An Iterative Frequency-Domain Minimum Mean Square Error Equalization Method Based on Weighted Fractional Fourier Transform for Double Dispersion Channels
A minimum mean square error, dual dispersion channel technology, applied to equalizers and other directions, can solve problems such as signal energy dispersion
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specific Embodiment approach 1
[0056] Specific implementation mode 1: The iterative frequency-domain minimum mean square error equalization method under the weighted fractional Fourier transform-based double dispersion channel of this implementation mode is implemented in the following steps:
[0057] 1. The sending end of the mixed carrier modulation system completes the mixed carrier modulation to obtain the time domain sequence x;
[0058] 2. Add a cyclic prefix to the time-domain sequence x obtained in step 1 and obtain a time-domain sampling sequence after parallel-to-serial conversion
[0059] 3. The time-domain sampling sequence in step 2 Serial transmission, after going through double dispersive channels, arrives at the receiving end of the mixed carrier modulation system;
[0060] 4. The receiving end of the hybrid carrier modulation system ignores the CP part, and each received time-domain sampling sequence y can be expressed as the convolution form of the sequence at the sending end of the hy...
specific Embodiment approach 2
[0119] Specific embodiment 2: The difference between this embodiment and specific embodiment 1 is that in step 1, the sending end of the hybrid carrier modulation system completes the hybrid carrier modulation to obtain the time domain sequence x, which is specifically:
[0120] At the sending end, the data bit sequence b with a length of NQ is mapped to an N-long QAM symbol sequence s after constellation modulation, and each Q bit {b n,0 ,...,b n,Q-1} is mapped to a symbol s n , perform -α-order WFRFT on the obtained QAM symbol sequence, and complete the mixed carrier modulation to obtain the time domain sequence:
[0121] x=F -α s=(w 0 I+w 1 F+w 2 A+w 3 f -1 )s
[0122] where F -α Represents -α-order normalized WFRFT matrix; I represents N×N identity matrix; F represents normalized discrete Fourier transform (discreteFouriertransform, DFT) matrix; A represents an N×N permutation matrix, whose internal elements satisfy when when [A] n,m :=δ( N ) In addition, for ...
specific Embodiment approach 3
[0125] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is that in step six, the receiving end of the hybrid carrier modulation system performs a sampling point on the frequency corresponding to a certain subcarrier in the frequency domain received The linear MMSE estimation is specifically:
[0126] u ^ k = u ‾ k + g k H ( y k - H k u ‾ ) ,
[0127] where y k =[y k-D ,...,y k+D ] t , H k contains H df The k-D to k+D lines of the equalizer coefficient vector can be expressed as:
[0128] g k ...
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