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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 1 Low Overhead Pilot Structures Igor Tolochko and Mike Faulkner, ATcrc, Victoria University

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 2 MIMO System Channel Estimatiom –Mt * Mr paths –S is the total transmit power: Tx power / antenna = S/Mt (equal power) –SNR is the receiver signal to noise ratio –MSE is the channel estimate error Goal Estimate all Paths With the Minimum Overhead PA 1 PA 2 PA 3 PA Mt RX 1 RX 2 RX 3 RX Mr AMt A2 A3 A1

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 3 Channel Estimation Requirements Mt x Mr MIMO requires Mt orthogonal pilots –Time orthogonality –Frequency –Code Low Pilot Overhead Low Complexity Low implementation (SNR) loss (low mean squared error) –MSE(channel) << SNR (data) –MSE < SNR -3dB (for 11a) SNR loss <= 1.76dB Channel MSE SNR Loss Comment SNR - inf(dB) 0dBPerfect Channel Estimation SNR – 6dB 0.97dB SNR – 3dB 1.76dBLong Symbol + Least Squares SNR3dBUse Differential Detection?? SISO Coherent Detection

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 4 Time Orthogonal One Transmitter at a time –Each PA must provide the full power, S, during pilot transmission –Overhead 2Mt symbols per packet –Simple LS processing for MSE=0.5N (-3dB) –11a Compatibility by inserting the ‘signal’ symbol after the first long, P(1), and transmitting it on A1 as per Jan Boer et al [2] 8 s Sub-carriers A1 A2 AMt 8 s Time Interleaved Long (TIL) Pilots P(1) P(2) P(Mt) Time Frequency cp

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 5 Code Orthogonality All Tx at same time –P(k)= k’th pilot –PA power of S/Mt during pilot transmission –Overhead 2Mt symbols per packet –Simple LS processing for MSE=0.5N (-3dB) –11a compatibility by inserting the ‘signal’ symbol after the first long symbol P(1) and transmitting it using co-transmission on A1 and A2 8 s Sub-carriers A1+A2 A1-A2 Example Mt=2 Walsh like Can be expanded to Mt antennas (low detection complexity if Mt=2,4,8) Code Interleaved Long (CIL) Pilots P(1) P(2) 8 s cp

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 6 Frequency Orthogonality All Tx active, but not in the same frequency bin –PA power of S/Mt during pilot transmission –Overhead of 2 symbols (1 long) per packet … but MSE=0.5N + interpolation error …. too high?? –Might need Longer Pilots, More Pilots or Frequency Domain Processing to reduce MSE. Simulations of Interpolation performance needed 8 s Sub-carriers A1 A2 Receiver uses Interpolation for non pilot positions AMt A1 Frequency Interleaved Long (FIL) Pilots cp

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 7 8 s 4 s 8 s Sub-carriers (a)(c) A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 A1 (b) A1 A2 A1 A2 A1 A2 A1 A2 A1 A2 The pilot schemes in a 2x1 OFDM system: (a) Frequency Interleaved Long (FIL). (b) Frequency and Time Interleaved Normal (FTIN) and (c) Double Frequency Interleaved Long (DFIL). Low Overhead Pilot Symbol Schemes to be Studied Note. FTIN (b) and DFIL (c) are not compatible to 11a as a first pilot signal FIL FTIN DFIL cp 4 s cp

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 8 Frequency Domain Channel Estimation [5] LS estimation is a noisy observation, given by: Linear minimum mean-squared error (LMMSE) estimator is a conditional mean estimator: LMMSE exploits frequency domain correlation of h(t) and performs interpolation and filtering of the noisy LS estimation Close to optimal (Weiner Filter) Assumptions Perfect synchronisation and SNR knowledge Exponential decaying channel impulse response LMMSE Processing + H

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 9 2x1 diversity, IEEE n NLOS channels [1] Channel B,C,D, rms <= 50 ns Channel Estimate MSE vs SNR Channel E, rms = 100 ns data SNR(dB) Mean Square Error(dB) LS in TIL or CIL LMMSE in FIL LMMSE in FTIN LMMSE in DFIL FTIN is the best of the single long pilot structures LMMSE smoothing/interpolation is best at low SNR

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 10 Channel F, rms = 150 ns 2x1 diversity, IEEE n NLOS channels Channel Estimate MSE vs SNR Typical Floor in Data that might be expected by ISI due to channel and impulse response Tx/Rx filters. Data is corrupted more than the Channel Estimate Channel F + filter ISI

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 11 Channel E, rms = 100 ns. Reduced complexity (RC) LMMSE Channel F, rms = 150 ns. Reduced complexity (RC) LMMSE 2x1 diversity, IEEE n NLOS channels

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 12 Channel E, rms = 100 ns. Reduced complexity (RC) LMMSE Channel F, rms = 150 ns. Reduced complexity (RC) LMMSE 3x1 diversity, IEEE n NLOS channels Performance Criteria: SNRmax (when MSE=SNR-3dB) :- the higher the better SNRmax

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 13 Table I. Single Pilot Symbol Overhead = 8us (1 long or 2 normal) Scheme SNRmax (dB) when MSE=SNR-3dB 21214141 FIL FTIN DFIL FIL/RC > 37 > 37 > – – 313 – – EE E F FF Table II. Double Pilot Symbol Overhead = 16us (2 long) Scheme SNRmax (dB) when MSE=SNR-3dB 21214141 FTIL > 37 > 131 – – EE E F FF SNR range for LMMSE to outperform Time Interleaved LS Figures over 20dB are probably acceptable Add between 4 to 10 dB to get the condition MSE =SNR

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 14 Conclusion Frequency domain processing can reduce pilot overhead to Mt normal symbols (Mt * 4 s). Example 8 s for 2x1 Interpolation error increases with delay spread Low overhead pilots perform best at Low SNR. Limiting performance in high delay spread channels with high SNR (are these common?) FTIN has reduced interpolation error and outperforms FIL, except in ISI channels. It is the best of the low overhead schemes. Frequency interleaving (FIL) is preferred because of compatibility. ISI corrupts data more than the channel MSE COMPLEXITY is HIGH –Complexity/bin Cp = No of MIMO Channels * no of operations per bin –For full LMMSE, Cp = (Mr*Mt)*(N/Mt) operations/bin Cp = Mr*N ; N=no. of active bins (=52) –RC systems have between x0.3 to x0.8 reduction.

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doc.: IEEE n Submission Jan 2004 M.Faulkner, ATcrcSlide 15 Reference 1. V. Erceg et al, TGn Channel Models, doc.: /940r, Nov Jan Boer et al. ‘ Backwards compatibility’,doc.: IEEE /714r0, Sept IEEE Std a/D7.0, “Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-Speed Physical Layer in the 5 GHz Band,” New York, USA, J. Medbo and P. Schramm, “Channel Models for HIPERLAN/2 in Different Indoor Scenarios”, ETSI BRAN doc. No. 3ER1085B, O. Edfors, M. Sandell, J.J. van de Beek, S.K. Wilson and P.O. Borjeson, “OFDM Channel Estimation by Singular Value Decomposition,” IEEE Trans. Commun., 46,(7), pp. 931–939, I. Tolochko, and M. Faulkner, “Real Time LMMSE Channel Estimation for Wireless OFDM Systems with Transmitter Diversity,” In Proc. IEEE 56th Vehicular Technology Conference VTC2002-Fall, Vancouver, Canada, Sept. 2002, pp. 1555–1559.

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