference on Civil Aviation Safety and Information technology, ICCASIT 2021

作者： Lijun, Wang Minghong, Zhang Yu, Han Lei, Shen Science and Technology on Communication Information Security Control Laboratory The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781665425186

In recent years, extensive research has been done to obtain better demodulation performance by combining signal demodulation with deep learning algorithms, such as convolutional neural networks (CNN). However, the demodulation performance of CNN is not much improved compared with traditional coherent demodulation algorithms. This paper proposes a signal demodulation algorithm based on generative adversarial networks (GAN). The proposed GAN-based demodulation network uses the confrontation characteristics between the generator and the discriminator in GAN to greatly improve the demodulation ability of the signal. Numerical results show that the demodulation performance is better than the coherent demodulation algorithm and the CNN-based demodulation algorithm. © 2021 IEEE

关键词： Demodulation

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A Dwt and Anc-Based Continuous Weighing Scheme of Bulk Materials in Belt Conveyor

SSRN

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SSRN 2023年

作者： Kim, Mun Hyok Choe, Ki Yong Pak, Kwang Son Hong, Si Myong Institute of Information Measurement Engineering Faculty of Automatic Engineering Kim Chaek University of Technology Pyongyang Korea People's Democratic Rep Institute of Control Engineering Faculty of Automatic Engineering Kim Chaek University of Technology Pyongyang Korea People's Democratic Rep Faculty of Information Engineering Kim Chaek University of Technology Korea Republic of

To measure accurately the total weight of bulk materials, which are distributed non-uniformly and carried successively on a belt conveyor, and the weight of each packaged product moved in fast speed becomes more important requirement for belt checkweigher. These conveyor-type checkweighers cause errors in weighing due to countless many factors such as structures, installations, operating and environmental conditions. This paper suggests a new hybrid weighing scheme consisting of discrete wavelet transform (DWT) and adaptive noise cancellation (ANC) to calculate weights of bulk materials conveyed continuously. This scheme uses wavelet decomposition and reconstruction to remove noises with high frequencies and uses adaptive filter to suppress noises with low frequencies. The simulation and experimental results show that this scheme removes various types of noises optimally to measure the weight with accuracy degree of ±0.5%. © 2023, The Authors. All rights reserved.

关键词： Adaptive filters

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The Meta Distribution of SINR in UAV-Assisted Cellular Networks

arXiv

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arXiv 2023年

作者： Shi, Minwei Yang, Kai Niyato, Dusit Yuan, Hang Zhou, He Xu, Zhan The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore The Key Laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing100101 China The School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China

Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic line-of-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when UAVs are equipped with steerable antennas, the network coverage and user fairness can be optimized simultaneously by carefully adjusting the UAV parameters. Copyright © 2023, The Authors. All rights reserved.

关键词： Directional patterns (antenna)

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Two Enhanced-Rate Power Allocation Strategies for Active IRS-Assisted Wireless Network

Two Enhanced-Rate Power Allocation Strategies for Active IRS...

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Computer communication and Artificial Intelligence (CCAI), International Conference on

作者： Qiankun Cheng Rongen Dong Wenlong Cai Ruiqi Liu Feng Shu Jiangzhou Wang Hainan University School of Information and Communication Engineering Haikou China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China Wireless and Computing Research Institute ZTE Corporation Beijing China University of Kent School of Engineering Canterbury U.K.

ISBN: (数字)9798350362763

ISBN: (纸本)9798350362770

Due to its ability of overcoming the impact of double-fading effect, active intelligent reflecting surface (IRS) has attracted a lot of attention. Unlike passive IRS, active IRS should be supplied by power, thus adjusting power between base station (BS) and IRS having a direct impact on the system rate performance. In this paper, the active IRS-aided network under a total power constraint is modeled with an ability of adjusting power between BS and IRS. Given the transmit beamforming at BS and reflecting beamforming at IRS, the SNR expression is derived to be a function of power allocation (PA) factor, and the optimization of maximizing the SNR is given. Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed. The former is to improve the rate performance of classic Newton's method to avoid involving a local optimal point by using multiple random initializations. To reduce its high computational complexity, the latter provides a closed-form solution by making use of the first-order Taylor polynomial approximation to the original SNR function. Actually, using TPA, the original optimization problem is transformed into a problem of finding a root for a third-order polynomial. Simulation results are as follows: the first-order TPA of SNR fit its exact expression well, the proposed two PA methods performs much better than fixed PA in accordance with rate, and approaches exhaustive search as the number of IRS reflecting elements goes to large-scale.

关键词： Array signal processing Wireless networks Simulation Polynomials Vectors Resource management Newton method

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Artificial Intelligence-Aid OTFS Receiver: Design and Performance Evaluation

Artificial Intelligence-Aid OTFS Receiver: Design and Perfor...

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Ubiquitous communication (Ucom), International Conference on

作者： Chenxi Wang Li Ping Qian Huijie Zhu College of Information Engineering Zhejiang University of Technology Hangzhou China Science and Technology on Communication Information Security Control Laboratory The 36th Research Institute of China Electronics Technology Jiaxing China

OTFS technology is attracting much attention due to its strong adaptability to high-speed mobility and high spectrum efficiency. Studies show that applying deep learning (DL) to traditional communication systems significantly improves their performance. To this end, this paper proposes an AI-aid OTFS receiver to enhance the performance of OTFS systems in high-speed mobile communication scenarios. The proposed receiver employs two networks - a channel estimation network called TFNet and a decoding network called RecovNet. In the channel estimation module, TFNet performs more accurate channel estimation based on the results of traditional channel estimation methods. In the decoding module, RecovNet decodes the signal based on the equalized signals. To validate the superiority of our proposed receiver, we conduct comparative testing with a traditional receiver under the integer Doppler channel. The experimental results demonstrate that integrating DL technology in OTFS systems effectively enhances their performance.

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Research on frequency control strategy of combined wind- energy storage system

Research on frequency control strategy of combined wind- ene...

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Smart Grids and Energy Systems (SGES), International Conference on

作者： Zhihong Jiang Guiyuan Liu Kangnan Song Han Li Hao Yang Han Wu School of Electrical Engineering and Information Technology Changchun Institute of Technology Changchun China National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control With Safety Operation Technology Changchun China International Joint Research Center for New Energy Power Generation and Network Control Technology of Jilin Province Changchun China

Under the high penetration rate of wind power, the power system puts forward technical requirements for the frequency regulation capability of wind farms. Considering that the frequency response capability of the double-fed induction generator (DFIG) is insufficient, it is proposed to combine energy storage (ES) with wind power for system frequency regulation. Based on the frequency characteristic models of the wind farm and the ES system, this paper establishes a prediction model for the over speed control of the wind farm and a prediction model for the electrochemical energy storage system, and optimizes the active power output of the wind turbine and the energy storage system. The strategy is based on the optimal control of the wind turbine output power and ES power variation, and on this basis, an optimal control model considering the ES state of charge (SOC) and power is designed. The simulation results show that the proposed control strategy can not only effectively suppress grid frequency deviation can also coordinate the ES state of charge and frequency control.

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Renal Anomalies through Ultrasound Imaging and Segmentation Techniques

Renal Anomalies through Ultrasound Imaging and Segmentation ...

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International Conference on Biosignals, Images and Instrumentation (ICBSII)

作者： T. Mangayarkarasi D. Najumnissa Jamal S. Kaja Mohideen Department of Instrumentation and Control Engineering Sri Sairam Engineering College Chennai India B.S. Abdur Rahman Crescent Institute of Science and Technology Chennai India Department of Electronics and Instrumentation Engineering B.S.Abdur Rahman Crescent Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering B.S. Abdur Rahman Crescent Institute of Science and Technology Chennai India

ISBN: (数字)9798350350951

ISBN: (纸本)9798350350968

In present days, the recent encroachment in the medicinal field and abnormality detection methodologies mutually by instrumentation also clinical methods has reached to a height in such a way that the clinical physicians are able to give an appropriate warning for the early detection of any disease and cure. This is widely applied in detecting abnormality of vital organs like kidney, heart, liver, gallbladder, etc. In this proposed work, the detection of prominent abnormalities in kidneys using US scanned images is analyzed using segmentation technique for feature extraction. The extracted features are saved as .csv file in which the significant Max intensity features exceeds threshold value detected as abnormal (cyst, calculi, tumor) image otherwise normal.

关键词： Image segmentation Ultrasonic imaging Instruments Noise Watersheds Feature extraction Medical diagnosis

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