Broadband Tunable Passively Q-Switched Erbium-Doped ZBLAN Fiber Laser Using Fe3O4-Nanoparticle Saturable Absorber

We experimentally demonstrate a passively Q-switched wavelength tunable 2.8 μm erbium-doped fiber laser. Fe3O4 nanoparticles deposited on a gold mirror are used as a saturable absorber (SA). Stable Q-switched pulses within the tunable range of 2710–2810 nm are obtained. At the wavelength of 2760 nm, a maximum Q-switched output power of 188 mW is achieved with a repetition rate of 115.8 kHz and a pulse width of 1.3 μs. The corresponding pulse energy is 1.68 μJ. This demonstration shows the ability of Fe3O4 to function as a broadband mid-infrared SA

Low-complexity joint power allocation and trajectory design for UAV-enabled secure communications with power splitting

An unmanned aerial vehicle (UAV)-aided secure communication system is conceived and investigated, where the UAV transmits legitimate information to a ground user in the presence of an eavesdropper (Eve). To guarantee the security,the UAV employs a power splitting approach, where its transmit power can be divided into two parts for transmitting confidential messages and artificial noise (AN), respectively. We aim to maximize the average secrecy rate by jointly optimizing the UAVs trajectory, the transmit power levels and the corresponding power splitting ratios allocated to different time slots during the whole flight time, subject to both the maximum UAV speed constraint, the total mobility energy constraint, the total transmit power constraint, and other related constraints. To efficiently tackle this non-convex optimization problem, we propose an iterative algorithm by blending the benefits of the block coordinate descent (BCD) method, the concave-convex procedure (CCCP) and the alternating direction method of multipliers (ADMM). Specially, we show that the proposed algorithm exhibits very low computational complexity and each of its updating steps can be formulated in a nearly closed form. Besides, it can be easily extended to the case of three-dimensional (3D) trajectory design. Our simulation results validate the efficiency of the proposed algorith

MIMO-aided nonlinear hybrid transceiver design for multiuser mmWave systems relying on Tomlinson-Harashima precoding

Hybrid analog-digital (A/D) transceivers designed for millimeter wave (mmWave) systems have received substantial research attention, as a benefit of their lower cost and modest energy consumption compared to their fully-digital counterparts. We further improve their performance by conceiving a Tomlinson-Harashima precoding (THP) based nonlinear joint design for the downlink of multiuser multiple-input multipleoutput (MIMO) mmWave systems. Our optimization criterion is that of minimizing the mean square error (MSE) of the system under channel uncertainties subject both to realistic transmit power constraint and to the unit modulus constraint imposed on the elements of the analog beamforming (BF) matrices governing the BF operation in the radio frequency domain. We transform this optimization problem into a more tractable form and develop an efficient block coordinate descent (BCD) basedalgorithm for solving it. Then, a novel two-timescale nonlinear joint hybrid transceiver design algorithm is developed, which can be viewed as an extension of the BCD-based joint design algorithm for reducing both the channel state information (CSI) signalling overhead and the effects of outdated CSI. Moreover, we determine the near-optimal cancellation order for the THP structure based on the lower bound of the MSE. The proposed algorithms can be guaranteed to converge to a Karush-Kuhn-Tucker (KKT) solution of the original problem. The simulation results demonstrate that our proposed nonlinear joint hybrid transceiver design algorithms significantly outperform the existing linear hybrid transceiver algorithms and approach the performance of the fully-digital transceiver, despite its lower cost and power dissipation

State of Health Diagnosis and Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Multi-Feature Data and Mechanism Fusion

State of Health (SOH) Diagnosis and Remaining Useful Life (RUL) Prediction of lithium-ion batteries (LIBs) are subject to low accuracy due to the complicated aging mechanism of LIBs. This paper investigates a SOH diagnosis and RUL prediction method to improve prediction accuracy by combining multi-feature data with mechanism fusion. With the approach of the normal particle swarm optimization, a support vector regression (SVR)-based SOH diagnosis model is developed. Compared with existing works, more comprehensive features are utilized as the feature variables, including three aspects: the representative feature during a constant-voltage protocol; the capacity; internal resistance. Further, the optimized regularized particle filter (ORPF) model with uncertainty expression is integrated to obtain more accurate RUL prediction and SOH diagnosis. Experiments validate the effectiveness of the proposed method. Results show that the proposed SOH diagnosis and RUL prediction method has higher accuracy and better stability compared with the traditional methods, which help to realize the decision of the maintenance process

Secrecy rate maximization of RIS-assisted SWIPT systems: A two-timescale beamforming design approach

Reconfigurable intelligent surfaces (RISs) achieve high passive beamforming gains for signal enhancement or interference nulling by dynamically adjusting their reflection coefficients. Their employment is particularly appealing for improving both the wireless security and the efficiency of radio frequency (RF)-based wireless power transfer. Motivated by this, we conceive and investigate a RIS-assisted secure simultaneous wireless information and power transfer (SWIPT) system designed for information and power transfer from a base station (BS) to an information user (IU) and to multiple energy users (EUs), respectively. Moreover, the EUs are also potential eavesdroppers that may overhear the communication between the BS and IU. We adopt two-timescale transmission for reducing the signal processing complexity as well as channel training overhead, and aim for maximizing the average worstcase secrecy rate achieved by the IU. This is achieved by jointly optimizing the short-term transmit beamforming vectors at the BS (including information and energy beams) as well as the long-term phase shifts at the RIS, under the energy harvesting constraints considered at the EUs and the power constraint at the BS. The stochastic optimization problem formulated is nonconvex with intricately coupled variables, and is non-smooth due to the existence of multiple EUs/eavesdroppers. No standard optimization approach is available for this challenging scenario. To tackle this challenge, we propose a smooth approximation aided stochastic successive convex approximation (SA-SSCA) algorithm. Furthermore, a low-complexity heuristic algorithm is proposed for reducing the computational complexity without unduly eroding the performance. Simulation results show the efficiency of the RIS in securing SWIPT systems. The significant performance gains achieved by our proposed algorithms over the relevant benchmark schemes are also demonstrated

Two-timescale hybrid analog-digital beamforming for mmWave full-duplex MIMO multiple-relay aided systems

Due to the severe pathloss experienced by electromagnetic wave transmission in the mmWave band, one challenge for the design of millimeter wave (mmWave) communication systems is coverage extension. Aiming to improve the coverage and sum rate performance of mmWave communications, we investigate new schemes for the design of full-duplex (FD) mmWave multiple-input multiple-output (MIMO) multiple-relay systems. Specifically, we propose a novel two-timescale analog-digital hybrid beamforming scheme to maximize the sum rate, while reducing the system complexity and channel state information (CSI) signalling overhead, as well as mitigating the effects of self interference and CSI errors caused by the delays. In the proposed scheme, the long-timescale analog beamforming matrices are designed based on the available channel statistics and updated in a frame-based manner, where a frame contains a fixed number of time slots, while for each time slot, the short-timescale digital beamforming matrices are optimized based on low-dimensional effective CSI matrices available in real-time. We develop an effective analog beamforming algorithm based on the cut-set bound and stochastic successive convex approximation (SSCA) and an innovative digital beamforming algorithm that relies on the theory of penalty dual decomposition (PDD) to maximize the system sum rate. The convergence properties and computational complexity of the proposed algorithms are also examined. Our simulation results show that the proposed two-timescale hybrid beamforming design significantly outperforms the conventional beamforming algorithms both in terms of the CSI-signalling overhead and the achievable sum rate in the presence of CSI delays

Survey network design of synchrotron in Heavy Ion Medical Machine in Lanzhou

<span style="color: rgb(51, 51, 51); font-family: arial, helvetica, sans-serif; font-size: 13px; line-height: 22px; background-color: rgb(248, 248, 248);">The paper introduces control survey network of installation strategy in the new HIMM (Heavy Ion Medical Machine). The 3D survey network is based on laser tracker and SA (Spatial Analyzer). Nine fiducial references and two scale bars were designed to guarantee high accuracy in control survey network. and Digital Level was used for altitude. The final RMS error of the global network could reach 0.04 mm, which guarantees the transverse position of quadrupoles requirement (0.10 mm) on the synchrotron.</span