Xuerong Cui

Threshold Selection for Ultra-Wideband TOA Estimation based on Neural Networks

Because of the good penetration into many common materials and inherent fine resolution, Ultra-Wideband (UWB) signals are widely used in remote ranging and positioning applications. On the other hand, because of the high sampling rate, coherent Time of Arrival (TOA) estimation algorithms are not practical for low cost, low complexity UWB systems. In order to improve the precision of TOA estimation, an Energy Detection (ED) based non-coherent TOA estimation algorithm using Artificial Neural Networks (ANN) is presented which is based on the skewness after energy detection. The expected values of skewness and kurtosis with respect to the Signal to Noise Ratio (SNR) are investigated. It is shown that the skewness is more suitable for TOA estimation. The best threshold values for different SNRs are investigated and the effects of integration period and channel modes are examined. Comparisons with other ED based algorithms show that in CM1 and CM2 channels, the proposed algorithm provides higher precision and robustness in both high and low SNR environments.

Threshold selection for ultra-wideband TOA estimation based on skewness analysis

Because of the high sampling rate, coherent Time of Arrival (TOA) estimation algorithms are not practical for low cost, low complexity Ultra-Wideband (UWB) systems. In this paper, an Energy Detection (ED) based non-coherent TOA estimation algorithm is presented. The expected values of skewness and kurtosis with respect to the Signal to Noise Ratio (SNR) are investigated. It is shown that the skewness is more suitable for TOA estimation. To improve the precision of TOA estimation, a new threshold selection algorithm is proposed which is based on skewness analysis. The best threshold values for different SNRs are investigated and the effects of integration period and channel modes are examined. Comparisons with other ED based algorithms show that in CM1 and CM2 channels, the proposed algorithm provides higher precision and robustness in both high and low SNR environments.

3-D TDOA/AOA location based on Extended Kalman Filter

In this paper, we propose a Time Difference Of Arrival/Angle-Of-Arrival (TDOA/AOA) location algorithm based on Extended Kalman Filter (EKF) for three-dimension scenario. Azimuth, angle of pitching and TDOA are constructed into a vector model for the EKF, and we can get the location of Mobile Station (MS).

Vehicle Positioning Using 5G Millimeter-Wave Systems

Recent growth in traffic and the resulting congestion and accidents has increased the demand for vehicle positioning systems. Existing global navigation satellite systems were designed for line of sight environments and thus accurately determining the location of a vehicle in urban areas with tall buildings or regions with dense foliage is difficult. Fifth generation (5G) cellular networks provide device-to-device communication capabilities which can be exploited to determine the real-time location of vehicles. Millimeter-wave (mmWave) transmission is regarded as a key technology for 5G networks. This paper examines vehicle positioning using 5G mmWave signals. Both a correlation receiver and an energy detector are considered for timing estimation. Furthermore, fixed and dynamic thresholds for energy detection are examined. It is shown that a correlation receiver can provide excellent ranging accuracy but has high computational complexity, whereas an energy detector has low computational complexity and provides good ranging accuracy. Furthermore, the Gaussian raised-cosine pulse (RCP), Gaussian pulse, and Sinc-RCP impulse radio waveforms provide the best performance.

Remotely-sensed TOA interpretation of synthetic UWB based on neural networks

Because of the good penetration into many common materials and inherent fine resolution, Ultra-Wideband (UWB) signals are widely used in remote sensing applications. Typically, accurate Time of Arrival (TOA) estimation of the UWB signals is very important. In order to improve the precision of the TOA estimation, a new threshold selection algorithm using Artificial Neural Networks (ANN) is proposed which is based on a joint metric of the skewness and maximum slope after Energy Detection (ED). The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for the IEEE802.15.4a channel models CM1 and CM2, the proposed ANN algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

Real-Time Positioning Based on Millimeter Wave Device to Device Communications

Current generation mobile wireless communication networks are not suitable for real-time positioning applications because timing information is not readily available. Fifth generation (5G) cellular networks provide device to device real-time communications which can be used for real-time positioning. Millimeter-wave (mmWave) transmission is regarded as a key technology in 5G networks. In this paper, several 73-GHz mmWave waveforms are investigated. A new threshold selection algorithm for energy detector-based ranging is proposed which employs a dynamic threshold based on an artificial neural network. The positioning performance using this algorithm with mmWave waveforms is investigated.

Threshold Selection for TOA Estimation based on Skewness and Slope in Ultra-wideband Sensor Networks

Accurate localization has gained significant interest within sensor networks but because of the high sampling rate, Matched Filter (MF) based coherent Time of Arrival (TOA) estimation algorithms are not practical for low cost, low complexity Ultra-wideband (UWB) ranging, positioning and tracking systems. In this paper, an Energy Detection (ED) based non-coherent TOA estimation algorithm is presented where the TOA is estimated via Threshold Crossing (TC). The expected values of skewness, maximum slope, kurtosis and standard deviation with respect to the Signal to Noise Ratio (SNR) are investigated using the IEEE 802.15.4a Channel Models (CM). It is shown that the skewness and maximum slope are more sensitive to the SNR and thus more suitable for TOA estimation. To improve the precision of ED based TOA estimation, especially in low SNR environments, a new threshold selection algorithm is proposed which is based on a joint metric of the skewness and maximum slope. The best threshold values for different SNRs are investigated and the effects of integration period and channel models are examined. Comparisons with other ED based algorithms show that in both the CM1 and CM2 channels, the joint metric provides higher precision and robustness in both high and low SNR environments.

Low Complexity Codebook-Based Beam Switching for 60 GHz Anti-Blockage Communication

A low complexity solution to the 60 GHz link- blockage problem is proposed based on the codebook beam switching technique. The directional link is easily blocked by a moving person, which is regarded as one of the severe problems in 60 GHz communication. Codebook based beam switching is a feasible technique to resolve the link-blockage by switching the beams from the blocked path to a backup reflection path. Typically, the selection of the best reflection path is crucial. Based on beam training mechanism, an ordered beam pair list (OBPL) of reflection paths is proposed for more accurate path selection and rapid link switching. Based on the OBPL, a complete and closed-form beam switching process is developed, which can apply for blockages of both LOS path and reflection NLOS paths. The link-blockage detection and LOS link- recovery detection are investigated. Theoretical analysis and numerical results show that for IEEE 802.15.3c indoor channel model, the proposed scheme has a good performance in complexity, applicability and system throughput. 

A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks

Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.

Multi-user Interference Mitigation in TH-PPM UWB Systems

This paper considers the influence of multi-user interference (MUI) on an impulse radio ultra-wideband (UWB) communication system. Binary pulse position modulation is employed with time hopping (TH) for multiple access communications. The users are assumed to transmit asynchronously. A technique to reduce the MUI is presented. It is shown that this approach is effective for UWB systems in both additive white Gaussian noise (AWGN) and IEEE 802.15.3a channels.