1 / 14

Channel Coherence Time

Channel Coherence Time. Date: 2009-07-13. Authors:. Introduction. For features like beamforming, SDMA, etc. that require feedback, the coherence time of the channel is the actual parameter that is important in determining the timeliness of the feedback

cheil
Download Presentation

Channel Coherence Time

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. Channel Coherence Time Date: 2009-07-13 Authors: Eldad Perahia, Intel Corporation

  2. Introduction • For features like beamforming, SDMA, etc. that require feedback, the coherence time of the channel is the actual parameter that is important in determining the timeliness of the feedback • Objective of this presentation is to compute the coherence time of the measured data in [1] and compare it to the 11n channel model Eldad Perahia, Intel Corporation

  3. Analysis Methodology • In the 11n channel model, Doppler was set to 1.2 km/hour (which sets the coherence time of the channel) but the estimate of Doppler was based on the amplitude of measured data • Doppler function resulted in a coherence time of 57 ms based on equation in [2] • Coherence time typically defined as time over which the time correlation function is above 0.5 [3] • We will examine autocorrelation functions of the 11n channel model and the measured data [1] using both complex data and amplitude data • As will be shown, Doppler and coherence time analysis needs to be based on complex data Eldad Perahia, Intel Corporation

  4. Example of the time progression of a single subcarrier of 11n channel model D TGn Channel Model Example Eldad Perahia, Intel Corporation

  5. Autocorrelation of complex data at 0.5 = 54 ms Coherence time computed by equation in [2] = 57 ms Very close agreement Autocorrelation of TGn Channel Model (1/2) Eldad Perahia, Intel Corporation

  6. Autocorrelation of the amplitude of the data results in long autocorrelation time (435 ms @ 0.5) Phase of the data is critical to accurate computation of the autocorrelation function Autocorrelation @ 0.5 = 35 ms Autocorrelation of TGn Channel Model (2/2) Eldad Perahia, Intel Corporation

  7. Measured data is comprised of 3x3 link This is an example of the time progression of a single subcarrier of a single Tx and Rx antenna combination i.e. H[1,2] for subcarrier 1 Example of Measured Data Eldad Perahia, Intel Corporation

  8. Autocorrelation of Complex Measured Data Eldad Perahia, Intel Corporation

  9. Top figure is the autocorrelation function of the amplitude of the data Bottom figure is the autocorrelation function of the phase of the data In comparison to the previous slide, in this example the phase of the data dominates the autocorrelation function Autocorrelation of Measured Data Eldad Perahia, Intel Corporation

  10. Data Processing (1/2) • For each pair of Tx and Rx antennas in the 3x3 link, an autocorrelation function was computed for time progression of a each subcarrier of the complex data, as illustrated in slide 8 • Time over which the time correlation function is above 0.5 (coherence time) was found from these autocorrelation functions Eldad Perahia, Intel Corporation

  11. These values were grouped to form a CDF of coherence times for each link CDFs were computed for the data for all the links in [1] 90% probability and 50% probability points are examined Data Processing (2/2) Eldad Perahia, Intel Corporation

  12. As described in [1], the type of motion between the transmitter and receiver is categorized as follows someone waving their hands in front of the device at both ends of the link (Double Motion, DM) someone waving their hands in front of the device at one end of the link (Single Motion, SM) many people known to be walking around (People Motion, PM) typical motion in office environment (Light Motion, LM) 90% probability coherence times are averaged together for links with the same type of motion 50% probability coherence times are averaged together for links with the same type of motion Coherence Time Results Eldad Perahia, Intel Corporation

  13. Conclusion • Channel coherence time of the measured data is twice as long as the 11n channel even in the highest motion case where someone was waving their hands in front of the device at both ends of the link • In typical office environment, the channel coherence time was 5-10x longer than the 11n channel model • 11ac channel model must be modified to better match measured channel coherence times • We welcome further measurements from other companies in order to properly model channel coherence time for TGac channel model Eldad Perahia, Intel Corporation

  14. References • [1] Perahia, E., Kenney., T., Stacey, R., et. al., Investigation into the 802.11n Doppler Model, IEEE 802.11-09/538r0, May 11, 2009 • [2] Erceg, V., Schumacher, L., Kyritsi, P., et al., TGn Channel Models, IEEE 802.11-03/940r4, May 10, 2004 • [3] Rappaport, T. S., “Wireless Communications: Principles and Practice,” Prentice Hall, 1996 Eldad Perahia, Intel Corporation

More Related