5G Positioning and Mapping With Diffuse Multipath

5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters(delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods breakdown or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.

[1]  Henk Wymeersch,et al.  Tensor Decomposition Based Beamspace ESPRIT for Millimeter Wave MIMO Channel Estimation , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[2]  Bernard H. Fleury,et al.  First- and second-order characterization of direction dispersion and space selectivity in the radio channel , 2000, IEEE Trans. Inf. Theory.

[3]  Robert W. Heath,et al.  Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems , 2014, IEEE Journal of Selected Topics in Signal Processing.

[4]  Henk Wymeersch,et al.  A Simple Method for 5G Positioning and Synchronization without Line-of-Sight , 2018, 1812.05417.

[5]  Florian Roemer,et al.  Higher-Order SVD-Based Subspace Estimation to Improve the Parameter Estimation Accuracy in Multidimensional Harmonic Retrieval Problems , 2008, IEEE Transactions on Signal Processing.

[6]  Katsuyuki Haneda,et al.  Sixty gigahertz indoor radio wave propagation prediction method based on full scattering model , 2014 .

[7]  Florian Roemer,et al.  Multi-dimensional model order selection , 2011, EURASIP J. Adv. Signal Process..

[8]  Henk Wymeersch,et al.  Position and Orientation Estimation Through Millimeter-Wave MIMO in 5G Systems , 2017, IEEE Transactions on Wireless Communications.

[9]  Jieping Ye,et al.  Detection of number of components in CANDECOMP/PARAFAC models via minimum description length , 2016, Digit. Signal Process..

[10]  Lin Gao,et al.  5G mmWave Cooperative Positioning and Mapping Using Multi-Model PHD Filter and Map Fusion , 2020, IEEE Transactions on Wireless Communications.

[11]  Henk Wymeersch,et al.  Impact of Rough Surface Scattering on Stochastic Multipath Component Models , 2018, 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).

[12]  Fredrik Tufvesson,et al.  5G mmWave Positioning for Vehicular Networks , 2017, IEEE Wireless Communications.

[13]  P. Stoica,et al.  Decoupled estimation of DOA and angular spread for spatially distributed sources , 1999 .

[14]  Rick S. Blum,et al.  Low-Rank Tensor Decomposition-Aided Channel Estimation for Millimeter Wave MIMO-OFDM Systems , 2016, IEEE Journal on Selected Areas in Communications.

[15]  Joos Vandewalle,et al.  A Multilinear Singular Value Decomposition , 2000, SIAM J. Matrix Anal. Appl..

[16]  Bo Ai,et al.  A Framework of Automatic Clustering and Tracking for Time-Variant Multipath Components , 2017, IEEE Communications Letters.

[17]  İsmail Güvenç,et al.  Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation , 2020, IEEE Access.

[18]  Iickho Song,et al.  Low-complexity estimation of 2D DOA for coherently distributed sources , 2003, Signal Process..

[19]  Shahrokh Valaee,et al.  Distributed source localization using ESPRIT algorithm , 2001, IEEE Trans. Signal Process..

[20]  Lajos Hanzo,et al.  Joint Angle Estimation and Signal Reconstruction for Coherently Distributed Sources in Massive MIMO Systems Based on 2-D Unitary ESPRIT , 2017, IEEE Access.

[21]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[22]  Sheng Chen,et al.  Harmonic Retrieval Based Baseband Channel Estimation for Millimeter Wave OFDM Systems , 2019, IEEE Transactions on Vehicular Technology.

[23]  Souleymen Sahnoun,et al.  Multidimensional ESPRIT for Damped and Undamped Signals: Algorithm, Computations, and Perturbation Analysis , 2017, IEEE Transactions on Signal Processing.

[24]  Andrzej Cichocki,et al.  CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping , 2012, IEEE Transactions on Signal Processing.

[25]  Hüseyin Arslan,et al.  Time Dispersion and Delay Spread Estimation for Adaptive OFDM Systems , 2008, IEEE Transactions on Vehicular Technology.

[26]  Theodore S. Rappaport,et al.  Millimeter Wave Channel Modeling and Cellular Capacity Evaluation , 2013, IEEE Journal on Selected Areas in Communications.

[27]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[28]  Moe Z. Win,et al.  High-Accuracy Localization for Assisted Living: 5G systems will turn multipath channels from foe to friend , 2016, IEEE Signal Processing Magazine.

[29]  Tamara G. Kolda,et al.  Tensor Decompositions and Applications , 2009, SIAM Rev..

[30]  Danijela Cabric,et al.  Tracking Sparse mmWave Channel: Performance Analysis Under Intra-Cluster Angular Spread , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[31]  Yide Wang,et al.  Efficient DSPE algorithm for estimating the angular parameters of coherently distributed sources , 2008, Signal Process..

[32]  Anil K. Jain Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[33]  Florian Roemer,et al.  Analytical Performance Assessment of Multi-Dimensional Matrix- and Tensor-Based ESPRIT-Type Algorithms , 2014, IEEE Transactions on Signal Processing.

[34]  Florian Roemer,et al.  Tensor-Structure Structured Least Squares (TS-SLS) to Improve the Performance of Multi-Dimensional Esprit-Type Algorithms , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[35]  Youming Sun,et al.  Computational Efficient Two-Dimension DOA Estimation for Incoherently Distributed Noncircular Sources With Automatic Pairing , 2017, IEEE Access.

[36]  E. Vitucci,et al.  Measurement and Modelling of Scattering From Buildings , 2007, IEEE Transactions on Antennas and Propagation.

[37]  Zhi Chen,et al.  Channel Estimation for Millimeter-Wave Multiuser MIMO Systems via PARAFAC Decomposition , 2016, IEEE Transactions on Wireless Communications.

[38]  Jian Yu,et al.  Clustering Enabled Wireless Channel Modeling Using Big Data Algorithms , 2018, IEEE Communications Magazine.

[39]  Gang Li,et al.  A low-complexity estimator for incoherently distributed sources with narrow or wide spread angles , 2007, Signal Process..

[40]  Henk Wymeersch,et al.  Tensor Decomposition-based Beamspace Esprit Algorithm for Multidimensional Harmonic Retrieval , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[41]  An Liu,et al.  Cloud-Assisted Cooperative Localization for Vehicle Platoons: A Turbo Approach , 2020, IEEE Transactions on Signal Processing.

[42]  Andrzej Cichocki,et al.  Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria , 2017, IEEE Transactions on Signal Processing.

[43]  Yide Wang,et al.  Efficient Subspace-Based Estimator for Localization of Multiple Incoherently Distributed Sources , 2008, IEEE Transactions on Signal Processing.