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Weiping Liu

Publications and source records attributed to Weiping Liu.

At least 37 records · Page 2Linked to original sources
arXiv2023

Capacity Limitation and Optimization Strategy for Flexible Point-to-Multi-Point Optical Networks

Point-to-multi-point (PtMP) optical networks become the main solutions for network-edge applications such as passive optical networks and radio access networks. Entropy-loading digital subcarrier multiplexing (DSCM) is the core technology to achieve low latency and approach high capacity for flexible PtMP optical networks. However, the high peak-to-average power ratio of the entropy-loading DSCM signal limits the power budget and restricts the capacity, which can be reduced effectively by clipping operation. In this paper, we derive the theoretical capacity limitation of the flexible PtMP optical networks based on the entropy-loading DSCM signal. Meanwhile, an optimal clipping ratio for the clipping operation is acquired to approach the highest capacity limitation. Based on an accurate clipping-noise model under the optimal clipping ratio, we establish a three-dimensional look-up table for bit-error ratio, spectral efficiency, and link loss. Based on the three-dimensional look-up table, an optimization strategy is proposed to acquire optimal spectral efficiencies for achieving a higher capacity of the flexible PtMP optical networks.

cs.IT↗
arXiv2023

Non-Integer-Oversampling Digital Signal Processing for Coherent Passive Optical Networks

Beyond 100G passive optical networks (PONs) will be required to meet the ever-increasing traffic demand in the future. Coherent optical technologies are the competitive solutions for the future beyond 100G PON but also face challenges such as the high computational complexity of digital signal processing (DSP). A high oversampling rate in coherent optical technologies results in the high computational complexity of DSP. Therefore, DSP running in a non-integer-oversampling below 2 samples-per-symbol (sps) is preferred, which can not only reduce computational complexity but also obviously lower the requirement for the analog-to-digital converter. In this paper, we propose a non-integer-oversampling DSP for meeting the requirements of coherent PON. The proposed DSP working at 9/8-sps and 5/4-sps oversampling rates can be reduced by 44.04% and 40.78% computational complexity compared to that working at the 2-sps oversampling rate, respectively. Moreover, a 400-Gb/s-net-rate coherent PON based on digital subcarrier multiplexing was demonstrated to verify the feasibility of the non-integer-oversampling DSP. There is almost no penalty on the receiver sensitivity when the non-integer-oversampling DSP is adopted. In conclusion, the non-integer-oversampling DSP shows great potential in the future coherent PON.

cs.IT↗
arXiv2023

Measurement of $^{19}$F($p$,$γ$)$^{20}$Ne reaction suggests CNO break-out in first stars

The origin of calcium production in the first stars (Pop III stars), which formed out of the primordial matter of the Big Bang, and their fates, remain most fascinating mysteries in astrophysics. Advanced nuclear burning and supernovae were thought to be the dominant source of the Ca production seen in all stars. Here we report on a qualitatively different path to Ca production through break-out from the "warm" carbon-nitrogen-oxygen (CNO) cycle. We extend direct measurement of the $^{19}$F($p$, $γ$)$^{20}$Ne break-out reaction down to an unprecedentedly low energy point of 186 keV and discover a key resonance at 225 keV. In the domain of astrophysical interest, at around 0.1 giga kelvin, this thermonuclear $^{19}$F($p$,$γ$)$^{20}$Ne rate is up to a factor of 7.4 larger than the previous recommended rate. Our stellar models show a stronger break-out during stellar hydrogen burning than thought before, and may reveal the nature of Ca production in Pop III stars imprinted on the oldest known ultra-iron poor star, SMSS0313-6708. This result from the China Jinping Underground Laboratory, the deepest laboratory in the world, offering an environment with extremely low cosmic-ray induced background, has far-reaching implications on our understanding of how the first stars evolve and die. Our rate showcases the impact that faint Pop III star supernovae can have on the nucleosynthesis observed in the oldest known stars and first galaxies, key mission targets of the James Webb Space Telescope.

astro-ph.SR↗
arXiv2023

The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge

Automatic intracranial hemorrhage segmentation in 3D non-contrast head CT (NCCT) scans is significant in clinical practice. Existing hemorrhage segmentation methods usually ignores the anisotropic nature of the NCCT, and are evaluated on different in-house datasets with distinct metrics, making it highly challenging to improve segmentation performance and perform objective comparisons among different methods. The INSTANCE 2022 was a grand challenge held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). It is intended to resolve the above-mentioned problems and promote the development of both intracranial hemorrhage segmentation and anisotropic data processing. The INSTANCE released a training set of 100 cases with ground-truth and a validation set with 30 cases without ground-truth labels that were available to the participants. A held-out testing set with 70 cases is utilized for the final evaluation and ranking. The methods from different participants are ranked based on four metrics, including Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), Relative Volume Difference (RVD) and Normalized Surface Dice (NSD). A total of 13 teams submitted distinct solutions to resolve the challenges, making several baseline models, pre-processing strategies and anisotropic data processing techniques available to future researchers. The winner method achieved an average DSC of 0.6925, demonstrating a significant growth over our proposed baseline method. To the best of our knowledge, the proposed INSTANCE challenge releases the first intracranial hemorrhage segmentation benchmark, and is also the first challenge that intended to resolve the anisotropic problem in 3D medical image segmentation, which provides new alternatives in these research fields.

eess.IV↗
arXiv2021

Highly efficient acousto-optic modulation using nonsuspended thin-film lithium niobate-chalcogenide hybrid waveguides

A highly efficient on-chip acousto-optic modulator, as a key component, occupies an exceptional position in microwave-to-optical conversion. Homogeneous thin-film lithium niobate is preferentially employed to build the suspended configuration forming the acoustic resonant cavity to improve the modulation efficiency of the device. However, the limited cavity length and complex fabrication recipe of the suspended prototype restrain further breakthrough in the modulation efficiency and impose challenges for waveguide fabrication. In this work, based on a nonsuspended thin-film lithium niobate-chalcogenide glass hybrid Mach-Zehnder interferometer waveguide platform, we propose and demonstrate a built-in push-pull acousto-optic modulator with a half-wave-voltage-length product as low as 0.03 V cm, presenting a modulation efficiency comparable to that of the state-of-the-art suspended counterpart. Based on the advantage of low power consumption, a microwave modulation link is demonstrated using our developed built-in push-pull acousto-optic modulator. The nontrivial acousto-optic modulation performance benefits from the superior photoelastic property of the chalcogenide membrane and the completely bidirectional participation of the antisymmetric Rayleigh surface acoustic wave mode excited by the impedance-matched interdigital transducer, overcoming the issue of amplitude differences of surface acoustic waves applied to the Mach-Zehnder interferometer two arms in traditional push-pull acousto-optic modulators.

physics.app-ph↗
arXiv2021

Multi-Rate Nyquist-SCM for C-Band 100Gbit/s Signal over 50km Dispersion-Uncompensated Link

In this paper, to the best of our knowledge, we propose the first multi-rate Nyquist-subcarriers modulation (SCM) for C-band 100Gbit/s signal transmission over 50km dispersion-uncompensated link. Chromatic dispersion (CD) introduces severe spectral nulls on optical double-sideband signal, which greatly degrades the performance of intensity-modulation and direct-detection systems. Based on the prior knowledge of the dispersive channel, Nyquist-SCM with multi-rate subcarriers is proposed to keep away from the CD-caused spectral nulls flexibly. Signal on each subcarrier can be individually recovered by a digital signal processing, including the feed-forward equalizer with no more than 31 taps, a two-tap post filter, and maximum likelihood sequence estimation with one memory length. Combining with entropy loading based on probabilistic constellation shaping to maximize the capacity-reach, the C-band 100Gbit/s multi-rate Nyquist-SCM signal over 50km dispersion-uncompensated link can achieve 7% hard-decision forward error correction limit and average normalized generalized mutual information of 0.967 at received optical power of -4dBm and optical signal-to-noise ratio of 47.67dB. In conclusion, the multi-rate Nyquist-SCM shows great potentials in solving the CD-caused spectral distortions.

cs.IT↗
arXiv2021

Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning

In-time and accurate assessments of on-road vehicle emissions play a central role in urban air quality and health policymaking. However, official insight is hampered by the Inspection/Maintenance (I/M) procedure conducted in the laboratory annually. It not only has a large gap to real-world situations (e.g., meteorological conditions) but also is incapable of regular supervision. Here we build a unique dataset including 103831 light-duty gasoline vehicles, in which on-road remote sensing (ORRS) measurements are linked to the I/M records based on the vehicle identification numbers and license plates. On this basis, we develop an ensemble model framework that integrates three machining learning algorithms, including neural network (NN), extreme gradient boosting (XGBoost), and random forest (RF). We demonstrate that this ensemble model could rapidly assess the vehicle-specific emissions (i.e., CO, HC, and NO). In particular, the model performs quite well for the passing vehicles under normal conditions (i.e., lower VSP (< 18 kw/t), temperature (6 ~ 32 °C), relative humidity (< 80%), and wind speed (< 5m/s)). Together with the current emission standard, we identify a large number of the dirty (2.33%) or clean (74.92%) vehicles in the real world. Our results show that the ORRS measurements, assisted by the machine-learning-based ensemble model developed here, can realize day-to-day supervision of on-road vehicle-specific emissions. This approach framework provides a valuable opportunity to reform the I/M procedures globally and mitigate urban air pollution deeply.

cs.LG↗
arXiv2021

Sorting OAM modes with metasurfaces based on raytracing improved optical coordinate transformation

Optical coordinate transformation (OCT) has attracted widespread attention in the field of orbital angular momentum (OAM) (de)multiplexing or manipulation, but the performance of OCT would suffer from its distortion. In this paper, we quantitatively analyze the distortion of OCT from the perspective of ray optics, and explain its rationality to work under non-normal incident light. For the special case of log-polar coordinate transformation (LPCT), we use a raytracing assisted optimization scheme to improve its distortion, which is related to a Zernike polynomial based phase compensation. After raytracing optimization, the root mean square error (RMSE) of the focused rays is reduced to 1/5 of the original value and the physical optic simulation also shows great improvement. In the experiment, we use three phase masks which are realized by metasurfaces, the measured results show well consistency with the simulation. Results in this paper have great potential to improve the performance of OCT related applications.

physics.optics↗
arXiv2021

The third- and fourth-order orbital angular momentum multiplexed amplification with ultra-low differential mode gain

In this Letter, a ring-core erbium-doped fiber (RC-EDF), with two-layer erbium-doped structure, supporting up to the fourth-order orbital angular momentum (OAM) mode is designed and fabricated for OAM mode multiplexed amplification. Using the RC-EDF, the third- and fourth-order OAM modes amplification with ultra-low differential mode gain (DMG) is demonstrated by observing both the modal intensity and phase distribution and measuring the modal gain under the fundamental mode core-pumping. The measured average gain of four modes (l=+3, -3, +4, -4) multiplexed amplification is higher than 19dB cover the C-band and the DMG is less than 1dB. Additionally, the gain of two conjugate OAM modes are almost the same under different pump power no matter they are amplified simultaneously or separately.

physics.optics↗
arXiv2021

Burst-Error Propagation Suppression for Decision-Feedback Equalizer in Field-Trial Submarine Fiber-Optic Communications

In this paper, we present a field-trial C-band 72Gbit/s optical on-off keying (OOK) system over 18.8km dispersion-uncompensated submarine optical cable in the South China Sea. Chromatic dispersion (CD) of 18.8km submarine optical cable causes four spectral nulls on the 36GHz bandwidth of 72Gbit/s OOK signal, which is the main obstacle for achieving an acceptable bit-error-rate (BER) performance. Decision feedback equalizer (DFE) is effective to compensate for the spectral nulls. However, DFE has a serious defect of burst-error propagation when the burst errors emerge due to the unstable submarine environment. Weighted DFE (WDFE) can be used to mitigate the burst-error propagation, but it cannot fully compensate for the spectral nulls because only a part of feedback symbols is directly decided. Fortunately, maximum likelihood sequence estimation (MLSE) can be added after the WDFE to simultaneously eliminate the resisting spectral distortions and implement optimal detection. Compared to the joint DFE and MLSE algorithm, the joint WDFE and MLSE algorithm can effectively suppress the burst-error propagation to obtain a maximum 2.9dB improvement of $\boldsymbol{Q}$ factor and eliminate the phenomenon of BER floor. In conclusion, the joint WDFE and MLSE algorithm can solve the burst-error propagation for the field-trial fiber-optic communications.

cs.IT↗
arXiv2020

Exploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization

Edge caching can effectively reduce backhaul burden at core network and increase quality-ofservice at wireless edge nodes. However, the beneficial role of edge caching cannot be fully realized when the offloading link is in deep fade. Fortunately, the impairments induced by wireless propagation environments could be renovated by a reconfigurable intelligent surface (RIS). In this paper, a new RIS-aided edge caching system is proposed, where a network cost minimization problem is formulated to optimize content placement at cache units, active beamforming at base station and passive phase shifting at RIS. After decoupling the content placement subproblem with hybrid beamforming design, we propose an alternating optimization algorithm to tackle the active beamforming and passive phase shifting. For active beamforming, we transform the problem into a semidefinite programming (SDP) and prove that the optimal solution of SDP is always rank-1. For passive phase shifting, we introduce block coordinate descent method to alternately optimize the auxiliary variables and the RIS phase shifts. Further, a conjugate gradient algorithm based on manifold optimization is proposed to deal with the non-convex unit-modulus constraints. Numerical results show that our RIS-aided edge caching design can effectively decrease the network cost in terms of backhaul capacity and power consumption.

cs.IT↗
arXiv2020

Adaptive Channel-Matched Detection for C-Band 64-Gbit/s Optical OOK System over 100-km Dispersion-Uncompensated Link

In this paper, we propose adaptive channel-matched detection (ACMD) for C-band 64-Gbit/s intensity-modulation and direct-detection (IM/DD) optical on-off keying (OOK) system over a 100-km dispersion-uncompensated link. The proposed ACMD can adaptively compensate most of the link distortions based on channel and noise characteristics, which includes a polynomial nonlinear equalizer (PNLE), a decision feedback equalizer (DFE) and maximum likelihood sequence estimation (MLSE). Based on the channel characteristics, PNLE eliminates the linear and nonlinear distortions, while the followed DFE compensates the spectral nulls caused by chromatic dispersion. Finally, based on the noise characteristics, a post filter can whiten the noise for implementing optimal signal detection using MLSE. To the best of our knowledge, we present a record C-band 64-Gbit/s IM/DD optical OOK system over a 100 km dispersion-uncompensated link achieving 7\% hard-decision forward error correction limit using only the proposed ACMD at the receiver side. In conclusion, ACMD-based C-band 64-Gbit/s optical OOK system shows great potential for future optical interconnects.

eess.SP↗
arXiv2019

BGD-based Adam algorithm for time-domain equalizer in PAM-based optical interconnects

To the best of our knowledge, for the first time, we propose adaptive moment estimation (Adam) algorithm based on batch gradient descent (BGD) to design a time-domain equalizer (TDE) for PAM-based optical interconnects. Adam algorithm has been widely applied in the fields of artificial intelligence. For TDE, BGD-based Adam algorithm can obtain globally optimal tap coefficients without being trapped in locally optimal tap coefficients. Therefore, fast and stable convergence can be achieved by BGD-based Adam algorithm with low mean square error. Meanwhile, BGD-based Adam algorithm is implemented by parallel processing, which is more efficient than conventional serial algorithms, such as least mean square and recursive least square algorithms. The experimental results demonstrate that BGD-based Adam feed-forward equalizer works well in 120-Gbit/s PAM8 optical interconnects. In conclusion, BGD-based Adam algorithm shows great potential for converging the tap coefficients of TDE in future optical interconnects.

cs.IT↗
arXiv2012

Enhancing network robustness for malicious attacks

In a recent work [Proc. Natl. Acad. Sci. USA 108, 3838 (2011)], the authors proposed a simple measure for network robustness under malicious attacks on nodes. With a greedy algorithm, they found the optimal structure with respect to this quantity is an onion structure in which high-degree nodes form a core surrounded by rings of nodes with decreasing degree. However, in real networks the failure can also occur in links such as dysfunctional power cables and blocked airlines. Accordingly, complementary to the node-robustness measurement ($R_{n}$), we propose a link-robustness index ($R_{l}$). We show that solely enhancing $R_{n}$ cannot guarantee the improvement of $R_{l}$. Moreover, the structure of $R_{l}$-optimized network is found to be entirely different from that of onion network. In order to design robust networks resistant to more realistic attack condition, we propose a hybrid greedy algorithm which takes both the $R_{n}$ and $R_{l}$ into account. We validate the robustness of our generated networks against malicious attacks mixed with both nodes and links failure. Finally, some economical constraints for swapping the links in real networks are considered and significant improvement in both aspects of robustness are still achieved.

physics.soc-ph↗
arXiv2011

Degree heterogeneity in spatial networks with total cost constraint

Recently, In [Phys. Rev. Lett. 104, 018701 (2010)] the authors studied a spatial network which is constructed from a regular lattice by adding long-range edges (shortcuts) with probability $P_{ij}\sim r_{ij}^{-α}$, where $r_{ij}$ is the Manhattan length of the long-range edges. The total length of the additional edges is subject to a cost constraint ($\sum r=C$). These networks have fixed optimal exponent $α$ for transportation (measured by the average shortest-path length). However, we observe that the degree in such spatial networks is homogenously distributed, which is far different from real networks such as airline systems. In this paper, we propose a method to introduce degree heterogeneity in spatial networks with total cost constraint. Results show that with degree heterogeneity the optimal exponent shifts to a smaller value and the average shortest-path length can further decrease. Moreover, we consider the synchronization on the spatial networks and related results are discussed. Our new model may better reproduce the features of many real transportation systems.

physics.soc-ph↗
arXiv2011

Information filtering via preferential diffusion

Recommender systems have shown great potential to address information overload problem, namely to help users in finding interesting and relevant objects within a huge information space. Some physical dynamics, including heat conduction process and mass or energy diffusion on networks, have recently found applications in personalized recommendation. Most of the previous studies focus overwhelmingly on recommendation accuracy as the only important factor, while overlook the significance of diversity and novelty which indeed provide the vitality of the system. In this paper, we propose a recommendation algorithm based on the preferential diffusion process on user-object bipartite network. Numerical analyses on two benchmark datasets, MovieLens and Netflix, indicate that our method outperforms the state-of-the-art methods. Specifically, it can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.

physics.data-an↗
arXiv2011

Effective Mechanism for Social Recommendation of News

Recommendation systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize network's topology we propose different stochastic algorithms that are scalable with respect to the network's size. Agent-based simulations reveal the features and the performance of these algorithms. To overcome the resultant drawbacks of each method we introduce two improved algorithms and show that they can optimize network's topology almost as fast and effectively as other not-scalable methods that make use of much more information.

physics.soc-ph↗