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VHT-LTF Design for IEEE802.11ac. Date: 20 10 -0 7 - 12. Authors:. Abstract. The long training field (LTF) provides a mean s for receivers to estimate MIMO-OFDM channels in 802.11ac systems.
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VHT-LTF Design for IEEE802.11ac Date: 2010-07-12 Authors:
Abstract • The long training field (LTF) provides a means for receivers to estimate MIMO-OFDM channels in 802.11ac systems. • An excellent LTF should not only minimize channel estimation errors, but also reduce overhead as much as possible. • An efficient VHT-LTF is proposed to improve the accuracy of channel estimation with less overhead.
Background • In 802.11n, the number of HT-LTFs is greater than or equal to the number of space-time streams (NSTS). • If 802.11ac uses the same mechanism, in order to support 8 space-time streams, the number of VHT-LTFs should be up to 8. It is obviously a resource waste, especially when the data field is short, e.g., NDP and sounding PPDU. • Can we design a VHT-LTF toachieve excellent performance with lessoverhead? • A class of advanced training sequences, CAZAC codes, can meet this requirement.
Introduction of CAZAC codes • What is CAZAC codes? • CAZAC (Constant Amplitude Zero Auto-Correlation ) codes are a class of complex-valued pseudo-random noise sequences with cyclic autocorrelation equal to zero. • Zadoff-Chu sequence is a well-known CAZAC code, which has been widely used in wireless systems. Zadoff-Chu sequence expression
Characteristics of CAZAC codes • Characteristics • Zero Auto-Correlation: It means that a CAZAC code is always orthogonal with its cyclic shifted versions. • Constant Amplitude • Major advantages • Reduce inter-symbol interference (ISI) • Avoid interferences between multiple antennas • Lower PAPR • As a result, CAZAC codes are regarded as optimum training sequences for channel estimation in MIMO-OFDM systems.
Simulation Parameters • The Frequency Domain-Least Square-Joint (FD-LS-JCE) channel estimation algorithm has a low implementation complexity [4], comparable with the FD-LS algorithm.
Only one symbol n = NVHT-LTF symbols CAZAC HT-LTF1 HT-LTF2 HT-LTFn NVHT-LTF symbols CAZAC CAZAC CAZAC Explanation of VHT-LTF Schemes • The CAZAC code for space-time stream k is generated by cyclically shifting the basic CAZAC code (for Stream 0) with k/NSTS code length. • The CAZAC code in Scheme 3 are repeated NVHT-LTF times.
Preformance Comparison (1x1, 2x2) • MSE denotes the mean square error of channel estimation.
Performance Analysis • The performance of CAZAC codes is much better than that of HT-LTFs when they use the same number of symbols. • The SNR gain is 8 ~12 dB at MSE=0.01 when HT-LTFs use the FD-LS algorithm. • The SNR gain is 4 ~ 6 dB at MSE=0.01 when HT-LTFs use the MMSE algorithm. • The CAZAC codes using one symbol can also achieve better performance than HT-LTFs using the FD-LS algorithm. • The CAZAC code using one symbol can still outperform HT-LTF using the MMSE algorithm when • the number of space-time streams is not too large (<= 4), or • SNR is high
Conclusion • With speical code characteristics, CAZAC codes are able to achieve better performance with less training symbols, and thus can be used to • enhance the channel estimation accuracy, and/or • improve the spectral efficiency, especially when the data field is short, e.g., NDP and sounding PPDU. • Due to significant performance advantages, we recommend CAZAC codes to be a candidate of VHT-LTFs, in which less backward compatibility with 11a/n needs to be concerned.
StrawPoll #1 • Do you support to reduce the number of VHT-LTFsto increase the spectral efficiency of 802.11ac and to edit the spec framework document, 11-09-0992, accordingly? • Yes: • No: • Abs:
StrawPoll #2 • Do you support to adopt some advanced training sequences (e.g., CAZAC codes) as VHT-LTFs and to edit the spec framework document, 11-09-0992, accordingly? • Yes: • No: • Abs:
References • [1] Specification Framework for Tgac, IEEE 802.11-09/0992r11, May 2010 • [2] IEEE 802.11n standard • [3] Hongyuan Zhang, et al., 802.11acPreamble, IEEE 802.11-10/0070r5, March 2010 • [4]Time and Frequency Domain Joint Channel Estimation in Multi-carrier Multi-branch Systems, Aachen, Germany: Shaker Verlag, 2005