The present invention relates to a method for a digital receiver and a receiver exploiting second order statistics for adaptive co-channel interference rejection in wireless communication. It uses digitally I, in phase, and Q, quadrature, branches of a received transmitted signal as input to the receiver, a coarse synchronization and a coarse frequency offset compensation have being performed on the signal. It comprises a means for derotation, means for separation, means for filtering, means for estimating and means for detecting transmitted symbols in the received signal. The invention thereby improving co-channel rejection in wireless communication, thus making it possible to increase the number of communication channels for frequencies used.
1. A method comprising:
receiving branches of transmitted signal by a digital receiver exploiting second order statistics for adaptive co-channel interference rejection in wireless communication, having digitally I, in phase, and Q, quadrature, wherein a coarse synchronization and a coarse frequency offset compensation are configured to be performed on said signal,
derotating the signal, and outputting a complex valued time discrete base band representation of the received signal if a used modulation form is one dimensional, else if a used modulation form is multiple dimensional then construct, from possibly two vector valued signal sequences, a complex valued signal sequence and outputting said complex valued signal;
separating said output signal into its real and imaginary parts which vector is output containing the transmitted signal, co-channel interfering user signals, additive noise and other possible disturbance;
estimating using the outputs and performing one or more of the following quantities: fine synchronisation, fine frequency offset estimation or compensation, or data model estimation for outputting one or more of said quantities;
filtering, using the real value output and coefficients in the data model output and performing a whitening operation on the signal additionally taking into account second order properties of noise and co-channel interference; and
detecting transmitted symbols, and making use of the output and the data model, thereby improving co-channel rejection in wireless communication, thus making it possible to increase the number of channels for frequencies used.
2. A method according to claim 1 , wherein said method performs a whitening operation that takes into account the second order statistical properties of the noise and co-channel interference.
3. A method according to claim 1 , wherein detection is performed by taking a binary decision, symbol by symbol based on a scalar input signal.
4. A method according to claim 1 , wherein linear equalization is performed followed by symbol by symbol detection.
5. A method according to claim 1 , wherein sequence estimation is performed on the whitened sequence.
6. A method according to claim 5 , wherein the sequence estimation is performed by using a filtered channel and a residual covariance matrix.
7. A method according to claim 1 , wherein detection is performed by a reduced complexity sequence estimation performed on the whitened sequence.
8. A method according to claim 1 , wherein a model for a communication channel is a linear FIR channel.
9. A method according to claim 1 , wherein a model for interference and noise is a linear vector valued moving average process.
10. A method according to claim 1 , wherein a model for interference and noise is a vector-valued autoregressive process.
11. A method according to claim 1 , wherein data model parameters are estimated using training data.
12. A method according to claim 1 , wherein data model parameters are estimated using estimated symbols.
13. A method according to claim 1 , wherein the model order is prespecified.
14. A method according to claim 1 , wherein the model order is chosen according to a model order selection criteria.
15. A method according to claim 1 , wherein the model order is adapted during communication according to error rate on the channel.
16. A method according to claim 1 , wherein multi models are estimated and used in the filtering and detection means, the model resulting in the lowest error rate providing the symbol estimates.
17. A method according to claim 1 , wherein timing estimation is performed on training data.
18. A method according to claim 1 , wherein timing estimation is performed using estimated symbols.
19. A method according to claim 1 , wherein timing estimation is performed simultaneously as the data model parameters are estimated using training data.
20. A method according to claim 1 , wherein frequency offset estimation is performed on training data.
21. A method according to claim 1 , wherein frequency offset estimation is performed using estimated symbols.
22. A method according to claim 1 , wherein frequency offset estimation is performed simultaneously as the data model parameters are estimated using training data.
23. A receiver,
wherein the receiver is configured to exploite second order statistics for adaptive co-channel interference rejection in wireless communication, having digitally I, in phase, and Q, quadrature, branches of a received transmitted signal as input to the receiver, a coarse synchronisation and a coarse frequency offset compensation have configured to be performed on said signal, the receiver comprising:
derotation block for derotating the signal, and outputting a complex valued time discrete base band representation of the received signal if a used modulation form is one dimensional, else if a used modulation form is multiple dimensional then construct, from possibly two vector valued signal sequences, a complex valued signal sequence and outputting said complex valued signal;
separation block for separating the derotated output signal into its real and imaginary parts which vector is output from said separation block containing the transmitted signal, cochannel interfering user signals, additive noise and other possible disturbance;
estimator block using the outputs from said separation block, filter block, and from detector block, and performing on one or more of the following quantities: fine synchronisation, fine frequency offset estimation or compensation, or data model estimation for outputting one or more of said quantities to said derotation block, filter block, detector block;
the filter block using the real value output from said separation block and coefficients in the data model output from the estimator block and performing a whitening operation on the signal additionally taking into account a second order properties of noise and co-channel interference, the filtered signal being output to the estimator block and detector block; and
detector block for transmitted symbols in the signal, making use of the output from said filter block and the data model from the estimator block, thereby improving cochannel rejection in wireless communication, thus making it possible to increase the number of communication channels for frequencies used.
24. A receiver according to claim 23 , wherein said filter block perform a whitening operation that takes into account the second order statistical properties of the noise and co-channel interference.
25. A receiver according to claim 23 , wherein detection is performed by taking a binary decision, symbol by symbol based on a scalar input signal.
26. A receiver according to claim 23 , wherein linear equalization is performed followed by symbol by symbol detection.
27. A receiver according to claim 23 , wherein a sequence estimation is performed on the whitened sequence.
28. A receiver according to claim 27 , wherein the sequence estimation is performed by using a filtered channel and a residual covariance matrix.
29. A receiver according to claim 23 , wherein detection is performed by a reduced complexity sequence estimation performed on the whitened sequence.
30. A receiver according to claim 23 , wherein a model for a communication channel is a linear FIR channel.
31. A receiver according to claim 23 , wherein a model for interference and noise is a linear vector valued moving average process.
32. A receiver according to claim 23 , wherein a model for interference and noise is a vector-valued autoregressive process.
33. A receiver according to claim 23 , wherein data model parameters are estimated using training data.
34. A receiver according to claim 23 , wherein data model parameters are estimated using estimated symbols.
35. A receiver according to claim 23 , wherein the model order is prespecified.
36. A receiver according to claim 23 , wherein the model order is chosen according to a model order selection criteria.
37. A receiver according to claim 23 , wherein the model order is adapted during communication according to error rate on the channel.
38. A receiver according to claim 23 , wherein multi models are estimated and used in the filtering and detection means, the model resulting in the lowest error rate providing the symbol estimates.
39. A receiver according to claim 23 , wherein timing estimation is performed on training data.
40. A receiver according to claim 23 , wherein timing estimation is performed using estimated symbols.
41. A receiver according to claim 23 , wherein timing estimation is performed simultaneously as the data model parameters are estimated using training data.
42. A receiver according to claim 23 , wherein frequency offset estimation is performed on training data.
43. A receiver according to claim 23 , wherein frequency offset estimation is performed using estimated symbols.
44. A receiver according to claim 23 , wherein frequency offset estimation is performed simultaneously as the data model parameters art estimated using training data.