arXiv subjects

Lin Cai

Publications and source records attributed to Lin Cai.

28 records · Page 2Linked to original sources

arXiv2019

PhyCode: A Practical Wireless Communication System Exploiting Superimposed Signals

Superimposed signals are anticipated to improve wireless spectrum efficiency to support the ever-growing IoT applications. Implementing the superimposed signal demands on ideally aligned signals in both the time and frequency domains. Prior work applied an average carrier-frequency offset compensation to the superimposed signal under the assumptions of homogeneous devices and static environments. However, this will cause a significant signal distortion in practice when heterogeneous IoT devices are involved in a dynamic environment. This paper presents PhyCode, which exploits the nature of varying offsets across devices, and designs a dynamic decoding scheme which can react to the exact offsets from different signal sources simultaneously. We implement PhyCode via a software-defined radio platform and demonstrate that PhyCode achieves a lower raw BER compared with the existing state-of-the-art method.

eess.SP↗

arXiv2019

3D Magic Mirror: Automatic Video to 3D Caricature Translation

Caricature is an abstraction of a real person which distorts or exaggerates certain features, but still retains a likeness. While most existing works focus on 3D caricature reconstruction from 2D caricatures or translating 2D photos to 2D caricatures, this paper presents a real-time and automatic algorithm for creating expressive 3D caricatures with caricature style texture map from 2D photos or videos. To solve this challenging ill-posed reconstruction problem and cross-domain translation problem, we first reconstruct the 3D face shape for each frame, and then translate 3D face shape from normal style to caricature style by a novel identity and expression preserving VAE-CycleGAN. Based on a labeling formulation, the caricature texture map is constructed from a set of multi-view caricature images generated by CariGANs. The effectiveness and efficiency of our method are demonstrated by comparison with baseline implementations. The perceptual study shows that the 3D caricatures generated by our method meet people's expectations of 3D caricature style.

cs.GR↗

arXiv2018

Consensus-based Privacy-preserving Data Aggregation

Privacy-preserving data aggregation in ad hoc networks is a challenging problem, considering the distributed communication and control requirement, dynamic network topology, unreliable communication links, etc. Different from the widely used cryptographic approaches, in this paper, we address this challenging problem by exploiting the distributed consensus technique. We first propose a secure consensus-based data aggregation (SCDA) algorithm that guarantees an accurate sum aggregation while preserving the privacy of sensitive data. Then, we prove that the proposed algorithm converges accurately and is $(ε, σ)$-data-privacy, and the mathematical relationship between $ε$ and $σ$ is provided. Extensive simulations have shown that the proposed algorithm has high accuracy and low complexity, and they are robust against network dynamics.

eess.SY↗

arXiv2017

Beyond Powers of Two: Hexagonal Modulation and Non-Binary Coding for Wireless Communication Systems

Adaptive modulation and coding (AMC) is widely employed in modern wireless communication systems to improve the transmission efficiency by adjusting the transmission rate according to the channel conditions. Thus, AMC can provide very efficient use of channel resources especially over fading channels. Quadrature Amplitude Modulation (QAM) is an ef- ficient and widely employed digital modulation technique. It typically employs a rectangular signal constellation. Therefore the decision regions of the constellation are square partitions of the two-dimensional signal space. However, it is well known that hexagons rather than squares provide the most compact regular tiling in two dimensions. A compact tiling means a dense packing of the constellation points and thus more energy efficient data transmission. Hexagonal modulation can be difficult to implement because it does not fit well with the usual power- of-two symbol sizes employed with binary data. To overcome this problem, non-binary coding is combined with hexagonal modulation in this paper to provide a system which is compatible with binary data. The feasibility and efficiency are evaluated using a software-defined radio (SDR) based prototype. Extensive simulation results are presented which show that this approach can provide improved energy efficiency and spectrum utilization in wireless communication systems.

eess.SP↗

arXiv2017

Preserving Data-Privacy with Added Noises: Optimal Estimation and Privacy Analysis

Networked system often relies on distributed algorithms to achieve a global computation goal with iterative local information exchanges between neighbor nodes. To preserve data privacy, a node may add a random noise to its original data for information exchange at each iteration. Nevertheless, a neighbor node can estimate other's original data based on the information it received. The estimation accuracy and data privacy can be measured in terms of $(ε, δ)$-data-privacy, defined as the probability of $ε$-accurate estimation (the difference of an estimation and the original data is within $ε$) is no larger than $δ$ (the disclosure probability). How to optimize the estimation and analyze data privacy is a critical and open issue. In this paper, a theoretical framework is developed to investigate how to optimize the estimation of neighbor's original data using the local information received, named optimal distributed estimation. Then, we study the disclosure probability under the optimal estimation for data privacy analysis. We further apply the developed framework to analyze the data privacy of the privacy-preserving average consensus algorithm and identify the optimal noises for the algorithm.

cs.IT↗

arXiv2017

Differential Private Noise Adding Mechanism and Its Application on Consensus

Differential privacy is a formal mathematical {stand-ard} for quantifying the degree of that individual privacy in a statistical database is preserved. To guarantee differential privacy, a typical method is adding random noise to the original data for data release. In this paper, we investigate the conditions of differential privacy considering the general random noise adding mechanism, and then apply the obtained results for privacy analysis of the privacy-preserving consensus algorithm. Specifically, we obtain a necessary and sufficient condition of $ε$-differential privacy, and the sufficient conditions of $(ε, δ)$-differential privacy. We apply them to analyze various random noises. For the special cases with known results, our theory matches with the literature; for other cases that are unknown, our approach provides a simple and effective tool for differential privacy analysis. Applying the obtained theory, on privacy-preserving consensus algorithms, it is proved that the average consensus and $ε$-differential privacy cannot be guaranteed simultaneously by any privacy-preserving consensus algorithm.

cs.IT↗

arXiv2017

Privacy-preserving Average Consensus: Privacy Analysis and Optimal Algorithm Design

Privacy-preserving average consensus aims to guarantee the privacy of initial states and asymptotic consensus on the exact average of the initial value. In existing work, it is achieved by adding and subtracting variance decaying and zero-sum random noises to the consensus process. However, there is lack of theoretical analysis to quantify the degree of the privacy protection. In this paper, we introduce the maximum disclosure probability that the other nodes can infer one node's initial state within a given small interval to quantify the privacy. We develop a novel privacy definition, named $(ε, δ)$-data-privacy, to depict the relationship between maximum disclosure probability and estimation accuracy. Then, we prove that the general privacy-preserving average consensus (GPAC) provides $(ε, δ)$-data-privacy, and provide the closed-form expression of the relationship between $ε$ and $δ$. Meanwhile, it is shown that the added noise with uniform distribution is optimal in terms of achieving the highest $(ε, δ)$-data-privacy. We also prove that when all information used in the consensus process is available, the privacy will be compromised. Finally, an optimal privacy-preserving average consensus (OPAC) algorithm is proposed to achieve the highest $(ε, δ)$-data-privacy and avoid the privacy compromission. Simulations are conducted to verify the results.

eess.SY↗

arXiv2016

An analytical method for error analysis of GRACE-like missions based on spectral analysis

The aim of this paper is to present an analytical relationship between the power spectral density of GRACE-like mission measurements and the accuracies of the gravity field coefficients mainly from the point of view of theory of signal and system, which indicates the one-to-one correspondence between spherical harmonic error degree variances and frequencies of the measurement noise. In order to establish this relationship, the average power of the errors due to gravitational acceleration difference and the relationship between perturbing forces and range-rate perturbations are derived, based on the orthogonality property of associated Legendre functions and the linear orbit perturbation theory, respectively. This method provides a physical insight into the relation between mission parameters and scientific requirements. By taking GRACE-FO as the object of research, the effects of sensor noises and time variable gravity signals are analyzed. If LRI measurements are applied, a mission goal with a geoid accuracy of 7.4 cm at a spatial resolution of 101 km is reachable, whereas if the KBR measurement error model is applied, a mission goal with a geoid accuracy of 10.2 cm at a spatial resolution of 125 km is reachable. Based on the discussion of the spectral matching of instrument accuracies, an improvement in accuracy of accelerometers is necessary for the match between the range errors and accelerometer noises in the future mission. Temporal aliasing caused by the time variable gravity signals is also discussed by this method.

physics.geo-ph↗

arXiv2014

A Geometrical-Based Throughput Bound Analysis for Device-to-Device Communications in Cellular Networks

Device-to-device (D2D) communications in cellular networks are promising technologies for improving network throughput, spectrum efficiency, and transmission delay. In this paper, we first introduce the concept of guard distance to explore a proper system model for enabling multiple concurrent D2D pairs in the same cell. Considering the Signal to Interference Ratio (SIR) requirements for both macro-cell and D2D communications, a geometrical method is proposed to obtain the guard distances from a D2D user equipment (DUE) to the base station (BS), to the transmitting cellular user equipment (CUE), and to other communicating D2D pairs, respectively, when the uplink resource is reused. By utilizing the guard distances, we then derive the bounds of the maximum throughput improvement provided by D2D communications in a cell. Extensive simulations are conducted to demonstrate the impact of different parameters on the optimal maximum throughput. We believe that the obtained results can provide useful guidelines for the deployment of future cellular networks with underlaying D2D communications.

cs.NI↗

arXiv2012

Error analysis for satellite gravity field determination based on two-dimensional Fourier methods

The time-wise and space-wise approaches are generally applied to data processing and error analysis for satellite gravimetry missions. But both the approaches, which are based on least-squares collocation, address the whole effect of measurement errors and estimate the resolution of gravity field models mainly from a numerical point of indirect view. Moreover, requirement for higher accuracy and resolution gravity field models could make the computation more difficult, and serious numerical instabilities arise. In order to overcome the problems, this study focuses on constructing a direct relationship between power spectral density of the satellite gravimetry measurements and coefficients of the Earth's gravity potential. Based on two-dimensional Fourier transform, the relationship is analytically concluded. By taking advantage of the analytical expression, it is efficient and distinct for parameter estimation and error analysis of missions. From the relationship and the simulations, it is analytically confirmed that the low-frequency noise affects the gravity field recovery in all degrees for the instance of satellite gradiometer recovery mission. Furthermore, some other results and suggestions are also described.

physics.geo-ph↗