A5053164461- Indoor and Outdoor Localization Technologies
- Target Tracking and Data Fusion in Sensor Networks
- Underwater Vehicles and Communication Systems
- PAPR reduction in OFDM
- Energy Efficient Wireless Sensor Networks
- Advanced Wireless Communication Technologies
- Distributed Sensor Networks and Detection Algorithms
- Wireless Communication Networks Research
- Power Line Communications and Noise
- Flow Measurement and Analysis
- Blind Source Separation Techniques
- Advanced Wireless Communication Techniques
- Advanced MIMO Systems Optimization
- IoT Networks and Protocols
- Structural Health Monitoring Techniques
- Sparse and Compressive Sensing Techniques
- Electromagnetic Compatibility and Noise Suppression
Ningbo University
2019-2025
In this paper, the target node localization problems based on hybrid RSS-AOA measurements in both noncooperative and cooperative three-dimensional (3-D) wireless sensor networks (WSNs) are discussed. By using novel error approximate expressions for received signal strength (RSS) angle-of-arrival (AOA) measurement models, new estimators least squares (LS) criterion proposed. These can be transformed into mixed semi-definite programming (SDP) second-order cone (SOCP) by applying convex...
Abstract This paper tackles the problem of signal‐to‐noise ratio estimation for cyclic prefix (CP)‐Less orthogonal frequency division multiplexing (OFDM) system in presence Gaussian noise over multipath fading channels. First, we introduce correlation CP‐Less OFDM signal with CP, and analyze correlations received signal. Second, isolate power from power. Finally, obtain close form expression SNR by using correlations. Computer simulation results verify effectiveness proposed method.
In this paper, we address the target localization problem based on hybrid range and angle measurements with unknown transmit power in both noncooperative cooperative scenarios, respectively. By analyzing approximate expressions of noise terms measurement models, an original nonconvex is formulated according to least square criterion. This transformed into a mixed semi-definite programing/second-order cone programing by using convex relaxation techniques. Computer simulation results verify...
This letter proposes a method for impulsive noise (IN) suppression in non-orthogonal multiple access (NOMA) downlink system by leveraging the graph signal processing (GSP) and ℓq-norm-based sparse recovery theories. Within GSP framework, we propose graph-based representation to characterize underlying structure of sub-carriers. Accordingly, Laplacian regularization (GLR) is defined capture similarities between Then, IN problem formulated as constraint optimization problem, incorporating...
In this letter, by using the effect of sensor motion on time delay and Doppler shift measurements, a semi-definite programming (SDP) solution is developed via convex relaxation to determine unknown source location. A novel constrained weighted least squares (CWLS) problem formulated according non-recursive measurement models without any approximation. After that, (SDR) performed transform CWLS into problem, which can guarantee global optimal solution. Simulation results show that proposed...
In this article, the multistatic localization problem with unknown propagation speed is investigated using differential delays and Doppler shifts between signals from direct indirect paths. A series of pseudolinear equations formulated via transformation measurement models. weighted least squares (WLS) formulation then proposed after ignoring second-order error terms, which can be rewritten as a nonconvex optimization relationships among variables included constraints. To deal nonconvexity...
This article develops a robust source localization method using time delay and Doppler shift measurements, where the sensor motion effect accompanied by location errors cannot be ignored. We begin transforming measurement models into series of nonlinear equations that take account, then construct constrained weighted least squares (CWLS) problem based on these equations. Because nonconvex nature problem, we relax it semidefinite programming (SDP) via convex relaxation further propose scheme...
Abstract Power line communication is severely affected by impulsive noise, especially asynchronous noise with high power spectral density and short duration. This paper presents an suppression method in system. Based on the component of background extracted from received signal using a null subcarrier matrix, sparse iterative covariance estimation proposed. A optimization problem for estimating formed based minimum matrix fitting criterion, then obtained algorithm. After that, estimated...