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Effective (20us) Preambles for MIMO-OFDM

Effective (20us) Preambles for MIMO-OFDM. Seigo Nakao SANYO Electric Co., Ltd. Japan snakao@gf.hm.rd.sanyo.co.jp Yoshiharu Doi SANYO Electric Co., Ltd. Japan doi@gf.hm.rd.sanyo.co.jp. Yasutaka Ogawa Hokkaido University Japan ogawa@ice.eng.hokudai.ac.jp. Presentation Contents.

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Effective (20us) Preambles for MIMO-OFDM

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  1. Effective (20us) Preambles for MIMO-OFDM Seigo Nakao SANYO Electric Co., Ltd. Japan snakao@gf.hm.rd.sanyo.co.jp Yoshiharu Doi SANYO Electric Co., Ltd. Japan doi@gf.hm.rd.sanyo.co.jp Yasutaka Ogawa Hokkaido University Japan ogawa@ice.eng.hokudai.ac.jp

  2. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  3. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  4. Training sequences: performance motivations • PHY overhead restricts high throughput. • Overlapped LTS can reduce the PHY overhead. • More efficient that staggered LTS usage • The proposed STS enable overlapped LTS.

  5. Training sequence usage • STS is used for • AGC • Timing detection • Rough frequency offset estimation • Detecting the number of antennas • Useful for overlapping LTS • LTS is used for • Channel estimation • Fine frequency offset estimation

  6. Example of overlapped STS and LTS TX1 STS1 LTS1 Sig DATA1 TX2 STS2 LTS2 Sig DATA2 Example of overlapped STS, staggered LTS TX1 STS1 LTS Sig Sig2 DATA1 TX2 STS2 LTS Sig DATA2 Overlapped and Staggered LTS Time to detect number of TX antennas

  7. TX1 STS1 LTS1 Sig DATA1 TX2 STS2 LTS2 Sig DATA2 STS Implication of overlapped LTS • “Overlapped STS and LTS”, can be easily deployed when the number of antennas can be known during the STS time. • The proposed STS provide this ability. • Overlapped approach implies some LTS considerations for efficient MIMO channel estimation.

  8. Desired STS characteristics: • Each TX antenna should have a unique STS. • The cross-correlation of 1 STS cycle for any pair of STSs should be 0 for • Easy synchronization, • Good frequency offset estimation, and • Optimum AGC implementation. (As concluded in IEEE 802.11-04-0002r2) • STSs may be used to help distinguish the number of TX antennas.

  9. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  10. Proposed STSs (ex: 4 Tx max) Used for sync, to find # Tx and fine AGC (using 6 of 12 carriers of the legacy STS) 1TX Legacy STS 2TX STS1 STSa 3TX STS1 STS2 STSb 4TX STS1 STS2 STS3 STSc Used for Fine AGC (using the other 6 carriers of legacy STS) Low cross-correlation Zero cross-correlation

  11. Examples of Proposed STSs(3 antenna max case) Carrier no. Legacy STSa STSb STS1 STS2 -24 1.472+1.472j 0 0 2.082+2.082j -2.082-2.082j -20 -1.472-1.472j 0 0 -2.082-2.082j -2.082-2.082j -16 1.472+1.472j 0 0 2.082+2.082j 2.082+2.082j -12 -1.472-1.472j 2.082+2.082j 2.082+2.082j 0 0 -8 -1.472-1.472j -2.082-2.082j 2.082+2.082j 0 0 -4 1.472+1.472j 0 0 2.082+2.082j 2.082+2.082j 4 -1.472-1.472j 2.082+2.082j -2.082-2.082j 0 0 8 -1.472-1.472j 0 0 -2.082-2.082j 2.082+2.082j 12 1.472+1.472j 2.082+2.082j -2.082-2.082j 0 0 16 1.472+1.472j 2.082+2.082j 2.082+2.082j 0 0 20 1.472+1.472j 2.082+2.082j 2.082+2.082j 0 0 24 1.472+1.472j 0 0 2.082+2.082j 2.082+2.082j sqrt(13/6)=1.472, sqrt(13/3)=2.082

  12. How to detect the number of antennas (3 antenna max case) Correlation peak Received signal Correlator for legacy STS (6carrier) Max Select Number of antennas Correlator for STSa Correlator for STSb

  13. Correlator for Legacy STS detection Carrier no. Legacy STS sequence Correlator for legacy STS (6carrier) -24 1.472+1.472j 0 This correlator can detect the legacy STS without any effects from STS1 and STS2. -20 -1.472-1.472j 0 -16 1.472+1.472j 0 -12 -1.472-1.472j -2.082-2.082j -8 -1.472-1.472j -2.082-2.082j -4 1.472+1.472j 0 4 -1.472-1.472j -2.082-2.082j 8 -1.472-1.472j 0 12 1.472+1.472j 2.082+2.082j 16 1.472+1.472j 2.082+2.082j 20 1.472+1.472j 2.082+2.082j 24 1.472+1.472j 0

  14. 50% 45% 40% 35% 30% 3 antenna case Channel model B 25% Detection Error 20% 15% 10% 5% 0 -10 -5 0 5 10 15 20 SNR [dB] Detecting Number of Antennas

  15. Legacy STS compatibility • The Proposed STSs take an approach analogous to that successfully used by .11G • The 11g document defines the same preambles as 11b, but venders don’t actually provide the same preambles – instead only use pure OFDM (like 11a) is used for throughput. • Similarly, The proposed STS can't be directly received by legacy STA. • Therefore the proposed STS have the same degree of backwards compatibility to 11a (as 11g does to 11b).

  16. Proposed STS advantages • The proposed STSs support overlapped LTS usage and can be used to detect any number of Tx antennas. • The required STS correlators can be cost effectively implemented • by defining STSa and STSb such that the correlator implementation cost can be much less than the cost of n separate correlators. • (e.g. STSa_I = STSb_Q, STSa_Q = STSbI)

  17. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  18. AGC performance • Generally, AGC calculates signal power over 16 FFT points (i.e. 1 STS). • The average power of the STS term should be the same as that of the average power of of the DATA term.

  19. Other candidates of new STSs • Frequency cyclic use of legacy STS • Which doesn’t have 16 FFT samples cycle (IEEE 802.11-04-0046r1) • Polarity changed STS of legacy STS (IEEE 802.11-04-0087r1)

  20. 4 3.5 3 2.5 Ave.Power of Data 2 1.5 1 0.5 0 0 1 2 3 4 Ave.power of 1 STS cycle Proposed STS AGC performance(channel model B)

  21. 4 4 3.5 3.5 3 3 2.5 2.5 Ave.Power of Data Ave.Power of Data 2 2 1.5 1.5 1 1 0.5 0.5 0 0 0 1 2 3 4 0 1 2 3 4 Ave.power of 1 STS cycle Ave.power of 1 STS cycle Other proposal’s AGC performance(channel model B) Polarity changed STS of legacy STS Frequency cyclic use of legacy STS

  22. Proposed STS AGC Advantages • Proposed STSs have good performance characteristics for AGC implementations. • Proposed STSs have an advantage over frequency cyclic use of legacy STS because the proposed STS is a 16 FFT points cycle. • No disadvantage results from using 6 carriers (vs. 12) for STS (for MIMO) • For 1 Tx, 12 carriers are better than 6 • For 2+ Tx, 6 carries are better than 12 because of cross correlation advantages.

  23. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  24. Reference • This portion of the paper is derived from the work of Yasutaka Ogawa, Hokkaido University Japan. • For reference, please see: Ogawa, et al. “A MIMO-OFDM System for High-Speed Transmission,” VTC2003-Fall, Oct. 2003.

  25. Overlapped LTS usage: • LTS should be used for fine frequency offset estimation. • LTS should have good performance for MIMO channel estimation.

  26. GI21 GI22 T1,1 T2,1 T1,2 T2,2 TX1 TX2 (32) (32) (64) (64) (64) (64) Proposal for new LTS and Channel Estimation: • The Impulse response between each TX and RX antenna pair is estimated by the minimum mean square error scheme using 2 LTSs in the time domain (128 samples). • Channel at each subcarrier is obtained by FFT of the zero padded impulse response.

  27. Channel and Frequency Offset (Df ) Estimation: • Coarse Df estimation is carried out using 3 cycles of the STS. • Phase rotation is compensated by the coarse Df estimator before the next steps. • Channel estimation is done using the 2 LTS portions (Ti,1 and Ti,2) assuming that Df = 0. • Replica of the time-domain LTS sequences with Df = 0 is calculated by the channel estimator. • Continued…

  28. Channel and Frequency Offset (Df ) Estimation: • Fine Df is estimated from the phase rotation in the LTS period using the replica. • Phase rotation is compensated again using the fine Df estimator. • Channel estimation is done again using the 2 LTS portions.

  29. 0 1 0 - 1 1 0 R - 2 E 1 0 B e g a r e v - 3 1 0 A - 4 1 0 D f E s t i m a t e d D W i t h p e r f e c t f k n o w l e d g e - 5 1 0 0 1 0 2 0 3 0 4 0 A v e r a g e E b / N 0 [ d B ] Average BER Performance of Proposed method: • TX 4, RX 4 • Df = 50kHz • QPSK • 9 data symbols / subcarrier • 16 multipath signals(Average power of the multipath signals decreases successively by 1 dB.) • No channel coding • Spatial filter (MMSE)

  30. Presentation Contents • Training sequences - performance motivations (STS and LTS) • Detecting the number of Tx Antennas via STS • AGC performance of proposed STS • Proposed LTS and channel estimation techniques • Conclusions

  31. Proposed STS Advantages • Enables easier use of overlapped LTS for PHY overhead reduction. • Detects the # Tx signals during STS time • Easy synchronization. • Good course frequency offset estimation. • Provides optimum AGC implementation. • Has good cross correlation characteristics w.r.t. to legacy STS. • Have cost effective correlator implantations. • Are appropriate for use with MIMO-OFDM

  32. Proposed LTS Advantages • Are appropriate for “overlapped LTS” usage. • Offer fine frequency offset estimation.

  33. References • Ogawa, et al. “A MIMO-OFDM System for High-Speed Transmission,” VTC2003-Fall, Oct. 2003. • IEEE 802.11-04-0002r2 • IEEE 802.11-04-0046r1 • IEEE 802.11-04-0087r1

  34. Questions (for Mr. Nakao)?

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