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Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening Alvin Leung Yang You EE381K-12 March 04, 2008.

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Presentation on theme: "Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening Alvin Leung Yang You EE381K-12 March 04, 2008."— Presentation transcript:

1 Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening Alvin Leung Yang You EE381K-12 March 04, 2008

2 General Background/Motivation Multiple transmit/receive antennas for communication systems  Higher capacity than single transmit/receive systems  Leveraging multiple antennas Space-time block coding  Frequency selective channels Multicarrier modulation Divide channel into many flat fading bins  Channel estimation

3 System Model 2 TX Antennas x 1 RX Antenna (MISO) R = (h0 * s0) + (h1 * s1) + n Multipath channel model with additive Gaussian noise

4 Orthogonal Frequency Division Multiplexing subchannel magnitude carrier channel frequency http://www.ece.utexas.edu/~rheath/research

5 Training vs Blind vs Semi-Blind Channel Estimation Must estimate the channel to recover the signal Training-based  Use pilot symbols/tones  Consume bandwidth, capacity loss Blind  Use inherent structure of signal  Constrained to special cases, less accurate Semi-blind  Use minimal amount of known symbols w/ inherent structure of signal

6 Low Complexity MIMO Blind, Adaptive Channel Shortening [R. K. Martin et al. 2005] OFDM requires cyclic prefix (CP) be longer than channel Can shorten the channel to ensure this condition Blind technique induces channel shortening by restoring the redundancy of CP Low complexity; shorten multiple channels simultaneously Unclear how to leverage multiple transmit antennas or estimate channel N samplesv samples CP: Cyclic Prefix CP s y m b o l i s y m b o l ( i+1) copy http://www.ece.utexas.edu/~rheath/research

7 Alamouti Coding [S. Alamouti 1998] Rate-1 code using simple coding matrix at transmitter and combiner at receiver Can be generalized to 2 transmitters and M receivers Adds structure and redundancy to received signal for channel estimation and robustness

8 Semi-Blind Channel Estimation [S. Zhou et al. 2002] Scalar ambiguity exists if channel estimated blindly from Alamouti structure Only two known symbols necessary to resolve true channel Less wasted symbols than training based

9 Proposed Project We leverage Martin’s blind channel shortening algorithm to reduce the channel length, allowing a shorter cyclic prefix Channel is estimated with semi-blind technique based on Alamouti with two known symbols Channel estimate used for frequency domain equalization, recover transmitted signal


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