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A multi-input single-output thermal management system design for liquid metal batteries

APPLIED THERMAL ENGINEERING 2023年第PartB期219卷

作者： Zhang, Yi Wang, Sheng Guo, Zhenlin Li, Haomiao Jiang, Kai Zhou, Min Huazhong Univ Sci & Technol HUST Sch Elect & Elect Engn State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Power Safety & Efficiency Wuhan 430074 Peoples R China

Liquid metal battery, with three-liquid-layer structure and high operating temperature, is a novel battery technology that shows great potential in grid energy storage. However, unlike lithium-ion batteries, liquid metal batteries are supposed to be heated to a high temperature before operation. Both temperature uniformity among cells and total energy consumption minimization is demanded in the preheating process. In this paper, an efficient thermal management controller design is proposed to optimize the temperature uniformity and energy consumption. Different from previous work, this design replaces the conventional single-input single-output controller with a multi-input single-output controller, which samples temperatures at different locations to control the heating rate. Experimental results show that the final controller error reaches a value of 1.2%. Based on the thermal management system design, a preheating strategy is further proposed to achieve the optimal balance between temperature uniformity and energy consumption. Compared with common strategies, the maximum temperature difference is reduced by 13.7% to 49.85 degrees C, and the energy consumption is reduced by 6.7% of the total module energy to 6.33 kWh. It is demonstrated in this study that the proposed thermal management system and heating strategy essentially improves the heating process of liquid metal battery stack.

关键词： Liquid metal battery Thermal management system multi-input single-output Temperature sensor array Temperature difference Energy consumption

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Joint Association, Beamforming, and Resource Allocation for multi-IRS Enabled MU-MISO Systems With RSMA

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第3期24卷 1602-1620页

作者： Wang, Chunjie Zhang, Xuhui Xing, Huijun Xue, Liang Wang, Shuqiang Shen, Yanyan Yang, Bo Guan, Xinping Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Hebei Univ Engn Sch Informat & Elect Engn Handan 056038 Peoples R China Hebei Key Lab Secur & Protect Informat Sensing & P Handan 056038 Peoples R China Chinese Univ Hong Kong Future Network Intelligence Inst Sch Sci & Engn Shenzhen 518172 Guangdong Peoples R China Chinese Univ Hong Kong Guangdong Prov Key Lab Future Networks Intelligenc Shenzhen 518172 Guangdong Peoples R China Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England Chinese Univ Hong Kong Future Network Intelligence Inst Sch Sci & Engn Shenzhen 518172 Guangdong Peoples R China Enterprise Innovat Ctr Energy Internet Sch Cloud Data Sensing Intelligence Handan 056002 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Minist Educ Shanghai 200240 Peoples R China

Intelligent reflecting surface (IRS) and rate-splitting multiple access (RSMA) technologies are at the forefront of enhancing spectrum and energy efficiency in the next generation multi-antenna communication systems. This paper explores a RSMA system with multiple IRSs, and proposes two purpose-driven scheduling schemes, i.e., the exhaustive IRS-aided (EIA) and opportunistic IRS-aided (OIA) schemes. The aim is to optimize the system weighted energy efficiency (EE) under the above two schemes, respectively. Specifically, the Dinkelbach, branch and bound, successive convex approximation, and the semidefinite relaxation methods are exploited within the alternating optimization framework to obtain effective solutions to the considered problems. The numerical findings indicate that the EIA scheme exhibits better performance compared to the OIA scheme in diverse scenarios when considering the weighted EE, and the proposed algorithm demonstrates superior performance in comparison to the baseline algorithms.

关键词： Intelligent reflecting surface rate-splitting multiple access multi-input single-output energy efficiency beamforming Intelligent reflecting surface rate-splitting multiple access multi-input single-output energy efficiency beamforming

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Identification of MISO Hammerstein Nonlinear Model with Moving Average Noise Based on Hybrid Signal 12

Identification of MISO Hammerstein Nonlinear Model with Movi...

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IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)

作者： Zhao, Caiting Ding, Zhenyu Li, Feng Jiangsu Univ Technol Coll Elect & Informat Engn Changzhou 213001 Jiangsu Peoples R China

ISBN: (纸本)9798350321050

The hybrid signal is used to identify the multi-input single-output (MISO) Hammerstein model. The hybrid signal consists of Gaussian signal and random signal, and the identification process is divided into two stages, namely, the stage of dynamic linear part and the stage of static nonlinear part. Firstly, the correlation analysis method is used to identify the linear part parameters. Then, for the parameters of the nonlinear part and the output noise model, an extended stochastic gradient algorithm with forgetting factor (FF-ESG) is adopted to deal with the issue that the convergence of stochastic gradient algorithm is slow. Theoretical analysis and experiments show that the presented method can identify the MISO Hammerstein model with moving average noise and obtain good identification accuracy.

关键词： Hammerstein model parameter identification correlation analysis method multi-input single-output

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Distributed Coordinated Beamforming Based on multi-Agent Reinforcement Learning in multicell MISO Systems

Distributed Coordinated Beamforming Based on Multi-Agent Rei...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Bai, Shaozhuang Gao, Zhenzhen Liao, Xuewen Xi An Jiao Tong Univ Dept Informat & Commun Engn Xian Shaanxi Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing Peoples R China

ISBN: (数字)9781665484800

ISBN: (纸本)9781665484800

Maximizing the sum-rate in multicell multiple input single output (MISO) systems is a non convex and NP-hard problem. Most existing algorithms trying to solve this problem are suboptimal with high computational cost and high system interaction overhead. In this paper, we propose a coordinated beamforming (CB) scheme based on multi-agent reinforcement learning (MARL) to maximize the sum-rate of the multicell MISO systems with limited information feedback and exchange. Specifically, the training of the proposed MARL network is guided by the actual sum-rate of the multiple cells, and the execution is performed totally locally by using the local channel quality information feedback. Simulation results show that compared to the existing distributed coordinated beamforming scheme, the proposed scheme achieves similar performance by using much reduced information overhead.

关键词： Coordinated beamforming multi-agent reinforcement learning multi-input single-output multicell systems

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Leveraging Active and Nearly Passive Reconfigurable Intelligent Surfaces Using Deep Learning Algorithm for 6G Wireless Networks

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2025年第5期36卷

作者： Megahed, Amal Elmesalawy, Mahmoud M. Abd El-Haleem, Ahmed. M. Ibrahim, Ibrahim I. Helwan Univ Fac Engn Dept Elect & Commun Engn Cairo Egypt

Active Reconfigurable Intelligent Surface (ARIS) shows promise in boosting the desired signal at the receiver user. However, the "fully-connected" architecture of ARIS needs high power due to additional active components. This paper adopts sub-connected ARIS to enhance achieved data rates with good energy efficiency at the Cell Edge Users (CEUs) and addresses the "multiplicative fading" effect caused when the signal propagates through a longer path (i.e., the serving Base Station (BS)-ARIS-CEU) than the straight route across the serving BS and the CEUs. Additionally, a Nearly Passive RIS (NP-RIS) is proposed to mitigate interfering signals from other BSs by creating destructive interference at the CEUs. The reflection matrix of the NP-RIS is extracted using Deep Learning (DL) techniques, with a select few NP-RIS reflecting elements being active. This model improves achieved data rates by around 58% for M = 16 RIS elements compared with the baseline model with the same number of elements in NP-RIS without ARIS implementation. Moreover, the proposed model enhances data rates by approximately 31.8% compared with a baseline using negative resistance Reflecting Elements (RE). However, the Spectral Energy Efficiency (SEE) using the second baseline will be improved over the "fully-connected" ARIS leading to the sub-connected ARIS solution to improve the SEE by nearly 25%.

关键词： active reconfigurable intelligent surface beamforming deep learning multi-input single-output nearly-passive reconfigurable intelligent surface spectral energy efficiency

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Nonlinear coded nonuniform superposition QAM by trellis-coding for MISO system in visible light communication

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Chinese Optics Letters 2022年第4期20卷 71-76页

作者： Zengyi Xu Wenqing Niu Jianyang Shi Nan Chi Key Laboratory for Information Science of Electromagnetic Waves(MoE) Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Peng Cheng Laboratory Shenzhen 518055China

In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superposition(NCNS)*** aim is to alleviate the nonlinearity effect caused by high instantaneous power in multi-input single-output(MISO)visible light communication(VLC)system,with an uneven probabilistic-shaped *** transmitter includes two LEDs to send signals independently,and the receiver uses a photo detector to receive the superposed QAM *** experiment results show that NCNS has a better robustness against nonlinearity than pulse amplitude modulation 4,approximately gaining a 16% increase in maximum usable peak-to-peak voltage and a 33% enlargement in dynamic range *** is a simple but effective approach to solve the bandwidth limits related to signal power and hopefully be applied in large power VLC systems such as underwater VLC,or to improve the robustness against power fluctuation.

关键词： visible light communication light-emitting diode multi-input single-output quadrature amplitude modulation nonlinear coding spectral shaping

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Novel hybrid approaches based on evolutionary strategy for streamflow forecasting in the Chellif River, Algeria

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ACTA GEOPHYSICA 2020年第1期68卷 167-180页

作者： Zakhrouf, Mousaab Bouchelkia, Hamid Stamboul, Madani Kim, Sungwon Univ Tlemcen Fac Technol Dept Hydraul URMER Lab Tilimsen Algeria Amar Telidji Univ Fac Architecture & Civil Engn Dept Civil Engn Res Lab Water Resources Soil & Environm Laghouat Algeria Dongyang Univ Dept Railroad Construct & Safety Engn Yeongju 36040 South Korea

In this study, the feedforward neural networks (FFNNs) were proposed to forecast the multi-day-ahead streamflow. The parameters of FFNNs model were optimized utilizing genetic algorithm (GA). Moreover, discrete wavelet transform was utilized to enhance the accuracy of FFNNs model's forecasting. Therefore, the wavelet-based feedforward neural networks (WFFNNs-GA) model was developed for the multi-day-ahead streamflow forecasting based on three evolutionary strategies [i.e., multi-input multi-output (MIMO), multi-input single-output (MISO), and multi-input several multi-output (MISMO)]. In addition, the developed models were evaluated utilizing five different statistical indices including root mean squared error, signal-to-noise ratio, correlation coefficient, Nash-Sutcliffe efficiency, and peak flow criteria. Results provided that the statistical values of WFFNNs-GA model based on MISMO evolutionary strategy were superior to those of WFFNNs-GA model based on MISO and MIMO evolutionary strategies for the multi-day-ahead streamflow forecasting. Results indicated that the performance of WFFNNs-GA model based on MISMO evolutionary strategy provided the best accuracy. Results also explained that the hybrid model suggested better performance compared with stand-alone model based on the corresponding evolutionary strategies. Therefore, the hybrid model can be an efficient and robust implement to forecast the multi-day-ahead streamflow in the Chellif River, Algeria.

关键词： Daily streamflow forecasting Wavelet transform Feed forward neural networks multi-input multi-output multi-input single-output multi-input several multi-output Chellif River

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Intrinsic Robustness of MISO Visible Light Communications: Partial CSIT Can be as Useful as Perfect One

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第2期67卷 1297-1312页

作者： Zhang, Yan-Yu Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450000 Henan Peoples R China

We consider a multi-input single-output visible light communication (MISO-VLC) system. For such system under both average and peak optical power constraint, an optimal space constellation maximizing the received minimum Euclidean distance is attained among all the feasible sets, respectively, for the case with or without channel state information at the transmitter (CSIT). These designs demonstrate that the optimal transmission only requires CSIT which is related to the possibilities of the echelon arrangement of the channel coefficients and jointly determined by the power regime and the ordering of channel coefficient values. Our findings point out that it is not necessary to probe the exact value of the MISO-VLC channel vector and limited CSIT can sufficiently guarantee the intrinsic robustness. In addition, the optimal designs admit low-complexity maximum likelihood detection. These properties make our proposed optimal designs especially attractive in such channels.

关键词： Visible light communications multi-input single-output channel state information intrinsic robustness

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Constellation-Optimal Beamformers for multiuser MISO Broadcast Visible Light Communications

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第6期65卷 3848-3870页

作者： Zhang, Yan-Yu Yu, Hong-Yi Zhang, Jian-Kang Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450000 Peoples R China McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

In this paper, we design energy-efficient space constellations for multiuser multi-input single-output visible light communication broadcast systems with channel state information (CSI) at the receiver in the three scenarios: 1) with CSI at the transmitter (CSIT);2) with statistical CSIT;and 3) without CSIT. By utilizing the cooperation of multiuser interference, optimal multidimensional additively uniquely decomposable constellation groups are designed to optimize the received worst case performance metrics of all users subject to two commonly used power constraints, i.e., average and peak optical power constraints. The resulting optimal designs are proved to be pulse amplitude modulated with an optimal beamformer, which can be efficiently attained by numerical search for Scenarios 1 and 2 and be given in a closed form for Scenario 3. One of the common significant advantages of these designs is the fast demodulation of the sum signal from a noisy received signal, since these optimal designs result in an equivalent ideal scalar AWGN channel. Comprehensive computer simulations demonstrate that our designs significantly outperform traditional zero-forcing, minimum mean square error, and time-division methods.

关键词： Additively uniquely decomposable constellation group broadcast channels maximum likelihood detection multi-input single-output optimal multidimensional constellation and visible light communications

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Deinterleaving of Mixtures of Renewal Processes

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2019年第4期67卷 885-898页

作者： Young, Jeremy Host-Madsen, Anders Nosal, Eva-Marie Univ Hawaii Manoa Dept Elect Engn Honolulu HI 96822 USA Shenzhen Res Inst Big Data Shenzhen Peoples R China Univ Hawaii Manoa Dept Ocean & Resources Engn Honolulu HI 96822 USA

This paper proposes a new method for impulsive source separation (deinterleaving) in multi-input single-output systems based purely on impulse spacing. The impulse spacing for each source is modeled as a renewal process. To classify sources, an algorithm is developed to maximize the likelihood of impulse assignment based on the impulse spacing distributions. A theoretical lower bound on performance is derived and the algorithm is shown to get reasonably close to the bound. The algorithm is extended for use when the impulse spacing distribution parameters are unknown. Performance is evaluated on multiple application examples.

关键词： Deinterleaving click trains jitttered PRI radar source separation renewal process marine mammals impulsive sources multi-input single-output

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