This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactiv...
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This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.
We consider the multiobjective optimization problem for the resource allocation of the multiagent network, where each agent contains multiple conflicting local objective functions. The goal is to find compromise solut...
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We consider the multiobjective optimization problem for the resource allocation of the multiagent network, where each agent contains multiple conflicting local objective functions. The goal is to find compromise solutions minimizing all local objective functions subject to resource constraints as much as possible, i.e., the Pareto optimums. To this end, we first reformulate the multiobjective optimization problem into one single-objective distributed optimization problem by using the weighted Lppreference index,where the weighting factors of all local objective functions are obtained from the optimization procedure so that the optimizer of the latter is the desired Pareto optimum of the former. Next, we propose novel predefined-time algorithms to solve the reformulated problem by time-based generators. We show that the reformulated problem is solved within a predefined time if the local objective functions are strongly convex and smooth. Moreover, the settling time can be arbitrarily preset since it does not depend on the initial values and designed parameters. Finally, numerical simulations are presented to illustrate the effectiveness of the proposed algorithms.
The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Rec...
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The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Recognition(HAR)***,the significant computational demands and memory requirements hinder the practical deployment of deep networks in resource-constrained *** paper introduces a novel network pruning method based on the energy spectral density of data in the frequency domain,which reduces the model’s depth and accelerates activity *** traditional pruning methods that focus on the spatial domain and the importance of filters,this method converts sensor data,such as HAR data,to the frequency domain for *** emphasizes the low-frequency components by calculating their energy spectral density ***,filters that meet the predefined thresholds are retained,and redundant filters are removed,leading to a significant reduction in model size without compromising performance or incurring additional computational ***,the proposed algorithm’s effectiveness is empirically validated on a standard five-layer CNNs backbone *** computational feasibility and data sensitivity of the proposed scheme are thoroughly ***,the classification accuracy on three benchmark HAR datasets UCI-HAR,WISDM,and PAMAP2 reaches 96.20%,98.40%,and 92.38%,***,our strategy achieves a reduction in Floating Point Operations(FLOPs)by 90.73%,93.70%,and 90.74%,respectively,along with a corresponding decrease in memory consumption by 90.53%,93.43%,and 90.05%.
This paper presents assessment of system strength of an emerging distribution system with high penetration of photovoltaic (PV) generators. Existence of low damped oscillatory modes due to control system interaction i...
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Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the...
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Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the state estimator as a function of perturbations in the input *** has already been shown that evaluating performance based only on the test dataset might not effectively indicate the ability of a trained DNN to handle input *** such,we analytically verify the robustness and trustworthiness of DNNs to input perturbations by treating them as mixed-integer linear programming(MILP)*** ability of batch normalization in addressing the scalability limitations of the MILP formulation is also *** framework is validated by performing time-synchronized distribution system state estimation for a modified IEEE 34-node system and a real-world large distribution system,both of which are incompletely observed by micro-phasor measurement units.
Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the desig...
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Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the design of sequential scanning beams for target detection with the required sensing resolution has not been tackled in the *** bridge this gap, this paper introduces a resolution-aware beam scanning design. In particular, the transmit information beamformer, the covariance matrix of the dedicated radar signal, and the receive beamformer are jointly optimized to maximize the average sum rate of the system while satisfying the sensing resolution and detection probability requirements.A block coordinate descent(BCD)-based optimization framework is developed to address the non-convex design problem. By exploiting successive convex approximation(SCA), S-procedure, and semidefinite relaxation(SDR), the proposed algorithm is guaranteed to converge to a stationary solution with polynomial time complexity. Simulation results show that the proposed design can efficiently handle the stringent detection requirement and outperform existing antenna-activation-based methods in the literature by exploiting the full degrees of freedom(DoFs) brought by all antennas.
AC optimal power flow (AC OPF) is a fundamental problem in power system operations. Accurately modeling the network physics via the AC power flow equations makes AC OPF a challenging nonconvex problem. To search for g...
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A numerical model of the bearing fault of a motor with a closed-slot rotor using the finite element method(FEM)is *** rotor’s radial motion can be regarded as static eccentric at the defect time points and healthy at...
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A numerical model of the bearing fault of a motor with a closed-slot rotor using the finite element method(FEM)is *** rotor’s radial motion can be regarded as static eccentric at the defect time points and healthy at other time *** frequency of the harmonic component is analyzed corresponding to bearing fault in stator current according to the radial movement of the motor ***,the relative permeability variation region is established to achieve the radial motion of the rotor with bearing ***,the relative permeability variation region is established in the health and static eccentric ***,the defect time points are estimated and the static eccentricity model by transient field is ***,the relative permeability of the variable region in the static eccentric model is imported into the variable region of the health model at the defect time *** simulation results show that the air gap flux density of the bearing fault model is different from that of the health model and static eccentric *** addition,the stator current contains harmonic components of the bearing *** analysis results prove the applicability of the proposed model.
The development of DC custom power protection devices is still in infancy that confines the sensitive loads integrated into medium-voltage(MV) and low-voltage(LV) DC networks. Considering the DC doubly-fed induction g...
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The development of DC custom power protection devices is still in infancy that confines the sensitive loads integrated into medium-voltage(MV) and low-voltage(LV) DC networks. Considering the DC doubly-fed induction generator(DCDFIG) based wind energy conversion system(WECS), this paper proposes a dual active bridge(DAB) based DC unified power quality conditioner(DC-UPQC) with the integration of superconducting magnetic energy storage(SMES) to maintain the terminal voltage of DC-DFIG and regulate the current flow. The principle of the proposed DC-UPQC has three parts, i.e., parallel-side DAB(PDAB), series-side DAB(SDAB), and SMES,used for the voltage compensation, current and power regulation, and energy storage, respectively. The circuit principle of the PDAB and SDAB and the modeling of SMES are analyzed in this paper. A DC dual control strategy is also proposed to deal with the DC voltage oscillation generated by the AC-side asymmetrical fault. A case study of DC-DFIG interfaced with DC power grid is carried out, integrated with the proposed SMES-based DC-UPQC to verify the high-power applications of the proposed structure. Finally, an experiment is implemented, and the results demonstrate the correctness of the theoretical analysis and the feasibility of the proposed structure.
This paper investigates the input-to-state stabilization of discrete-time Markov jump systems. A quantized control scheme that includes coding and decoding procedures is proposed. The relationship between the error in...
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