9ce23c4a10
new general processing structure just before splitting off the projects folder from this repo
40 lines
1.8 KiB
Matlab
40 lines
1.8 KiB
Matlab
function [eq_, pf_, mlse_, mlse_db_, eq_post] = configureEqualizers(M, len_tr, vnle_order, dfe_order, mu_dc, mu_ffe, mu_dfe, pf_ncoeffs)
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% CONFIGUREEQUALIZERS Creates and configures equalizer objects
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%
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% Inputs:
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% M - PAM level
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% len_tr - Training length
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% vnle_order - Array with orders for VNLE [order1, order2, order3]
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% dfe_order - Array with orders for DFE
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% mu_dc - DC adaptation rate
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% mu_ffe - Array with adaptation rates for FFE [mu1, mu2, mu3]
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% mu_dfe - Adaptation rate for DFE
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% pf_ncoeffs - Number of coefficients for postfilter
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%
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% Outputs:
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% eq_ - Configured EQ object
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% pf_ - Configured Postfilter object
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% mlse_ - Configured MLSE_viterbi object
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% mlse_db_ - Configured MLSE_viterbi object for duobinary
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% eq_post - Configured FFE object for post-processing
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% Configure main equalizer
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eq_ = EQ("Ne", vnle_order, "Nb", dfe_order, ...
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"training_length", len_tr, "training_loops", 5, "dd_loops", 5, ...
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"K", 2, "DCmu", mu_dc, "DDmu", [mu_ffe mu_dfe], ...
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"DFEmu", 0.005, "FFEmu", 0, "plotfinal", 0, "ideal_dfe", 1);
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% Configure postfilter
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pf_ = Postfilter("ncoeff", pf_ncoeffs, "useBurg", 1);
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% Configure MLSE objects
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mlse_ = MLSE_viterbi("duobinary_output", 0, 'M', M, ...
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'trellis_states', PAMmapper(M,0).levels);
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mlse_db_ = MLSE_viterbi("DIR", [1,1], "duobinary_output", 0, ...
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"M", M, "trellis_states", PAMmapper(M,0).levels);
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% Configure post-FFE
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eq_post = FFE("epochs_tr", 5, "epochs_dd", 5, "len_tr", 4096*2, ...
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"mu_dd", 1e-4, "mu_tr", 0, "order", 2001, ...
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"sps", 1, "decide", 0);
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end |