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
Semi-Blind Equalization for OFDM using Space-Time Block Coding and Channel Shortening
Alvin LeungYang You
EE381K-12May 1, 2008
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)
Channel Shortening
Needed in order to preserve cyclic convolution in OFDM Designed as FIR filter – compresses channel energy
Alamouti Coding
Orthogonalizes transmitted symbol
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).
System Model – TX
Θ1 and Θ2 - Linear precoders [JxK] M(.) - Alamouti space-time encoding OFDM
IFFT +CP
IFFT +CP
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
Channel Shortening for Equal Channels
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
Channel Estimate Comparison
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