Reduced complexity sliding window based equalizer

Abstract

A method and apparatus for use in data estimation in wireless communication are provided. A wireless communications signal is received and transformed to produce a received vector. The received vector is processed using a sliding window based approach that includes processing each of a plurality of windows. For each window, an approximate circulant channel response matrix is produced for use in estimating a data vector corresponding to the window.

1 . An apparatus for use in wireless communication comprising:
 a receiver configured to transform a received wireless communications signal to produce a received vector by sampling at a multiple of a data signal chip rate; and   a processor configured to process the received vector using a sliding window based approach, such that for each processing window in a plurality of processing windows an approximate circulant channel response matrix is produced and used to estimate a data vector corresponding to the window.   
   
   
       2 . (canceled) 
   
   
       3 . The apparatus of  claim 1 , further comprising:
 a root-raised cosine filtering unit configured to apply a root-raised cosine filter to the received vector.   
   
   
       4 . The apparatus of  claim 1 , wherein the processor is configured to ignore noise cross correlation. 
   
   
       5 . The apparatus of  claim 1 , wherein the processor is configured to use the received vector and the approximate circulant channel response matrix arranged in a natural order. 
   
   
       6 . The apparatus of  claim 1 , wherein the receiver is configured to transform a plurality of received wireless communications signals from a plurality of antennas to produce a received vector. 
   
   
       7 . The apparatus of  claim 1 , wherein the processor is configured to multiply a discrete Fourier transform of a pulse shaping filter by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation. 
   
   
       8 . The apparatus of  claim 1 , wherein the processor is configured to multiply a discrete Fourier transform of an ideal pulse shape by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation. 
   
   
       9 . The apparatus of  claim 1 , further comprising:
 a summer, configured to combine the data vector corresponding to each window to form a combined data vector.   
   
   
       10 . The apparatus of  claim 1  configured as a wireless transmit/receive unit (WTRU). 
   
   
       11 . The apparatus of  claim 1  configured as a base station. 
   
   
       12 . A method for use in wireless communications, the method comprising:
 transforming a received wireless communications signal to produce a received vector by sampling at a multiple of a data signal chip rate; and   processing the received vector using a sliding window based approach, such that for each processing window in a plurality of processing windows an approximate circulant channel response matrix is produced and used to estimate a data vector corresponding to the window.   
   
   
       13 . (canceled) 
   
   
       14 . The method of  claim 12 , further comprising:
 applying a root-raised cosine filter to the received vector.   
   
   
       15 . The method of  claim 12 , wherein the processing includes ignoring noise cross correlation. 
   
   
       16 . The method of  claim 12 , wherein the processing includes using the received vector and the approximate circulant channel response matrix arranged in a natural order. 
   
   
       17 . The method of  claim 12 , wherein the transforming includes producing a plurality of received vectors corresponding to a plurality of received wireless communications signals from a plurality of antennas. 
   
   
       18 . The method of  claim 12 , wherein the processing includes multiplying a discrete Fourier transform of the pulse shaping filter by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation. 
   
   
       19 . The method of  claim 12 , wherein the processing includes multiplying a discrete Fourier transform of an ideal pulse shape by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation. 
   
   
       20 . The method of  claim 12 , further comprising:
 combining the data vector corresponding to each window to form a combined data vector.