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data-driven Bandpass Filter Design for Estimating Symbol Rate of Sporadic signal at Low SNR

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第4期21卷 2680-2694页

作者： Pei, Can Bi, Suzhi Quan, Zhi Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China

Symbol rate is one of the most important parameters in signal demodulation process. In real-time signal processing, traditional symbol rate estimation algorithms for the Multiple Phase Shift Keying (M-PSK) and the Multiple Quadrature Amplitude Modulation (M-QAM) are based on the Fourier transform of signal's complex envelope. At the low signal-to-noise ratio (SNR), the accuracy of symbol rate estimation can be improved by increasing the number of symbols as much as possible. However, this improvement is infeasible in many applications such as the energy-limited Internet of Things devices and sporadic noncooperative transmissions. In this paper, we propose a data-driven bandpass filter (BPF) design scheme for accurate estimation of symbol rate under low SNR with only a small number of symbols available. The proposed scheme considerably improves the estimation performance by optimizing the BPF design using the equivalent dynamic linearization model with time-varying pseudo-partial derivatives. Specifically, the proposed scheme iteratively optimizes the upper and lower cut-off frequencies of the BPF based on the measured complex envelope spectrum until achieving the optimal BPF. Therefore, the peaks of the complex envelope spectrum are extracted as the estimate of the symbol rate by applying the optimal BPF. Experimental results indicate the promise of the proposed scheme as an efficient symbol rate estimator for sporadic signal at low SNR and with a small number of symbols.

关键词： Estimation Band-pass filters signal to noise ratio Cutoff frequency Wavelet transforms Bandwidth signal processing algorithms Symbol rate estimation data-driven signal processing complex envelope spectrum digital filter design wireless communication

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data-driven Hybrid Beamforming for Uplink Multi-User MIMO in Mobile Millimeter-Wave Systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第11期21卷 9341-9350页

作者： Ma, Yuan Ren, Silei Quan, Zhi Feng, Zhiyong Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China

To enable user diversity while balancing tradeoffs between cost and flexibility, we exploit hybrid analog-digital beamforming for multi-user mobile systems. By combining array and spatial signal-processing techniques, highly directional beams can be formed with high beamforming gain to achieve sufficient link budget. In this way, fine selection of codewords for analog beamforming is essential to ensure the uplink rate, which may increase the latency of establishing a reliable communication link, especially for mobile millimeter-wave communication systems. In order to guarantee the reliability of communication, adaptive data-driven beam tracking is proposed to find the suitable beamformer/combiner pair to achieve the given signal-to-interference-plus-noise ratios constraint. Unlike the model-based approach, the proposed approach is dependent only on the real-time measurement data based on a dynamic linearization representation of a time-varying pseudo-gradient parameter estimation procedure. Numerical analyses show that the proposed beam tracking algorithm can achieve good tracking performance with lower training overhead compared with traditional schemes.

关键词： Array signal processing Radio frequency Wireless communication Uplink Antenna arrays Quality of service Millimeter wave communication Hybrid beamforming millimeter-wave communication data-driven signal processing pseudo-partial derivative adaptive control

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A TEST FOR CONDITIONAL CORRELATION BETWEEN RANDOM VECTORS BASED ON WEIGHTED U-STATISTICS 47

A TEST FOR CONDITIONAL CORRELATION BETWEEN RANDOM VECTORS BA...

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47th IEEE International Conference on Acoustics, Speech and signal processing (ICASSP)

作者： Vila, Marc Riba, Jaume Tech Univ Catalonia SPCOM UPC Signal Theory & Commun Dept Barcelona Spain

ISBN: (纸本)9781665405409

This article explores U-Statistics as a tool for testing conditional correlation between two multivariate sources with respect to a potential confounder. The proposed approach is effectively an instance of weighted U-Statistics and does not impose any statistical model on the processed data, in contrast to other well-known techniques that assume Gaussianity. By avoiding determinants and inverses, the method presented displays promising robustness in small-sample regimes. Its performance is evaluated numerically through its MSE and ROC curves.

关键词： Conditional Correlation U-Statistics Order Statistics data-driven signal processing Small Sample Regime

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data-driven Multi-armed Beam Tracking for Mobile Millimeter-Wave Communication Systems 96

Data-Driven Multi-armed Beam Tracking for Mobile Millimeter-...

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IEEE 96th Vehicular Technology Conference (VTC-Fall)

作者： Zhang, Shengdong Ma, Yuan Zhang, Xingjian Wang, Jian Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Harbin Inst Technol Sch Elect & Informat Engn Shenzhen 518055 Peoples R China Nanjing Univ Sch Elect Sci & Engn Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781665454681

The goal of the next-generation mobile communication system is higher data-rates, lower latency, and higher energy-efficient performance, which bring about the demands for fast beam tracking in time-varying mobile communication. With the development of large-scale antenna array technology, highly directional beams can be formed with limited radio frequency chains. However, traditional exhaustive searching scheme has unacceptable overhead that leads to great challenges for applying to mobile millimeter-wave environments. Fast beam tracking scheme therefore has been recognized as a key technology in millimeter wave communication. To address this issue, this paper proposes a data-driven multi-armed beam tracking scheme to select the beamforming/combining vectors that achieve the target quality of service based on the real-time measurement, rather than the prior knowledge such as channel and user mobility information in beamforming design. To further speed up the beam tracking process, multi-armed beam is created to sample multiple spatial directions simultaneously. Simulation results show that the proposed data-driven multi-armed beam tracking method could achieve fast beam tracking performance with high resolution and reduced training overhead.

关键词： Beam tracking millimeter-wave communication multi-armed beam data-driven signal processing

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data-driven Beam Tracking for Mobile Millimeter-Wave Communication Systems Without Channel Estimation

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IEEE WIRELESS COMMUNICATIONS LETTERS 2021年第12期10卷 2747-2751页

作者： Ma, Yuan Ren, Silei Chen, Wei Quan, Zhi Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

In order to guarantee the reliability of millimeter-wave communication under user mobility, fast beam tracking is essential to adapt the beamforming vectors in time-varying beamspace channels. To find the best beam alignment, traditional exhaustive search scans all possible beam directions, thus introducing up to seconds of delay for wireless networks to accommodate mobile clients. In this letter, we propose a data-driven beam tracking approach to find the beamforming/combining vectors that achieve the target quality of service based on a series of equivalent dynamic linearization data models with a time-varying pseudo-gradient parameter estimation procedure. Unlike the model-based approach, which requires the prior knowledge about the channel and user mobility in beamforming design, the proposed data-driven approach depends only on the real-time measurement data. Numerical analyses show that the proposed data-driven beam tracking algorithm can achieve reliable tracking performance with much shorter alignment time compared to traditional schemes.

关键词： Array signal processing Radio frequency Target tracking signal to noise ratio Quality of service data models Real-time systems Beam tracking millimeter-wave communication data-driven signal processing pseudo-partial derivative

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data-driven Measurement of Receiver Sensitivity in Wireless Communication Systems

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第5期67卷 3665-3676页

作者： Ma, Yuan Wang, Xu Quan, Zhi Poor, H. Vincent Shenzhen Univ Coll Informat Engn Shenzhen 518060 Peoples R China Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

Receiver sensitivity is one of the most important parameters in determining the overall performance of a radio frequency communication system. The traditional receiver sensitivity measurement is to use exhaustive search in a specified range to identify the receiver's sensitivity. However, such an exhaustive search is neither efficient in terms of measurement time, nor accurate due to the fixed step-size. In this paper, a data-driven approach is proposed to measure the receiver sensitivity based on a dynamic linearization representation of a timevarying pseudo-gradient parameter estimation procedure. Unlike the model-based approach, the proposed data-driven approach is dependent only on the input and output measurement data. Furthermore, an analytical approach is presented to derive the minimum number of test packets needed to satisfy the desired confidence level for packet error rate estimation. By adapting the number of test packets, the proposed approach can converge to the exact receiver sensitivity with less time. A theoretical analysis of the proposed approach is provided and further validated by numerical analyses and real-world experimental verification. These analyses show that the proposed data-driven sensitivity measurement can a achieve good estimation performance within a few iterations as well as reduce measurement time.

关键词： Receiver sensitivity radio frequency wireless communication systems data-driven signal processing pseudo partial derivative statistical analysis

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data-driven SIMULATION USING THE NUCLEAR NORM HEURISTIC 44

DATA-DRIVEN SIMULATION USING THE NUCLEAR NORM HEURISTIC

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44th IEEE International Conference on Acoustics, Speech and signal processing (ICASSP)

作者： Dreesen, Philippe Markovsky, Ivan VUB Brussels Belgium

ISBN: (纸本)9781479981311

Applications of signal processing and control are classically model-based, involving a two-step procedure for modeling and design: first a model is built from given data, and second, the estimated model is used for filtering, estimation, or control. Both steps typically involve optimization problems, but the combination of both is not necessarily optimal, and the modeling step often ignores the ultimate design objective. Recently, data-driven alternatives are receiving attention, which employ a direct approach combining the modeling and design into a single step. In earlier work, it was shown that datadriven signal processing problems can often be rephrased as missing data completion problems, where the signal of interest is part of an incomplete low-rank mosaic Hankel structured matrix. In this paper, we consider the exact data case and the problem of simulating from a given input, an output trajectory of the unknown data generating system. Our findings suggest that, when using an adequate rescaling of the given data, the exact data-driven simulation problem can be solved by replacing the original structured low-rank matrix completion problem by a convex optimization problem, using the nuclear norm heuristic.

关键词： data-driven signal processing low-rank matrix completion mosaic Hankel matrix nuclear norm convex optimization

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