Liangtian Wan

Routing protocols for underwater wireless sensor networks

Recently, underwater wireless sensor networks (UWSNs) have emerged as a promising networking technique for various underwater applications. An energy efficient routing protocol plays a vital role in data transmission and practical applications. However, due to the specific characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and high latency, it is difficult to build routing protocols for UWSNs. In this article we focus on surveying existing routing protocols in UWSNs. First, we classify existing routing protocols into two categories based on a route decision maker. Then the performance of existing routing protocols is compared in detail. Furthermore, future research issues of routing protocols in UWSNs are carefully analyzed.

Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial

Intelligent transportation systems (ITSs) of industrial systems have played an important role in Internet of things (IOT). The assistant calibration system (ACS) of vehicles is an emerging technology, which services the driver to drive the vehicle safely. To solve some existing problems in ACS such as frequency pairing, vehicle localization judgment, and driving in the curve road, two direction-of-arrival (DOA) estimation-based approaches are proposed to resolve these problems. However, the performance of most conventional DOA estimation algorithms is affected by the mutual coupling among the elements. The special structure of the mutual coupling matrix of the uniform linear array is applied to eliminate the effect of mutual coupling. Then, a novel on-grid DOA estimation algorithm based on compressive sensing (CS) strategies is proposed in the presence of unknown mutual coupling. In order to compensate the aperture loss of discarding information that the array receives, the array aperture is extended by the vectorization operator. In order to deal with the effect of grid mismatch, an off-grid DOA estimation algorithm based on sparse Bayesian learning (SBL) is proposed in this paper. The temporal correlation between the neighboring snapshot numbers is considered in the off-grid algorithm. The computer simulation verifies the effectiveness of the proposed algorithms.

DOA Estimation for Coherently Distributed Sources Considering Circular and Noncircular Signals in Massive MIMO Systems

In mobile communication, the signal that a base station received cannot be regarded as a point source anymore because of the multipath propagation. A distributed source model is more suitable for the realistic scenarios. In this paper, an approach of direction-of-arrival (DOA) estimation is proposed for coherently distributed (CD) sources consisting of circular and noncircular signals in a massive or large-scale multiple-input multiple-output system. The noncircular characteristic can improve the performance of DOA estimation. However, most algorithms are not suitable for DOA estimation where circular and noncircular signals coexist. Based on the analysis of constraint conditions satisfied by the steering vector of mixed signals, a multiple signal classification (MUSIC) like approach is proposed for the DOA estimation of CD sources consisting of circular and noncircular signals. On the conditions of low signal-to-noise ratio, small snapshot numbers, and large source numbers, the pseudopeaking may appear. This phenomenon has been analyzed, and a modified MUSIC-like approach is proposed. Simulation results demonstrate that both two proposed algorithms can estimate more sources than the number of sensors. The estimation performances of the two proposed algorithms outperform the traditional MUSIC algorithm.

Distributed Parameter Estimation for Mobile Wireless Sensor Network Based on Cloud Computing in Battlefield Surveillance System

The construction of a battlefield surveillance system is very important for monitoring the attack of enemy aircrafts and missiles, which integrates various sensors and mobile devices. Then, multiple battlefield surveillance systems can be connected together to form a battlefield surveillance network. The mobile nodes can be deployed in a certain region to monitor enemy aircrafts and missiles. Thus, some important issues have to be solved efficiently, including the cooperation across the administrative domains of a cloud network, the direction-of-arrival (DOA), and a polarization estimation algorithm for a mobile wireless sensor network (MWSN). In this paper, the architecture of a battlefield surveillance system is constructed based on mobile cloud computing and 5G link. The root multiple signal classification (Root-MUSIC)-like algorithm is proposed for estimating the 1-D DOA and a polarization parameter with a uniform linear array. The Root-MUSIC algorithm is replaced by the Fourier transform, the former algorithm that can be extended to an arbitrary topology structure of a MWSN. Then, the proposed algorithm is extended to the 2-D DOA and a polarization estimation in further. Based on the deployment of different MWSNs, the estimation results of DOA and polarization parameters are fused in order to improve the estimation performance. Finally, the parameter information (DOA and polarization parameter) of enemy aircrafts and missiles can be achieved. The computer simulation verifies the effectiveness of the proposed algorithm. The proposed algorithm ensures the parameter estimation accuracy with a low computational complexity.

The Critical Patients Localization Algorithm Using Sparse Representation for Mixed Signals in Emergency Healthcare System

In this paper, a new architecture for the emergency healthcare system based on mobile cloud computation (MCC) and fifth-generation (5G) wireless link is proposed. Based on the processing speed of MCC and the communication rate of 5G scheme, this system can monitor and locate patients in real time. Multiple base stations of the massive multiple input multiple output cooperate with each other to locate the patients using cross-location method. Then, a new direction-of-arrival (DOA) estimation algorithm is proposed in the presence of unknown mutual coupling. The uncorrelated signals are first estimated using the estimation of signal parameters via rotational invariance technique algorithm. Then, these estimators construct the manifold matrix of uncorrelated signals to estimate the mutual coupling coefficients. The information about uncorrelated signals and mutual coupling is eliminated based on oblique projection technique in order to estimate the DOAs of coherent signals using the original array. Finally, the DOAs of coherent signals are achieved based on sparse representation theory. Simulation results demonstrate the effectiveness and performance of the proposed algorithm.

PD Source Diagnosis and Localization in Industrial High-Voltage Insulation System via Multimodal Joint Sparse Representation

Partial discharge (PD) is the manifestation of insulation degradation, and it is regarded as a great risk in the field of industrial high-voltage insulation system. In this paper, the direction-of-arrival (DOA) estimation algorithm is used for the localization of partial-discharge source. The intersecting point of two rays, which come from two different directions measured by two uniform linear arrays (ULAs), can be regarded as the plane location of partial-discharge source. Fast rise times of partial-discharge pulses result in a wide electromagnetic spectrum, thus this paper focuses on the DOA estimation of wideband signals. The technique of multimodal joint sparse representation (MJSR) has been used to improve the performance of biometrics recognition. Here, we extend it to DOA estimation. The received data are represented by a sparse linear combination of potential steering vectors, while constraining the observations from different frequencies subject to sharing the same sparsity pattern. Based on the simultaneous orthogonal matching pursuit (SOMP) and alternating direction method of multipliers (ADMM), a hard threshold algorithm is proposed for DOA estimation. In order to reduce the computational complexity of hard threshold algorithm, an improved soft threshold DOA estimation algorithm based on the ADMM is proposed as well. The effectiveness of the proposed algorithms is validated by simulations and real tests.

A Novel DOA Estimation Algorithm Using Array Rotation Technique

The performance of traditional direction of arrival (DOA) estimation algorithm based on uniform circular array (UCA) is constrained by the array aperture. Furthermore, the array requires more antenna elements than targets, which will increase the size and weight of the device and cause higher energy loss. In order to solve these issues, a novel low energy algorithm utilizing array base-line rotation for multiple targets estimation is proposed. By rotating two elements and setting a fixed time delay, even the number of elements is selected to form a virtual UCA. Then, the received data of signals will be sampled at multiple positions, which improves the array elements utilization greatly. 2D-DOA estimation of the rotation array is accomplished via multiple signal classification (MUSIC) algorithms. Finally, the Cramer-Rao bound (CRB) is derived and simulation results verified the effectiveness of the proposed algorithm with high resolution and estimation accuracy performance. Besides, because of the significant reduction of array elements number, the array antennas system is much simpler and less complex than traditional array.

The Application of DOA Estimation Approach in Patient Tracking Systems with High Patient Density

In this paper, an improved localization method named three-uniform-linear-array localization is proposed for patient track systems. Three receivers adopting a smart antenna technique cooperate with each other to locate the patients using the angulation positioning method. In order to be able to track patients in environment with high patient density, a high-resolution direction-of-arrival (DOA) estimation algorithm for the coexistence of noncircular and circular signals is proposed. First, the maximal and common noncircularity rated signals are preliminarily estimated. Second, based on the noise space block matrix, the DOAs of these signals are re-estimated with high accuracy. Then, the covariance matrix of the maximal and common noncircularity rated signals is reconstructed. The contributions of these signals are eliminated after performing a subtraction operation on the covariance matrix of the received data and only those of circular signals remain. Finally, the DOAs of circular signals are obtained. Results of simulations and real tests demonstrate the effectiveness and performance of the proposed algorithm.

A DOA Estimation Approach for Transmission Performance Guarantee in D2D Communication

In Device-to-Device (D2D) communications of massive Multiple-Input Multiple-Output (MIMO) system, the inter-channel interference (ICI) can severely deteriorate the entire system performance. The beamforming technique can be used to alleviate this situation. Thus the localization of the users’ equipment (UE) should be known as a prior. In wireless communication, due to the effect of multipath, the model of incident signal should be regarded as distributed sources instead of point sources. In this paper, we propose a 2-D DOA estimation algorithm for coherently distributed (CD) sources based on conformal array. First, three rational invariance relationships are constructed based on generalized steering vectors (GSVs). Then the propagator method (PM) is used for estimating three rational invariance matrices. Finally, the 2-D DOA of CD sources can be obtained from the eigenvalues of three rational invariance matrices. Without spectrum peaking searching, and estimation and eigendecomposition of sampling covariance matrix, the proposed algorithm has low computational complexity. For the condition with a large amount of data, the distributed and parallel PM is proposed to deal with this problem. Simulation results verify the effectiveness of the proposed algorithm.

A Low Energy Consumption DOA Estimation Approach for Conformal Array in Ultra-Wideband

Most direction-of-arrival (DOA) estimation approaches for conformal array suffer from high computational complexity, which cause high energy loss for the direction finding system. Thus, a low energy consumption DOA estimation algorithm for conformal array antenna is proposed in this paper. The arbitrary baseline direction finding algorithm is extended to estimate DOA for a conformal array in ultra-wideband. The rotation comparison method is adopted to solve the ambiguity of direction finding. The virtual baseline approach is used to construct the virtual elements. Theoretically, the virtual elements can be extended in the space flexibility. Four elements (both actual and virtual elements) can be used to obtain a group of solutions. The space angle estimation can be obtained by using sub-array divided technique and matrix inversion method. The stability of the proposed algorithm can be guaranteed by averaging the angles obtained by different sub-arrays. Finally, the simulation results verify the effectiveness of the proposed method with high DOA estimation accuracy and relatively low computational complexity.