Publications

Concealed faults can be important for understanding the regional structural geology and the subsurface fluid distribution. However, such faults are usually difficult to identify and characterize because of their small size and complex mechanism. To address this issue, we present an integrated approach of three-dimensional seismic data mapping and physical modeling experiments to examine the geometrical and kinematic characteristics of concealed faults and their relationship with the main faults in the Huawa area, east China. Three series of experiments were designed to characterize the differences in the scale of concealed faults and main faults, which also allowed us to examine how the concealed faults grow with the main faults in the area. Through this integrated study, we have demonstrated that: 1) NE-SW-striking concealed faults are below the resolution of the available seismic datasets and not easily recognized in seismic sections and that most of them grew later than the E-W-striking main faults, with some of them having grown at the same time; 2) pre-existing faults, rather than asymmetry of the basin structure, affect the faults that develop during subsequent episodes of extension; 3) E-W-striking pre-existing faults under a NW-SE stress direction of extension are most likely the formation mechanism of concealed faults. This study is of reference value in the interpretation of concealed faults in other regions.

In order to obtain and use the incomplete information in the power grid fault diagnosis, a unified information model is proposed in this paper. The structure of the model is given, the extended CIM of IEC61970 is employed to describe the primary component topology and component parameters, and IEC61850 is employed to describe the secondary system. Further, the two models are harmonized by OWL. The proposed model can solve the information integrity and standardization issues of fault diagnosis, and make fault diagnosis system practical.

By reconfiguring wireless channels via passive signal reflection, intelligent reflecting surface (IRS) can bring significant performance enhancement for wireless communication systems. However, such performance improvement generally relies on the knowledge of channel state information (CSI) for IRS-involved links. Prior works on IRS CSI acquisition mainly estimate IRS-cascaded channels based on the extra pilot signals received at the users/base station (BS) with time-varying IRS reflections, which, however, needs to modify the existing channel training/estimation protocols of wireless systems. To address this issue, we propose in this paper a new channel estimation scheme for IRS-assisted communication systems based on the received signal power measured at the user terminal, which is practically attainable without the need of changing the current protocol. Due to the lack of signal phase information in measured power, the autocorrelation matrix of the BS-IRS-user cascaded channel is estimated by solving an equivalent rank-minimization problem. To this end, a low-rank-approaching (LRA) algorithm is proposed by employing the fractional programming and alternating optimization techniques. To reduce computational complexity, an approximate LRA (ALRA) algorithm is also developed. Furthermore, these two algorithms are extended to be robust against the receiver noise and quantization error in power measurement. Simulation results are provided to verify the effectiveness of the proposed channel estimation algorithms as well as the IRS passive reflection design based on the estimated channel autocorrelation matrix.

This paper studies the achievable rate region of the K-user Gaussian multiple-input single-output interference channel (MISO-IC) with the interference treated as noise, when improper or circularly asymmetric complex Gaussian signaling is applied. The transmit optimization with improper Gaussian signaling involves not only the signal covariance matrix as in the conventional proper or circularly symmetric Gaussian signaling, but also the signal pseudo-covariance matrix, which is conventionally set to zero in proper Gaussian signaling. By exploiting the separable rate expression with improper Gaussian signaling, we propose a separate transmit covariance and pseudo-covariance optimization algorithm, which is guaranteed to improve the users' achievable rates over the conventional proper Gaussian signaling. In particular, for the pseudo-covariance optimization, we establish the optimality of rank-1 pseudo-covariance matrices, given the optimal rank-1 transmit covariance matrices for achieving the Pareto boundary of the rate region. Based on this result, we are able to greatly reduce the number of variables in the pseudo-covariance optimization problem and thereby develop an efficient solution by applying the celebrated semidefinite relaxation (SDR) technique. Finally, we extend the result to the Gaussian MISO broadcast channel (MISO-BC) with improper Gaussian signaling or so-called widely linear transmit precoding.

In wireless networks, communication links may be subject to random fatal impacts: for example, sensor networks under sudden power losses or cognitive radio networks with unpredictable primary user spectrum occupancy. Under such circumstances, it is critical to quantify how fast and reliably the information can be collected over attacked links. For a single point-to-point channel subject to a random attack, named as a \emph{dying channel}, we model it as a block-fading (BF) channel with a finite and random delay constraint. First, we define the outage capacity as the performance measure, followed by studying the optimal coding length $K$ such that the outage probability is minimized when uniform power allocation is assumed. For a given rate target and a coding length $K$, we then minimize the outage probability over the power allocation vector $\mv{P}_{K}$, and show that this optimization problem can be cast into a convex optimization problem under some conditions. The optimal solutions for several special cases are discussed. Furthermore, we extend the single point-to-point dying channel result to the parallel multi-channel case where each sub-channel is a dying channel, and investigate the corresponding asymptotic behavior of the overall outage probability with two different attack models: the independent-attack case and the $m$-dependent-attack case. It can be shown that the overall outage probability diminishes to zero for both cases as the number of sub-channels increases if the \emph{rate per unit cost} is less than a certain threshold. The outage exponents are also studied to reveal how fast the outage probability improves over the number of sub-channels.

With the advantages of causing no damage to the flow field, no pressure loss, no impact on normal operation of the plant power, the ultrasonic flowmeter can be applied in pipeline transmission and measuring the flow in pipelines of various diameters and the volume of urban water supply. This paper introduces the working principles and the advantages of ultrasonic flowmeter with time - difference, and explore the causes of errors in its operation.

Three configurations of a unique single-phase power generation system based on inexpensive single-phase induction motors are proposed in this paper. All of these configurations are well suited for residential or equivalent small-scale grid-tied power generation schemes because of their reduced cost, smaller footprint and minimum or no required maintenance. The wind power generation schemes presented in this paper could be used in stand-alone or grid-parallel mode without using any energy storage. Various characteristics of these configurations are summarized in this paper with necessary simulation and experimental results. In addition, an analytical model of the single-phase induction generator is presented to identify its operating characteristics.

There is a growing need for government agencies to monitor suspicious communication links to prevent crimes and terror attacks. In this paper, we study a legitimate surveillance scenario where a legitimate monitor aims to intercept the suspicious communication between a transmitter and a receiver over fading channels. The legitimate monitor can eavesdrop (decode) the information of the suspicious link only when its achievable data rate is no smaller than that at the suspicious receiver. In practice, the legitimate eavesdropping is challenging, especially when the legitimate monitor is far from the suspicious transmitter. To overcome this issue, we propose a new approach, namely proactive eavesdropping via cognitive jamming, in which the legitimate monitor purposely jams the receiver and changes the suspicious communication (e.g., to a smaller data rate) in order to overhear easily. In particular, we consider delay-sensitive and delay-insensitive applications for the suspicious transmission, under which the legitimate monitor maximizes the eavesdropping non-outage probability and the relative eavesdropping rate, respectively, by optimizing its jamming power allocation over different fading states subject to an average power constraint. We present efficient algorithms for optimally solving the formulated problems. Numerical results show that thanks to the cognitive jamming, the proposed proactive eavesdropping scheme greatly outperforms the conventional passive eavesdropping without jamming.

The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal quantization/compression techniques in the fronthaul to maximize the network throughput. However, most of the previous results are based on information-theoretical quantization methods, which are hard to implement due to the extremely high complexity. In this paper, we consider using practical uniform scalar quantization in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN system, where the mobile users are assigned with orthogonal sub-carriers for multiple access. In particular, we consider joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system end-to-end throughput. Efficient algorithms are proposed to solve the joint optimization problem when either information-theoretical or practical fronthaul quantization method is applied. Interestingly, we find that the fronthaul capacity constraints have significant impact to the optimal wireless power control policy. As a result, the joint optimization shows significant performance gain compared with either optimizing wireless power control or fronthaul quantization alone. Besides, we also show that the proposed simple uniform quantization scheme performs very close to the throughput performance upper bound, and in fact overlaps with the upper bound when the fronthaul capacity is sufficiently large. Overall, our results would help reveal practically achievable throughput performance of C-RAN, and lead to more efficient deployment of C-RAN in the next-generation wireless communication systems.

Intelligent reflecting surface (IRS) is envisioned to have abundant applications in future wireless networks by smartly reconfiguring the signal propagation for performance enhancement. Specifically, an IRS consists of a large number of low-cost passive elements each reflecting the incident signal with a certain phase shift to collaboratively achieve beamforming and suppress interference at one or more designated receivers. In this paper, we study an IRS-enhanced point-to-point multiple-input single-output (MISO) wireless system where one IRS is deployed to assist in the communication from a multi-antenna access point (AP) to a single-antenna user. As a result, the user simultaneously receives the signal sent directly from the AP as well as that reflected by the IRS. We aim to maximize the total received signal power at the user by jointly optimizing the (active) transmit beamforming at the AP and (passive) reflect beamforming by the phase shifters at the IRS. We first propose a centralized algorithm based on the technique of semidefinite relaxation (SDR) by assuming the global channel state information (CSI) available at the IRS. Since the centralized implementation requires excessive channel estimation and signal exchange overheads, we further propose a low-complexity distributed algorithm where the AP and IRS independently adjust the transmit beamforming and the phase shifts in an alternating manner until the convergence is reached. Simulation results show that significant performance gains can be achieved by the proposed algorithms as compared to benchmark schemes. Moreover, it is verified that the IRS is able to drastically enhance the link quality and/or coverage over the conventional setup without the IRS.

On dispersing different base matrices combined with masking, different kinds of quasi-cyclic low-density parity check (QC-LDPC) codes are constructed, which may achieve good error performances. Two new algebraic constructions of regular QC-LDPC codes are presented in this paper. The two constructions are based on two base matrices by dispersing and masking. The two base matrices are based on the generators of the cyclic group of a prime field. Results show that the two classes of codes presented in this paper perform well with iterative decoding over AWGN channel and have advantages over MacKay codes in some aspects of code performances. We find that one of the constructed codes converges very fast with iterative decoding, which is a critical property in ultra-high throughput communication systems.

In this paper, we study the three-node Gaussian relay channel with decode-and-forward (DF) relaying, in which the source and relay nodes transmit with power drawn from energy-harvesting sources. Assuming a deterministic energy-harvesting model under which the energy arrival time and the harvested amount are known prior to transmission, the throughput maximization problem over a finite horizon of N transmission blocks is investigated. We consider the nodelay-constrained (NDC) traffic case, for which the relay can store the decoded information from the source with arbitrary delay before forwarding it to the destination in each N-block transmission. Although the formulated problem is non-convex, we prove the optimality of a separation principle for the source and relay power allocation over time, based upon which a two-stage algorithm is developed to obtain the optimal source and relay power profiles separately.