Method and Apparatus for Algorithm on Flexible Square-Qam Coherent Detection

1. A decision-directed modified least mean square (DD-MLMS) method comprising: receiving an mQAM modulated data signal comprising a plurality of symbols; and equalizing the data signal using an adaptive finite impulse response (FIR) filter having multiple tap coefficients, wherein the tap coefficients are adaptively updated using a DD-MLMS algorithm and a cost function according to earlier symbol character information, wherein the filter tap coefficients updating equation is w(n)=w(n−1)+μe(n)x(n)*, where w(n) is the adaptive FIR filter, μ is a convergence parameter, e(n) is a complex error vector, x(n) is the received data signal, and [·]* stands for conjugation operation; wherein each of the symbols is determined as a decision symbol that is a shortest distance away from a respective mQAM constellation point, and the DD-MLMS algorithm tries to force the equalized signal to reside on the decision point, whereby carrier phase offset is blindly compensated.

2. The method of claim 1 , wherein the DD-MLMS algorithm minimizes mean square error.

3. The method of claim 1 , wherein the cost function is multi-modulus on both a real signal part and an imaginary signal part.

4. The method of claim 1 , further comprising: reserving amplitude error information and phase error information; and using the amplitude error information and the phase error information in calculating separately, and then combining, errors of a real signal part and an imaginary signal part.

5. The method of claim 4 , further comprising estimating a real part of an output signal and an imaginary part of the output signal.

6. A decision-directed modified least square mean (DD-MLMS) system comprising: a filter adapted to receive an mQAM modulated data signal comprising a plurality of symbols, and equalize the data signal using an adaptive finite impulse response (FIR) filter having multiple tap coefficients, wherein the tap coefficients are adaptively updated using a DD-MLMS algorithm and a cost function according to earlier symbol character information, wherein the filter tap coefficients updating equation is w(n)=w(n−1)+μe(n)x(n)*, where w(n) is the adaptive FIR filter, μ is a convergence parameter, e(n) is a complex error vector, x(n) is the received data signal, and [·]* stands for conjugation operation; wherein each of the symbols is determined as a decision symbol that is a shortest distance away from a respective mQAM constellation point, and the DD-MLMS algorithm tries to force the equalized signal to reside on the decision point, whereby carrier phase offset is blindly compensated.

7. The system of claim 6 , wherein the DD-MLMS algorithm minimizes mean square error.

8. The system of claim 6 , wherein the cost function is multi-modulus on both a real signal part and an imaginary signal part.

9. The system of claim 6 , wherein the filter is further adapted to: reserve amplitude error information and phase error information; and use the amplitude error information and the phase error information to calculate separately, and then combine, errors of a real signal part and an imaginary signal part.

10. The system of claim 9 , wherein the filter is further adapted to estimate a real part of an output signal and an imaginary part of the output signal.

11. The system of claim 6 , wherein the system is adapted to receive a non-mQAM modulated data signal, the system further comprising: a plurality of cascaded adaptive blind equalizers comprising multiple finite impulse response (FIR) filters for polarization separation and multiple finite impulse response filters for carrier phase recovery, wherein, in operation, the finite impulse response filters are adaptively updated by using a pre-convergence method followed by DD-MLMS for precise feedback control.

12. The system of claim 11 , wherein DD-MLMS minimizes mean square error.

13. The system of claim 11 , wherein signal processing within the plurality of cascaded adaptive blind equalizers is modulation format independent for a square-QAM signal with the exception of a required symbol final decision.