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A Low Complexity Sequential Message Passing Detection Algorithm for RCP-OTFS Systems

IEEE WIRELESS COMMUNICATIONS LETTERS 2025年第4期14卷 964-968页

作者： Xu, Renhe Liang, Yuanyi Huai, Qiwei Yuan, Weina East China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China

Orthogonal Time Frequency Space (OTFS) modulation exhibits excellent bit error rate (BER) performance in high-speed mobile scenarios. However, the two-dimensional modulation of OTFS causes inter-Doppler interference (IDI) in fractional Doppler channel, which reduces channel sparsity and brings higher complexity to signal detection. In this letter, we derive the delay-Doppler (DD) domain input-output relationship in block vector form based on the Reduce Cyclic Prefix-OTFS (RCP-OTFS) systems, and prove that the block channel matrix has column orthogonality under rectangular waveform. Based on this property, a low complexity sequential message passing (SMP) algorithm is proposed to achieve signal detection. The proposed algorithm weights and combines the block received signal and uses the new observation nodes for message transmission. Furthermore, the sequential updates is introduced to sequentially update the information passed from variable nodes to observation nodes. Our simulation results show that the proposed algorithm has lower computational complexity and faster convergence speed compared to the baseline algorithms, and has similar BER performance to the message passing (MP) algorithm.

关键词： Vectors Message passing Delays Interference Bit error rate approximation algorithms Time-frequency analysis Signal detection Receivers Matrix converters OTFS message passing signal detection fractional doppler sequential update

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Optimal Power Flow Incorporating Renewable Energy Sources and FACTS Devices: A Chaos Game Optimization Approach

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IEEE ACCESS 2024年 12卷 23338-23362页

作者： Mohamed, Amal Amin Kamel, Salah Hassan, Mohamed H. Dominguez-Garcia, Jose Luis Aswan Univ Fac Engn Dept Elect Engn Aswan 81542 Egypt Minist Elect & Renewable Energy Cairo 11517 Egypt IREC Catalonia Inst Energy Res St Adria De Besos 08930 Barcelona Spain

This study addresses the optimal power flow (OPF) problem incorporating renewable energy sources (RES) and flexible alternating current transmission systems (FACTS) using the Chaos Game Optimization (CGO) algorithm. Five objective functions are considered, which include minimizing generation costs, emissions, active power loss, voltage deviation, and enhancing voltage profiles. The OPF formulation considers the anticipated electricity production from wind turbines (WT) and photovoltaic (PV) units as dependent variables, while the voltage magnitude at WT and PV buses is treated as a control variable. Probabilistic models based on wind speed and solar irradiance are used to forecast the electrical output of WT and PV units. The proposed OPF methodology and solution method are validated on the IEEE 30-bus test network. This paper introduces and applies four optimization techniques inspired by biological and natural phenomena, namely CGO, Osprey Optimization Algorithm (OOA), RIME Algorithm, and Slime Mould Algorithm (SMA), to address both single-OPF and multi-OPF objective problems in electric power networks. The suggested optimization approaches are tested under different operational scenarios, considering various combinations of FACTS, renewable energy sources (solar PV and wind), and their locations in the network. To predict wind and solar PV power generation, Weibull and lognormal probability density functions are utilized, respectively. The objective function accounts for reserve cost due to overestimation and penalty cost due to underestimation of intermittent solar and wind power. The results demonstrate that the CGO technique is more efficient than other methods in solving OPF instances.

关键词： Renewable energy sources Optimization Heuristic algorithms Generators approximation algorithms Voltage measurement Metaheuristics Wind power generation Solar power generation Photovoltaic systems Renewable energy source wind power generation solar photovoltaic FACTS devices load flow CGO algorithm

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On Optimal Tracking of Rapidly Varying Telecommunication Channels

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2024年 72卷 2726-2738页

作者： Niedzwiecki, Maciej Gancza, Artur Gdansk Univ Technol Fac Elect Telecommun & Comp Sci Dept Signals & Syst PL-80233 Gdansk Poland

When parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the BF approach can be optimized. The paper presents and compares three locally optimized BF algorithms differing in computational requirements. It also demonstrates how the performance of the proposed algorithms can be enhanced in cases where prior knowledge depends on unknown and/or time-varying environmental factors.

关键词： Estimation Signal processing algorithms approximation algorithms Noise Vectors Trajectory Noise measurement Time-varying channels local basis function approach parameter tracking recursive estimation

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Improved approximation algorithms for matroid and knapsack median problems and applications 17

Improved approximation algorithms for matroid and knapsack m...

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17th International Workshop on approximation algorithms for Combinatorial Optimization Problems, APPROX 2014 and the 18th International Workshop on Randomization and Computation, RANDOM 2014

作者： Swamy, Chaitanya Combinatorics and Optimization University Waterloo WaterlooONN2L 3G1 Canada

ISBN: (纸本)9783939897743

We consider the matroid median problem [11], wherein we are given a set of facilities with opening costs and a matroid on the facility-set, and clients with demands and connection costs, and we seek to open an independent set of facilities and assign clients to open facilities so as to minimize the sum of the facility-opening and client-connection costs. We give a simple 8-approximation algorithm for this problem based on LP-rounding, which improves upon the 16-approximation in [11]. We illustrate the power and versatility of our techniques by deriving: (a) an 8-approximation for the two-matroid median problem, a generalization of matroid median that we introduce involving two matroids;and (b) a 24-approximation algorithm for matroid median with penalties, which is a vast improvement over the 360-approximation obtained in [11]. We show that a variety of seemingly disparate facility-location problems considered in the literature-data placement problem, mobile facility location, κ-median forest, metric uniform minimumlatency UFL-in fact reduce to the matroid median or two-matroid median problems, and thus obtain improved approximation guarantees for all these problems. Our techniques also yield an improvement for the knapsack median problem. © Prasad Raghavendra and Tselil Schramm.

关键词： approximation algorithms

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On the Fine-Grained Distributed Routing and Data Scheduling for Interplanetary Data Transfers

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2024年第1期21卷 451-462页

作者： Tian, Xiaojian Zhu, Zuqing Univ Sci & Technol China Sch Informat Sci & Technol Hefei 230027 Anhui Peoples R China

Interplanetary networks (IPNs) are complex communication infrastructures used for data exchange among spacecrafts, rovers and ground stations. Due to the significant delay and uncertainty in communications, efficient routing and data scheduling of interplanetary data transfer (IP-DT) becomes crucial. With the increase of deep space (DS) exploration missions, it would be difficult for existing IPNs to cope with the growing of IP-DT demands. In this work, to improve the performance of IP-DTs in IPNs, we formulate an integer linear programming (ILP) model and design an effective fine-grained distributed routing and data scheduling (FD-RDS) algorithm based on it. We prove that the proposed algorithm is a polynomial-time 2-approximation algorithm for solving the ILP model. Extensive simulations show that our proposals can significantly improve the efficiency and reliability of IPNs. Specifically, our proposals outperforms known benchmarks in terms of both the delivery ratio and E2E latency of IP-DTs.

关键词： Routing Scheduling Distributed databases Delays Topology approximation algorithms Network topology Interplanetary network delay tolerant network distributed route selection distributed scheduling

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Accelerated Path Planning for Large-Scale Grid Maps

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IEEE ACCESS 2024年 12卷 121792-121807页

作者： Sun, Duohang Sun, Zhe Shao, Peinan China Elect Technol Grp Corp Res Inst 32 Shanghai 200000 Peoples R China

Path planning is a critical task in automated navigation and seeks to identify optimal collision-free routes for autonomous systems such as unmanned vehicles, aircrafts, and surface ships within a specified environment. The rapid computation of optimal paths in large-scale grid maps remains a major challenge. This paper presents an enhanced HPA* pathfinding algorithm that utilizes an abstract representation of grid maps to facilitate fast navigation. The enhancements to the HPA* algorithm include a detailed examination of neighborhood branch extensions, the incorporation of a high-quality heuristic function, and the implementation of repulsive force fields. The effectiveness of this improved HPA* algorithm in large-scale grid environments is demonstrated by extensive experiments in real-world settings. In terms of computational efficiency, for path planning in real scenarios, the computation time of the HPA* Improved algorithm can be reduced by more than 95% relative to the A* algorithm, and the computation time can still be reduced by more than 80% relative to the HPATheta* algorithm, even though the computation time can be reduced by more than 80%. Even compared to HPATheta* algorithm, the computation time can still be reduced by more than 80%. Specifically, the improved HPA* algorithm significantly reduces the time required to generate path results while also enhancing path safety. This study provides valuable insights into advanced pathfinding techniques that could advance automated navigation systems.

关键词： Path planning Heuristic algorithms Computational efficiency approximation algorithms Optimization Aircraft navigation Remotely guided vehicles Navigation Collision avoidance Abstract map improved HPA large-scale maps path planning

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A Review on the Applications of Reinforcement Learning Control for Power Electronic Converters

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2024年第6期60卷 8430-8450页

作者： Chen, Peng Zhao, Jianfeng Liu, Kangli Zhou, Jingyang Dong, Kun Li, Yufan Guo, Xirui Pan, Xin Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China Nanjing Forestry Univ Coll Informat Sci & Technol Nanjing 210037 Peoples R China

In modern micro-grid systems, the control of power electronic converters faces numerous challenges, including the uncertainty of parameters of the controlled objects, variations in the operating environment, and the increased complexity of models for controlled objects. Meanwhile, traditional control strategies for power electronic converters are characterized by high model dependency, slow dynamic response, and static control parameters, which make them inappropriate for the development of modern micro-grid systems. In response to this problem, researchers have proposed reinforcement learning (RL) control strategies to achieve fast adaptive control through real-time interaction with the environment. However, there is currently a lack of comprehensive literature reviews specifically focusing on RL control for power electronic converters. To fill this gap, this article provides a summary of existing published research papers. Specifically, the mainstream RL algorithms are listed. The existing RL control strategies for various power electronic converter topologies are introduced. The sim-to-real methods for practical implementation are illustrated. The underlying design considerations are discussed. Moreover, the future research prospects are explored.

关键词： Power electronics Classification algorithms Artificial neural networks approximation algorithms Accuracy Estimation Convergence Power electronic converter reinforcement learning control strategy model-free control

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Eye-Gaze Tracking Based on Head Orientation Estimation Using FMCW Radar Sensor

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Jung, Jaehoon Kim, Jihye Kim, Seong-Cheol Lim, Sohee Seoul Natl Univ SNU Dept Elect & Comp Engn Seoul 08826 South Korea Seoul Natl Univ SNU Inst New Media & Commun INMC Seoul 08826 South Korea Samsung Res Robot Syst Team Samsung Elect Seoul 06765 South Korea

In this article, we propose an eye-gaze tracking method based on head orientation estimation that uses a single 60-GHz frequency-modulated continuous-wave (FMCW) radar sensor. The FMCW radar data are acquired for cases, in which the radar is illuminating the front or side of the face. Because the variation in facial muscles caused by eye blinking is more pronounced when a human gazes at the radar, the orientation of the human head can be estimated by analyzing the received radar signal. First, an approximate range-angle map is generated to identify whether a human exists. When a human is detected, the received signal is projected onto the lower subspace of interest. Subsequently, a super-resolution algorithm is applied to the projected signal to obtain a precise target spectrum. The accumulated spectrogram is used as input to MobileNet to classify radar signal images corresponding to different orientations of the human head. The classification results show that the proposed method can identify the orientation of a human head with an accuracy exceeding 90%.

关键词： Radar Radar tracking Estimation Radar detection Radar antennas Multiple signal classification Monitoring approximation algorithms Receiving antennas Head Eye-gaze tracking frequency-modulated continuous-wave (FMCW) radar head orientation MobileNet neural network super-resolution

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AoI-Aware, Digital Twin-Empowered IoT Query Services in Mobile Edge Computing

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IEEE-ACM TRANSACTIONS ON NETWORKING 2024年第4期32卷 3636-3650页

作者： Li, Jing Guo, Song Liang, Weifa Wu, Jie Chen, Quan Xu, Zichuan Xu, Wenzheng Wang, Jianping City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Guangdong Univ Technol Sch Comp Guangzhou 510006 Peoples R China Dalian Univ Technol Sch Software Dalian 116620 Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610000 Peoples R China

The Mobile Edge Computing (MEC) paradigm gives impetus to the vigorous advancement of the Internet of Things (IoT), through provisioning low-latency computing services at network edges. The emerging digital twin technique has been explosively growing in the IoT community, which bridges the gap between physical objects and their digital representations in an MEC network, enabling real-time monitoring and analysis, simulations on the dynamics of systems, accurate predictions on behaviours of objects, and optimization on network resource allocation. In this paper, we consider AoI-aware query services in an MEC network empowered by digital twin technology for diverse IoT applications. We aim to maximize the weighted sum of the accumulative freshness of query results measured by the Age of Information (AoI) and the total query service delay of admitted requests. To this end, we first formulate a novel minimization problem that explores nontrivial trade-offs between the two conflicting optimization objectives: the freshness of query results and service delays, and we show the NP-hardness of the problem. Then, we propose an approximation algorithm with a provable approximation ratio for the problem, at the expense of bounded computing capacity violations. We also develop a heuristic for the problem without any capacity violations. We finally evaluate the performance of the proposed algorithms via simulations. The simulation results demonstrate that the proposed algorithms are promising, and outperform the comparison benchmarks.

关键词： Internet of Things Digital twins Delays approximation algorithms Sensors Heuristic algorithms Data models Digital twin mobile edge computing query services age of information IoT applications service delays approximation algorithms resource allocation optimization

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AoI-Aware Service Provisioning in Edge Computing for Digital Twin Network Slicing Requests

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第12期23卷 14607-14621页

作者： Li, Jing Guo, Song Liang, Weifa Wang, Jianping Chen, Quan Hong, Zicong Xu, Zichuan Xu, Wenzheng Xiao, Bin City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China Guangdong Univ Technol Sch Comp Guangzhou 510006 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Dalian Univ Technol Sch Software Dalian 116024 Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610065 Peoples R China

Digital twins are poised to enter our lives with Industry 4.0. The Digital Twin Network (DTN) paradigm is projected to deliver upon the promise of efficient collaboration among digital twins to enable complicated and systematic services across many domains, through depicting an overall picture of a group of physical objects. To achieve timely data processing of digital twins, Mobile Edge Computing (MEC) shifts the computational power towards the network edge, and network slicing is well-suited to bundle heterogeneous physical resources to build logical networks based on edge servers for accommodating DTNs. In light of this, in this paper we investigate DTN slicing-enabled service provisioning in MEC, where each DTN slice consists of one master digital twin and a set of worker digital twins, and each worker digital twin is synchronized through collecting data from a respective object periodically. The master digital twin aggregates the processed data from worker digital twins to model the DTN continuously for user query services, whilst meeting delay requirements of users. We capture the utility gain of a DTN slicing request based on the DTN model quality at its master digital twin that is impacted by the Age of Information (AoI), and we focus on two novel optimization problems: the utility maximization problem for a single DTN slicing request, and the dynamic utility maximization problem for multiple DTN slicing requests. We propose an approximation algorithm for the former, and an online algorithm with a provable competitive ratio for the latter. We also evaluate the performance of the proposed algorithms through simulations. Experimental results demonstrate that the proposed algorithms are promising, outperforming their counterparts by at least 10.2%.

关键词： Digital twins Heuristic algorithms approximation algorithms Network slicing Delays Data models Synchronization Digital twin mobile edge computing network slicing request age of information approximation algorithm online algorithm and resource allocation

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