1,474 publications from this institution
Effective wave absorbing composite film was developed by electrodeposition of Ni nano particles distributed in carbon nanotubes (Nano-Ni/CNTs) using an AAO/CNTs electrode. Scanning electron microscopy images confirmed the uniform dispersion of Ni nano-particles in the CNTs, with the particle diameter increasing from 20nm to 100 nm as the deposition time increased. XRD test results revealed that the crystal phase of the Ni nano-particles remained unchanged at different deposition time, displaying an fcc structure. The film’s microwave electromagnetic properties were evaluated using a vector network analyzer, and the return loss curve demonstrated that the Ni nano-particles/CNTs composite exhibited excellent wave absorption capabilities. The composite film showed an effective absorption width of 13 GHz (4-17 GHz) and achieved a minimum reflection loss of −17 dB at 14 GHz.
In this letter, we consider a double-active-intelligent reflecting surface (IRS) aided wireless communication system, where two active IRSs assist the communication from a base station (BS) to multiple users via double-reflection links. Under the assumption of fixed per-element amplification power for each active-IRS element, we formulate a rate maximization problem subject to practical constraints on the reflection design, elements allocation, and placement of active IRSs. To solve this non-convex problem, we first obtain the optimal active-IRS reflections and BS beamforming, based on which we then jointly optimize the active-IRS elements allocation and placement by using the alternating optimization (AO) method. Moreover, we show that given the fixed per-element amplification power, the received signal-to-noise ratio (SNR) at the user increases asymptotically with the square of the number of reflecting elements; while given the fixed number of reflecting elements, the SNR does not increase with the per-element amplification power when it is asymptotically large. Finally, numerical results validate the proposed algorithm and compare the rate performance to benchmark systems.
This paper studies a new active eavesdropping technique via the so-called spoofing relay attack, which could be launched by the eavesdropper to significantly enhance the information leakage rate from the source over conventional passive eaves-dropping. With this attack, the eavesdropper acts as a relay to spoof the source to vary transmission rate in favor of its eavesdropping performance by either enhancing or degrading the effective channel of the legitimate link. The maxi-mum information leakage rate achievable by the eavesdropper and the corresponding optimal operation at the spoofing relay are obtained. It is shown that such a spoofing relay attack could impose new challenges from a physical-layer security perspective since it leads to significantly higher information leakage rate than conventional passive eavesdropping.
For that traditional current protection has defects in distribution network which contains distributed power supply,distance protection application in distribution network is suggested to be considered.It can make up shortages of current protection by distance protection based on simulating verification,but its ability to tolerate transition resistance when being applied in medium and low voltage distribution network is poor.For solving this problem,this paper analyzes influence on distance protection by transition resistance when short circuit fault happening on double-side power lines in distribution network while connecting distributed power supply,studies out an algorithm by using sequence component algorithm for measuring fault resistance value by collecting current and voltage phase values of lines which may not be affected by transition resistance.Based on MATLAB simulating verification,it establishes a distribution network model containing wind power units.The simulating result proves that this algorithm can measure fault resistance value correctly and discriminate faults in protection area.Meanwhile,it is of high precision in calculation to remove influence on distance protection by transition resistance well.
No abstract is provided for this article.
The space motion equation of Anti-torpedo-torpedo(ATT) intercepted incoming torpedo was established. The space motion equations for ATT intercepting the incoming torpedo are set up, the spatial motion of ATT and the torpedo is decomposed to the longitudinal and side planes and the guidance rate is designed respectively. Discontinuous smooth function is used to smooth the jitter of the end interceptor of Hit probability and miss distance of ATT under different interception conditions is simulated. The simulation results show that SMG can effectively overcome the target maneuver, ATT self detection error and the coupling between the longitudinal plane and the side plane, it has a high hit probability. The hit probability is also related to the initial position of ATT and the incoming torpedo, the initial ballistic angle and the ballistic angle.
No abstract is provided for this article.
This paper proposes the application of Model Driven Architecture (MDA) for distributed services Run-time Infrastructure to achieve reusing simulation services and communicating in heterogeneous network environments. Platform-Independent Model (PIM) is built based on simulation services definition in service-oriented distributed Run-time Infrastructure by interface definition language Slice to describe simulation service and special data structure. The simulation service model is mapped to Platform-Specific Model (PSM) by slice mapping tool. The paper achieves the heterogeneous communication between federation, simulation services and Simulation Service Management Bus (SSMB) by same communication protocol. In practice, this solution is effective for simulation services reuse and communication in heterogeneous network environments.
In this paper, we study the three-dimensional (3D) path planning for a cellular-connected unmanned aerial vehicle (UAV) to minimize its flying distance from given initial to final locations, while ensuring a target link quality in terms of the expected signal-to-interference-plus-noise ratio (SINR) at the UAV receiver with each of its associated ground base stations (GBSs) during the flight. To exploit the location-dependent and spatially varying channel as well as interference over the 3D space, we propose a new radio map based path planning framework for the UAV. Specifically, we consider the channel gain map of each GBS that provides its large-scale channel gains with uniformly sampled locations on a 3D grid, which are due to static and large-size obstacles (e.g., buildings) and thus assumed to be time-invariant. Based on the channel gain maps of GBSs as well as their loading factors, we then construct an SINR map that depicts the expected SINR levels over the sampled 3D locations. By leveraging the obtained SINR map, we proceed to derive the optimal UAV path by solving an equivalent shortest path problem (SPP) in graph theory. We further propose a grid quantization approach where the grid points in the SINR map are more coarsely sampled by exploiting the spatial channel/interference correlation over neighboring grids. Then, we solve an approximate SPP over the reduced-size SINR map (graph) with reduced complexity. Numerical results show that the proposed solution can effectively minimize the flying distance/time of the UAV subject to its communication quality constraint, and a flexible trade-off between performance and complexity can be achieved by adjusting the grid quantization ratio in the SINR map. Moreover, the proposed solution significantly outperforms various benchmark schemes without fully exploiting the channel/interference spatial distribution in the network.
Six-dimensional movable antenna (6DMA) is an innovative technology to improve wireless network capacity by adjusting 3D positions and 3D rotations of antenna surfaces based on channel spatial distribution. However, the existing works on 6DMA have assumed a central processing unit (CPU) to jointly process the signals of all 6DMA surfaces to execute various tasks. This inevitably incurs prohibitively high processing cost for channel estimation. Therefore, we propose a distributed 6DMA processing architecture to reduce processing complexity of CPU by equipping each 6DMA surface with a local processing unit (LPU). In particular, we unveil for the first time a new \textbf{\textit{directional sparsity}} property of 6DMA channels, where each user has significant channel gains only for a (small) subset of 6DMA position-rotation pairs, which can receive direct/reflected signals from users. In addition, we propose a practical three-stage protocol for the 6DMA-equipped base station (BS) to conduct statistical CSI acquisition for all 6DMA candidate positions/rotations, 6DMA position/rotation optimization, and instantaneous channel estimation for user data transmission with optimized 6DMA positions/rotations. Specifically, the directional sparsity is leveraged to develop distributed algorithms for joint sparsity detection and channel power estimation, as well as for directional sparsity-aided instantaneous channel estimation. Using the estimated channel power, we develop a channel power-based optimization algorithm to maximize the ergodic sum rate of the users by optimizing the antenna positions/rotations. Simulation results show that our channel estimation algorithms are more accurate than benchmarks with lower pilot overhead, and our optimization outperforms fluid/movable antennas optimized only in two dimensions (2D), even when the latter have perfect instantaneous CSI.
In this letter, a method is proposed to optimally combine the received signal samples in space and time based on the principle of maximizing the signal-to-noise ratio (SNR). After the combining, energy detection (ED) is used. However, optimal combining needs information of the source signal and channel, which is usually unknown. To overcome this difficulty, a method is proposed to blindly combine the signal samples. Similar to energy detection, blindly combined energy detection (BCED) does not need any information of the source signal and the channel a priori. BCED can be much better than ED for highly correlated signals, and most importantly, it does not need noise power estimation and overcomes ED's susceptibility to noise uncertainty. Also, perfect synchronization is not required. Simulations based on wireless microphone signals and randomly generated signals are presented to verify the methods.
