UNBIASED ADAPTIVE DECISION FEEDBACK EQUALIZATION

It is well-known that the decision rule in the mini-mum mean-squares-error decision feedback equalizer(MMSE-DFE) is biased, and therefore suboptimum with respect to error probability. We present a new family of algorithms that solve the bias problem in the adaptive DFE. A novel constraint, called the constant-norm con-straint, is introduced unifying the quadratic constraint and the monic one. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of unbiased adaptive DFE. The simula-tion results demonstrate that the proposed method in-deed produce unbiased solution in the presence of noise while keeping very simple both in computation and im-plementation.