1 / 21

On Tap Angular Spread and Kronecker Structure of WLAN Channel Models

On Tap Angular Spread and Kronecker Structure of WLAN Channel Models. Qinghua Li (Intel) Kai Yu (KTH) Minnie Ho (Intel) Jeng Lung (Intel) David Cheung (Intel) Cliff Prettie (Intel). Outline. Motivation Measurement Environments Data Processing FD-SAGE algorithm

jpatricia
Download Presentation

On Tap Angular Spread and Kronecker Structure of WLAN Channel Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. On Tap Angular Spread and Kronecker Structure of WLAN Channel Models Qinghua Li (Intel) Kai Yu (KTH) Minnie Ho (Intel) Jeng Lung (Intel) David Cheung (Intel) Cliff Prettie (Intel) Q. Li (Intel), K. Yu (KTH), et al

  2. Outline • Motivation • Measurement Environments • Data Processing • FD-SAGE algorithm • Estimation performance in synthetic channels • RMS Angular Spread • Cluster identification • Tap angular spread • Cluster angular spread • Verification of Kronecker Product Structure Q. Li (Intel), K. Yu (KTH), et al

  3. Verification of Two Assumptions • Tap angular spread — an important modeling assumption • 5o tap angular spread • One path per tap within one cluster Q. Li (Intel), K. Yu (KTH), et al

  4. Kronecker Product Structure for Spatial Correlation • The spatial correlation matrix of each tap is assumed to the Kronecker product of the transmit and receive correlation matrixes. • The spatially correlated channel matrix is given by Q. Li (Intel), K. Yu (KTH), et al

  5. Measurements • Typical large office • Access point antenna is mounted under ceiling • Station antennas could be blocked by cubicle walls and file cabinets • 3’ x 6’ and 1.5’ x 1.5’ antenna crosses 6’ AP (mounted under ceiling) STA (at desk level) Q. Li (Intel), K. Yu (KTH), et al

  6. Signal Processing Algorithm • Joint estimation of delay, angle, and channel gain • Maximum likelihood • Space-alternating generalized expectation-maximization (SAGE) : grouped coordinate ascent search algorithm where Q. Li (Intel), K. Yu (KTH), et al

  7. Signal Processing Algorithm • SAGE Performance in synthetic channels • About 3o angle resolution o : synthetic x : estimated 12 10 8 Path Magnitude 6 4 2 0 300 250 400 200 350 150 300 250 100 200 50 150 0 100 Excess Delay (ns) o Incident Angle ( ) Q. Li (Intel), K. Yu (KTH), et al

  8. Cluster Identification • Power delay profile • Single exponential decay curve • RMS delay spread about 50 ns -80 -90 -100 -110 Average Received Power (dB) -120 -130 -140 -150 0 200 400 600 800 1000 1200 1400 1600 Excess Delay (ns) Q. Li (Intel), K. Yu (KTH), et al

  9. -3 x 10 5 4 3 2 1 0 300 250 200 150 350 300 250 100 200 150 100 50 50 0 o Incident Angle ( ) Cluster Identification • 3D multipath profile Path Magnitude Excess Delay (ns) Q. Li (Intel), K. Yu (KTH), et al

  10. -3 x 10 4 60 ns 2 0 0 50 100 150 200 250 300 350 -3 x 10 4 90 ns 2 0 0 50 100 150 200 250 300 350 -3 x 10 4 120 ns 2 0 0 50 100 150 200 250 300 350 Incident Angle (o) Time Slice of Multipath Profile • Multipath arrivals at delay 60 ns, 90 ns, and 120 ns Q. Li (Intel), K. Yu (KTH), et al

  11. Incident Angle (o) Cluster Identification • 2D filtering in angle-delay domain • Six clusters are identified Q. Li (Intel), K. Yu (KTH), et al

  12. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 5 10 15 20 RMS Angular Spread • Two sets of measurements with 50ns RMS delay spread, 112 taps, and 12 clusters • Cumulative distribution function of tap angular spread : mean 13.2o • Average cluster angular spread : 14.6o • Conclusion : Cluster AS ≈ Tap AS CDF RMS angular spread for each tap (o) Q. Li (Intel), K. Yu (KTH), et al

  13. Covariance Matrices Assume N x M channel matrix H, we estimate • Channel covariance matrix for tap L: • Covariance matrix at Tx for tap L: • Covariance matrix at Rx for tap L: Q. Li (Intel), K. Yu (KTH), et al

  14. Mismatches in Kronecker Structure • To evaluate the Kronecker Structure of MIMO channel covariance matrix, we define: • Normalized Residual for each tap • Wideband Model Error Q. Li (Intel), K. Yu (KTH), et al

  15. Measurement Results • Normalized Residuals for data set 14 30 Data set 14, 2x2 case 25 20 Normalized Residuals (%) 15 10 5 0 30 40 50 60 70 80 90 100 110 120 Tap Index Q. Li (Intel), K. Yu (KTH), et al

  16. 25 20 15 Wideband Model Error (%) 10 Data set 14: NLOS Data set 7: roughly LOS 5 0 1 2 3 4 5 6 7 8 Number of Receive Antenna Elements Wideband Model Errors • Error increases with number of antennas Q. Li (Intel), K. Yu (KTH), et al

  17. Summary • Large array measurements • Joint angle, delay, and gain estimation (SAGE) • Multiple clusters may arrive within few taps and they can’t be identified from a single exponential decay curve • Cluster Angular Spread ≈ Tap Angular Spread. • Model error introduced by Kronecker structure increases with the number of antennas Q. Li (Intel), K. Yu (KTH), et al

  18. Appendix • Power delay profile (STN) • Single exponential decay curve • RMS delay spread about 54 ns -80 -90 -100 -110 Average Received Power (dB) -120 -130 -140 -150 0 200 400 600 800 1000 1200 1400 1600 Time Delay (ns) Q. Li (Intel), K. Yu (KTH), et al

  19. -3 x 10 4 3 2 1 0 35 30 25 20 15 400 350 300 250 10 200 150 100 5 50 0 Appendix (Cont’d) • 3D multipath profile Path Magnitude Excess Delay (ns) o Incident Angle ( ) Q. Li (Intel), K. Yu (KTH), et al

  20. Appendix (Cont’d) • 2D filtering in angle-delay domain • Manually identified 7 clusters together with 3D-image Q. Li (Intel), K. Yu (KTH), et al

  21. Appendix (Cont’d) • Cumulative distribution function of tap angular spread ; mean value: 11.5o • Average cluster angular spread : 14.1o • Conclusion : Cluster AS ≈ Tap AS 1 0.9 0.8 0.7 0.6 Cumulative Distribution Function 0.5 0.4 0.3 0.2 0.1 0 5 10 15 20 25 30 Angular Spread for each tap (degree) Q. Li (Intel), K. Yu (KTH), et al

More Related