A refined class of cost functions in blind equalization
V. Shtrom, H. Howard Fan · 2002
The use of gradient descent recursive algorithms in blind adaptive equalization requires a cost function with a unique minimum such that the FIR equalizer setup removes sufficient intersymbol interference (ISI). A cost function based on minimizing the difference between the second and the fourth norms of the joint channel-equalizer impulse response, each raised to the fourth power, i.e., /spl par//spl middot//spl par//sub 2//sup 4/-/spl par//spl middot//spl par//sub 4//sup 4/ is proposed. An implementable recursive on-line algorithm using the above cost function is also derived for QAM inputs. A sizable array of examples shows that the above class is unimodal in equalizer weights. Extensive simulations show that the performance of the newly proposed algorithms is comparable to the CMA algorithms' performance without the misconvergences.