89 research outputs found
An ultralow-energy negative cluster ion beam system and its application in preparation of few-layer graphene
Outage Performance of Multi-tier UAV Communication with Random Beam Misalignment
By exploiting the degree of freedom on the altitude, unmanned aerial vehicle
(UAV) communication can provide ubiquitous communication for future wireless
networks. In the case of concurrent transmission of multiple UAVs, the
directional beamforming formed by multiple antennas is an effective way to
reduce co-channel interference. However, factors such as airflow disturbance or
estimation error for UAV communications can cause the occurrence of beam
misalignment. In this paper, we investigate the system performance of a
multi-tier UAV communication network with the consideration of unstable beam
alignment. In particular, we propose a tractable random model to capture the
impacts of beam misalignment in the 3D space. Based on this, by utilizing
stochastic geometry, an analytical framework for obtaining the outage
probability in the downlink of a multi-tier UAV communication network for the
closest distance association scheme and the maximum average power association
scheme is established. The accuracy of the analysis is verified by Monte-Carlo
simulations. The results indicate that in the presence of random beam
misalignment, the optimal number of UAV antennas needs to be adjusted to be
relatively larger when the density of UAVs increases or the altitude of UAVs
becomes higher
A novel gas ionization sensor using Pd nanoparticle-capped ZnO
A novel gas ionization sensor using Pd nanoparticle-capped ZnO (Pd/ZnO) nanorods as the anode is proposed. The Pd/ZnO nanorod-based sensors, compared with the bare ZnO nanorod, show lower breakdown voltage for the detected gases with good sensitivity and selectivity. Moreover, the sensors exhibit stable performance after more than 200 tests for both inert and active gases. The simple, low-cost, Pd/ZnO nanorod-based field-ionization gas sensors presented in this study have potential applications in the field of gas sensor devices
Joint Beamforming and Offloading Design for Integrated Sensing, Communication and Computation System
Mobile edge computing (MEC) is powerful to alleviate the heavy computing
tasks in integrated sensing and communication (ISAC) systems. In this paper, we
investigate joint beamforming and offloading design in a three-tier integrated
sensing, communication and computation (ISCC) framework comprising one cloud
server, multiple mobile edge servers, and multiple terminals. While executing
sensing tasks, the user terminals can optionally offload sensing data to either
MEC server or cloud servers. To minimize the execution latency, we jointly
optimize the transmit beamforming matrices and offloading decision variables
under the constraint of sensing performance. An alternating optimization
algorithm based on multidimensional fractional programming is proposed to
tackle the non-convex problem. Simulation results demonstrates the superiority
of the proposed mechanism in terms of convergence and task execution latency
reduction, compared with the state-of-the-art two-tier ISCC framework.Comment: 5 pages, 4 figures, submitted to IEEE journals for possible
publicatio
Joint Transmitter Design for Robust Secure Radar-Communication Coexistence Systems
This paper investigates the spectrum sharing between a multiple-input
single-output (MISO) secure communication system and a multiple-input
multiple-output (MIMO) radar system in the presence of one suspicious
eavesdropper. We jointly design the radar waveform and communication
beamforming vector at the two systems, such that the interference between the
base station (BS) and radar is reduced, and the detrimental radar interference
to the communication system is enhanced to jam the eavesdropper, thereby
increasing secure information transmission performance. In particular, by
considering the imperfect channel state information (CSI) for the user and
eavesdropper, we maximize the worst-case secrecy rate at the user, while
ensuring the detection performance of radar system. To tackle this challenging
problem, we propose a two-layer robust cooperative algorithm based on the
S-lemma and semidefinite relaxation techniques. Simulation results demonstrate
that the proposed algorithm achieves significant secrecy rate gains over the
non-robust scheme. Furthermore, we illustrate the trade-off between secrecy
rate and detection probability
Sensing Aided Covert Communications: Turning Interference into Allies
In this paper, we investigate the realization of covert communication in a
general radar-communication cooperation system, which includes integrated
sensing and communications as a special example. We explore the possibility of
utilizing the sensing ability of radar to track and jam the aerial adversary
target attempting to detect the transmission. Based on the echoes from the
target, the extended Kalman filtering technique is employed to predict its
trajectory as well as the corresponding channels. Depending on the maneuvering
altitude of adversary target, two channel models are considered, with the aim
of maximizing the covert transmission rate by jointly designing the radar
waveform and communication transmit beamforming vector based on the constructed
channels. For the free-space propagation model, by decoupling the joint design,
we propose an efficient algorithm to guarantee that the target cannot detect
the transmission. For the Rician fading model, since the multi-path components
cannot be estimated, a robust joint transmission scheme is proposed based on
the property of the Kullback-Leibler divergence. The convergence behaviour,
tracking MSE, false alarm and missed detection probabilities, and covert
transmission rate are evaluated. Simulation results show that the proposed
algorithms achieve accurate tracking. For both channel models, the proposed
sensing-assisted covert transmission design is able to guarantee the
covertness, and significantly outperforms the conventional schemes.Comment: 13 pages, 12 figures, submitted to IEEE journals for potential
publicatio
SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator
Recent years have seen growing interest in 3D human faces modelling due to
its wide applications in digital human, character generation and animation.
Existing approaches overwhelmingly emphasized on modeling the exterior shapes,
textures and skin properties of faces, ignoring the inherent correlation
between inner skeletal structures and appearance. In this paper, we present
SCULPTOR, 3D face creations with Skeleton Consistency Using a Learned
Parametric facial generaTOR, aiming to facilitate easy creation of both
anatomically correct and visually convincing face models via a hybrid
parametric-physical representation. At the core of SCULPTOR is LUCY, the first
large-scale shape-skeleton face dataset in collaboration with plastic surgeons.
Named after the fossils of one of the oldest known human ancestors, our LUCY
dataset contains high-quality Computed Tomography (CT) scans of the complete
human head before and after orthognathic surgeries, critical for evaluating
surgery results. LUCY consists of 144 scans of 72 subjects (31 male and 41
female) where each subject has two CT scans taken pre- and post-orthognathic
operations. Based on our LUCY dataset, we learn a novel skeleton consistent
parametric facial generator, SCULPTOR, which can create the unique and nuanced
facial features that help define a character and at the same time maintain
physiological soundness. Our SCULPTOR jointly models the skull, face geometry
and face appearance under a unified data-driven framework, by separating the
depiction of a 3D face into shape blend shape, pose blend shape and facial
expression blend shape. SCULPTOR preserves both anatomic correctness and visual
realism in facial generation tasks compared with existing methods. Finally, we
showcase the robustness and effectiveness of SCULPTOR in various fancy
applications unseen before.Comment: 16 page, 13 fig
Secrecy Balancing over Two-User MISO Interference Channels with Rician Fading
This paper considers a 2-user multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM), in which the Rician channel model is assumed. The coordinated beamforming vectors at the two transmitters have the similar parameterizations as those for perfect CSI, which could be optimized jointly and achieved by agreeing on the real parameters between the two users. Our main contribution is that a quadratic relationship between the two real-valued parameters can be derived for the Rician channel to reach the ergodic secrecy rate balancing point. Simulation results present the secrecy performance over the 2-user MISO IFC-CM scenario
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