Subspace-based blind channel identification of SISO-FIR systems with improper random inputs
Signal Processing - Signal processing in communications
Blind paraunitary equalization
Signal Processing
Blind paraunitary equalization
Signal Processing
Performance limits of alphabet diversities for FIR SISO channel identification
IEEE Transactions on Signal Processing
| Hi-index | 35.69 |
A novel analytical blind single-input single-output (SISO) identification algorithm is presented, based on the noncircular second-order statistics of the output. It is shown that statistics of order higher than two are not mandatory to restore identifiability. Our approach is valid, for instance, when the channel is excited by phase shift keying (PSK) inputs. It is shown that the channel taps need to satisfy a polynomial system of degree 2 and that identification amounts to solving the system. We describe the algorithm that is able to solve this particular system entirely analytically, thus avoiding local minima. Computer results eventually show the robustness with respect to noise and to channel length overdetermination. Identifiability issues are also addressed.