semi-blind equalization for ofdm using space-time block coding and channel shortening
DESCRIPTION
Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening. Alvin Leung Yang You EE381K-12 May 1, 2008. General Background/Motivation. Multiple antenna communication systems Higher capacity Leveraging multiple antennas Spatial Diversity Space-Time Coding - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/1.jpg)
Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening
Alvin LeungYang You
EE381K-12May 1, 2008
![Page 2: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/2.jpg)
General Background/Motivation Multiple antenna communication systems
Higher capacityLeveraging multiple antennas
Spatial Diversity Space-Time Coding
Frequency selective channels Modeled as FIR filter Orthogonal Frequency Division Multiplexing (OFDM)
![Page 3: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/3.jpg)
Channel Shortening
Needed in order to preserve cyclic convolution in OFDM Designed as FIR filter – compresses channel energy
Alamouti Coding
Orthogonalizes transmitted symbol
![Page 4: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/4.jpg)
Objective
Evaluate a combination of blind channel shortening and semi-blind channel estimation in a multi-antenna ST-OFDM system over a realistic channel model (3GPP TR 25.996 spatial channel model).
![Page 5: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/5.jpg)
System Model – TX
Θ1 and Θ2 - Linear precoders [JxK] M(.) - Alamouti space-time encoding OFDM
IFFT +CP
IFFT +CP
![Page 6: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/6.jpg)
System Model – Channel and RX
wChannel
ShortenerFFT-CP
D1 and D2 - effective frequency domain channelsw(n) is AWGNM(.) removes space-time codingΓ equalizes z(n) to obtain symbol estimates
![Page 7: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/7.jpg)
Channel Shortening for Equal Channels
![Page 8: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/8.jpg)
Bit Error Rate = 5.3191e-005 Bit Error Rate = 9.5745e-005
Bit Error Rate = 0.0089 Bit Error Rate = 4.5745e-004
Constellation Comparison – Two Channels
![Page 9: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/9.jpg)
Channel Estimate Comparison
![Page 10: Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening](https://reader035.vdocuments.us/reader035/viewer/2022071718/56812deb550346895d934872/html5/thumbnails/10.jpg)
Conclusions
Computation of SVD in estimation very complex – O(N3)
Iterative channel estimation assumes very slowly changing channel
Blind channel shortener based on ergodic statistics – requires large sample size
We are exploring training based approaches