Soft constraint satisfaction (SCS) blind channel equalization algorithms
Oguz Tanrikulu, B. Baykal, Anthony George Constantinides, Jonathon A. Chambers · International Journal of Adaptive Control and Signal Processing · 1998
The constant modulus adaptive blind equalization algorithms presented in this paper are shown to correspond to an error performance surface which is much improved upon that of existing algorithms such as the well-known constant modulus (or Godard) algorithm. Many undesirable local solutions (ULSs) are avoided by careful derivation. We use a deterministic optimization criterion with a soft constraint to obtain an update equation which contains a normalized gradient vector and a particular continuous non-linearity. This approach is extended to multiple constraints to yield faster converging algorithms. An autoregressive AR channel model is studied to demonstrate analytically the absence of a class of ULSs. Finally, the findings are verified experimentally for various (AR) and moving-average (MA) channels. © 1998 John Wiley & Sons, Ltd.