The 5G Localisation Waveform

Transcription

1 The 5G Localisation Waveform Ronald Raulefs, Armin Dammann, Thomas Jost, Michael Walter, Siwei Zhang German Aerospace Center (DLR) ETSI Workshop on Future Radio Technologies January 2016

2 DLR.de Chart 2 Our Goal: Ubiquitous Navigation Where GPS fails, we likely have dense mobile radio networks!

3 DLR.de Chart 3 Today s Mobile Radio Positioning Propagation Delay Based Positioning Propagation Model (BS MT) Path Loss BS 1 MT 1 Shadow Fading MT 3 BS 2 MT 2 BS 3 Time Difference of Arrival (TDOA) Requires 3 base stations

4 DLR.de Chart 4 What 5G Can Offer for Positioning Higher Frequencies Connectivity range decreases But if connected, it s LoS High Signal Bandwidths Higher ranging accuracy Less vulnerable against multipath propagation Cramer Rao Lower Bound for ranging equivalent signal bandwidth Device-to-Device (D2D) Communications Additional ranging measurements Much more 5G devices than today High number of devices in com range Number of range measurements grows quadratically # BS MT links: N MT N BS # D2D links (max): N MT (N MT -1) to solve for 3 N MT unknowns (x m, y m, T m )

5 DLR.de Chart 5 Cooperative Positioning BS 1 MT 1 Centralized, Network Centric MTs transmit to a central positioning unit. Central unit calculates position solutions for the MTs jointly. MT 3 MT 2 BS 2 Decentralized, MT Driven Each MT calculates its own position based on its own observations. MTs share their estimates (position and time base offset) BS 3 Works even if there are less than 3 base stations hearable!

6 DLR.de Chart 6 Performance Evaluation Non Coop. Positioning Accuracy d BS best case worst case outage probability: 82% Random distribution of a MT in triangular area between 3 BSs If the channel is in NLoS: Best case (solid lines): Consider as LoS (no NLoS bias) Worst case (dashed lines): Not connected There is a large outage!

7 DLR.de Chart 7 Performance Results Coop. Positioning Accuracy, Outage Probability worst case best case approx footballers per km² 1000 MTs per km² means 1 MT per 1000 m² 1000 m²

8 DLR.de Chart 8 5G Localization Waveforms Ranging Error Evaluation Cramer-Rao Lower Bound (CRLB) Example: Synchronization with LTE Primary Synchronization Sequences (PSS), with squared equivalent bandwidth Is tight for high SNR and does not account for the threshold effect. Therefore we use the Ziv-Zakai Lower Bound (ZZLB) with the localization signal s autocorrelation function φ(τ) and the Gaussian Q-function CRLB is tight for high SNRs Simulation results show threshold effect

9 DLR.de Chart 9 5G Localization Waveforms Triangular Waveform Power Spectrum Density Ranging Error Performance Autocorrelation ZZLB accounts for threshold effect ZZLB and CRLB diverge α = 1 provides the optimum

10 DLR.de Chart 10 5G Localization Waveforms Dircac-Rectangular Waveform Power Spectrum Density Ranging Error Performance Autocorrelation Provides maximum squared equivalent bandwidth β 2 = B 2 /4 for γ = 1. Optimum γ for different SNR ranges

11 DLR.de Chart 11 5G Localization Waveforms Dolph-Chebyshev Waveform Power Spectrum Density Ranging Error Performance Autocorrelation Parameter a controls ACF sidelobe attenuation Optimum a for different SNR ranges

12 DLR.de Chart 12 Conclusion 5G envisages properties which are beneficial for cooperative positioning D2D, M2M communication is the big step for positioning Our example: Devices per km² provide sub-meter accuracy 5G localisation waveform design for optimal ranging/positioning performance Power spectrum density form determines ranging performance Higher (equivalent) signal bandwidth better performance at high SNRs Take care about threshold effect choose appropriate sidelobe suppression 5G Positioning? Yes, 5G can! With promising positioning performance achieved by optimized localisation waveforms & cooperative positioning