July. 2005 C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE 802. 15-05-0426-01-004a Submission Slide 1 Project: IEEE P802.15 Working Group for Wireless Personal.

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Presentation transcript:

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 1 Project: IEEE P Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [Robust Ranging Algorithm for UWB radio] Date Submitted: [19 July, 2005] Source: [Cheolhyo Lee (1), Jae Young Kim (1), Eun Chang Choi (1), Chong Hyun Lee (2)] Company [(1) Electronics and Telecommunications Research Institute (ETRI) (2) Seokyeong University] Address [(1) 161 Gajeong-dong, Yuseong-gu, Daejeon, Republic of Korea (2) 16-1 Jungneung-Dong, Sungbuk-Ku, Seoul, Republic of Korea] Voice :[(1) , (2) ], FAX: [(1) (2) ] [(1) (2) Abstract:[The robust ranging algorithm is proposed for the alternative PHY for a] Purpose:[This submission is in response to the committees request to submit the proposal enabled by an alternate TG4a PHY] Notice:This document has been prepared to assist the IEEE P It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release:The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 2 Robust Ranging Algorithm for UWB Radio Electronics and Telecommunications Research Institute (ETRI) Seokyeong University Republic of Korea

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 3 Proposed Algorithm Proposed algorithm flow & summary Comparisons of complexities with MERL and I2R Simulations for CM1 Simulations for CM8 Conclusions Outline

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 4 Proposed Algorithm TOA Estimator BPF ( ) 2 LPF / 1-4ns integrator ADC Add few Frames & Compute Energy FFT Convert Time to Frequency High Resolution Algorithm SNR Increase Compute Energy

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 5 Other Architectures for Comparison TOA Estimator BPF ( ) 2 LPF / 2-4ns integrator ADC 1D to 2D Conversion Length-3 Vertical Median or Minimum Filtering Removes interference 2D to 1D Conversion with Energy Combining Energy image generation "Path-arrival dates" table 1D to 2D Conversion Assumption path synchronization Matrix Filtering + Assumption/path selection Time base 1-2ns accuracy Time stamping Analog comparator Sliding Correlator Energy combining across symbols interference suppression 1D-2D Conversion 2D-1D Conversion Energy image generation Bipolar template MERL I2RI2R FT R&D

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 6 Finding the Subspace Finding Spectrum Finding TOA Proposed Algorithm Flow Algorithm based High Resolution TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 7 Proposed Algorithm Summary Required Operation: – Correlation – FFT – Comparison Complexity (N: No. of Energy Block) – R: N point Correlation – FFT: N point FFT – Noise Subspace: N point scalar and vector multiplication – Peak Finding: N point comparison

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 8 Complexity of the Proposed Algorithms AlgorithmComplexity N = 32 Accumulation of signals (Preamble symbols-1) x 31 chip sequences adds. 992 op. (= 32 x 31, assuming preamble symbols is 31) N point FFT (Two FFTs) 2x(N/2)log 2 N complex mults. 2xNlog 2 N complex additions 960 op. (=2x80 complex mults= 2x4x80 real mults. + 2x2x80 real adds.) 640 op. (= 2x160 complex adds. = 2x320 real adds.) Correlation3xN*N real multiplication 3xN*(N-1) real addition 3072 op. (=3x1024 real mults.) 2976 op. (= 3x992 real adds.) SubspaceN complex multiplication192 op. (=128 real mults real adds.) Finding PeaksN-1 Comparison31 comparisons Total Operations 8863 op. ( Complexity O(N 2 ) ) Memory sizeN32

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 9 Complexity of Algorithm by MERL AlgorithmComplexityN = 32 N x N image*(N x N) x 3 rearrange operations 3072 op. (= 32 x 32 x 3) 2D to 1D conversion (Preamble symbols-1) x 31 chip sequences adds. 992 op. (= 31 x 32) Total operation4064 op. ( Complexity O (N 2 ) ) Memory sizeN x N = N * Sorting (3 point Median Filtering) = 3 2 rearrange operations = (Compare & allocation) = 9 - Complexity Ratio = Proposed/MERL = 8863/4064 = 218% -> Two times

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 10 Complexity of Algorithm by I2R AlgorithmComplexityN = 32 Sliding CorrelationN*N real adds.1024 real adds. N/2 x N imagesliding correlation x 31 chip sequences op. (= 1024 x 31) 2D to 1D conversion (Preamble symbols-1) x 31 chip sequences adds. 465 op. (= 15 x 31) Total operation32209 op. (= ) ( Complexity O(N 3 ) ) Memory sizePreamble symbols x 31 chip sequences 496 (= 16 x 31) - Complexity Ratio = Proposed/I2R = 8863/32209 = 27.4% -> less than I2R

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 11 Simulation Parameters for CM1 CM1 Channel considered Ts = 1ns SNR 8~22dB 10 Frames are accumulated. Three High Resolution Algorithms Compare with MERL True TOA = 10

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 12 Simulation Results SNR 8dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 13 Simulation Results SNR 8dB True TOA High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 14 SNR 9dB True TOA Simulation Results

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 15 SNR 9dB True TOA High Resolution TOAVSMERL Simulation Results

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 16 Simulation Results SNR 14dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 17 Simulation Results SNR 14dB True TOA High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 18 Simulation Results SNR 17dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 19 Simulation Results SNR 17dB True TOA High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 20 Simulation Results SNR 22dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 21 Simulation Results SNR 22dB True TOA High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 22 Simulation Parameters for CM8 CM8 Channel considered Window length = 64 Ts = 1ns SNR 10~22dB 5 Frames are accumulated. High Resolution Algorithms Compare with MERL True TOA = 10

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 23 Simulation Results SNR 10dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 24 Simulation Results SNR 10 dB High Resolution TOAVSMERL True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 25 Simulation Results SNR 11dB True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 26 Simulation Results SNR 11 dB High Resolution TOAVSMERL True TOA

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 27 Simulation Results SNR 13dB

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 28 Simulation Results SNR 13dB High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 29 Simulation Results SNR 17dB

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 30 Simulation Results SNR 17dB High Resolution TOAVSMERL

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 31 Key Issue Complexity – FFT is just the order of O(Nlog 2 (N))=> O(N) – What is the complexity of correlator? -> equal or greater than O(N 2 ) It depends on how many correlation operation is required – Order of complexity Proposed algorithm = MERL < I2R Proposed algorithmMERLI2R ComplexityO(N 2 ) O(N 3 )

July C. Lee, J. Kim, E. Choi, C. Lee doc.: IEEE a Submission Slide 32 Conclusions Advantages – Low complexity and high performance – Small memory size – High performance for low SNR and SINR – Can be applied to Coherent system – Small TOA estimation error (by CM8 simulation) – Independent to signal waveform Future works – Need comprehensive simulation – Consider the SOP environment