362 lines
15 KiB
Matlab
362 lines
15 KiB
Matlab
classdef FFE_A2TrackedLevels < handle
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%FFE_A2TrackedLevels FFE with A2 tracked-level decision thresholds.
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%
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% This class is intentionally narrow: it contains the normal adaptive FFE
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% flow plus the A2 tracked-level decision logic. The output sample y stays
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% unchanged; only the decision constellation is moved by the tracked
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% level-wise offsets.
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properties
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sps
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order
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e
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e_tr
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error
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len_tr
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mu_tr
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epochs_tr
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adaption_technique
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dd_mode
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mu_dd
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epochs_dd
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dd_len_fraction
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% A2 tracked-level decision
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dc_level_avg_bufferlength_a2
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dc_level_update_blocklength_a2
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dc_smoothing_a2
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dc_level_weights_a2
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P
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constellation
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decide
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save_debug = 0
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debug_struct
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end
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methods
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function obj = FFE_A2TrackedLevels(options)
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arguments(Input)
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options.sps = 2
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options.order = 15
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options.len_tr = 4096
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options.mu_tr = 0
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options.epochs_tr = 5
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options.adaption_technique adaption_method = adaption_method.lms
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options.dd_mode = 1
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options.mu_dd = 1e-5
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options.epochs_dd = 5
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options.dd_len_fraction = 1
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options.dc_level_avg_bufferlength_a2 = 0
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options.dc_level_update_blocklength_a2 = 0
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options.dc_smoothing_a2 = 0
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options.dc_level_weights_a2 = 0
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options.decide = false
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options.save_debug = 0
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end
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fn = fieldnames(options);
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for n = 1:numel(fn)
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obj.(fn{n}) = options.(fn{n});
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end
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assert(obj.dc_level_avg_bufferlength_a2 >= 0);
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assert(obj.dc_level_update_blocklength_a2 >= 0);
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obj.e = zeros(obj.order,1);
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obj.error = 0;
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obj.dc_level_avg_bufferlength_a2 = floor(obj.dc_level_avg_bufferlength_a2);
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obj.dc_level_update_blocklength_a2 = floor(obj.dc_level_update_blocklength_a2);
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obj.dc_smoothing_a2 = min(max(obj.dc_smoothing_a2,0),1);
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end
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function [X,Noi] = process(obj,X,D)
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X = X.normalize("mode","rms");
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obj.constellation = unique(D.signal);
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delta = 0.05;
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obj.P = (1/delta) * eye(obj.order);
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training = true;
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showviz = false;
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obj.equalize(X.signal,D.signal,obj.mu_tr,obj.epochs_tr,obj.len_tr,training,showviz);
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obj.e_tr = obj.e;
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n = X.length;
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training = false;
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if obj.dd_mode
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[signal,decision] = obj.equalize(X.signal,D.signal,obj.mu_dd,obj.epochs_dd,n,training,showviz);
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else
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[signal,decision] = obj.equalize(X.signal,D.signal,0,1,n,training,showviz);
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end
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if obj.decide
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X.signal = decision;
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else
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X.signal = signal;
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end
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X.fs = D.fs;
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X = X.logbookentry([num2str(obj.order),' tap FFE A2 tracked levels']);
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Noi = X - D;
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end
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function [y,d_hat] = equalize(obj,x,d,mu,epochs,N,training,showviz)
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arguments
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obj
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x
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d
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mu
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epochs
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N
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training
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showviz %#ok<INUSA>
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end
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x = [zeros(floor(obj.order/2),1); x; zeros(obj.order,1)];
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lambda = mu;
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n_symbols = ceil(N / obj.sps);
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y = zeros(n_symbols,1);
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d_hat = zeros(n_symbols,1);
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err = zeros(n_symbols,1);
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constellation = obj.constellation;
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adaption_code = obj.adaptionCode();
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adaption_is_rls = adaption_code == 3;
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mask = ones(obj.order,1);
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maincursor_pos = ceil(length(obj.e)/2);
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grad = 0;
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weight = 0;
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update = 0;
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if mu == 0 || (~obj.dd_mode && ~training)
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epochs = 1;
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end
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dc_level_enabled = obj.dc_level_avg_bufferlength_a2 > 1 && any(obj.dc_level_weights_a2(:) ~= 0);
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if dc_level_enabled
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if isempty(constellation)
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builtin("error","FFE_A2TrackedLevels:MissingConstellation", ...
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"A2 tracked-level decision requires obj.constellation to be set.");
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end
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n_levels = numel(constellation);
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if isscalar(obj.dc_level_weights_a2)
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dc_level_weight_by_level = repmat(obj.dc_level_weights_a2,n_levels,1);
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elseif numel(obj.dc_level_weights_a2) == n_levels
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dc_level_weight_by_level = obj.dc_level_weights_a2(:);
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else
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builtin("error","FFE_A2TrackedLevels:InvalidDCLevelWeights", ...
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"dc_level_weights_a2 must be scalar or have one entry per constellation level.");
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end
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dc_level_buffer_len = obj.dc_level_avg_bufferlength_a2;
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dc_level_buffer = NaN(n_levels,dc_level_buffer_len);
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dc_level_buffer_pos_by_level = zeros(n_levels,1);
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dc_level_sum_by_level = zeros(n_levels,1);
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dc_level_buffer_valid_count_by_level = zeros(n_levels,1);
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dc_level_offset_by_level = zeros(n_levels,1);
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dc_level_valid_count_by_level = zeros(n_levels,1);
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dc_level_update_blocklength = obj.dc_level_update_blocklength_a2;
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if dc_level_update_blocklength <= 0
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dc_level_update_blocklength = dc_level_buffer_len;
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end
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dc_level_update_blocklength = max(1,floor(dc_level_update_blocklength));
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dc_level_window_future_fraction = obj.dc_smoothing_a2; %#ok<NASGU>
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end
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debug_enabled = obj.save_debug;
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if debug_enabled
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obj.debug_struct.error = NaN(1,n_symbols);
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obj.debug_struct.error_first_epoch = NaN(1,n_symbols);
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obj.debug_struct.main_cursor = NaN(1,n_symbols);
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obj.debug_struct.mu_nlms = NaN(1,n_symbols);
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obj.debug_struct.update_gradient = NaN(1,n_symbols);
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obj.debug_struct.dc_level_mpi_est = NaN(1,n_symbols);
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obj.debug_struct.dc_level_weight = NaN(1,n_symbols);
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obj.debug_struct.dc_level_valid_count = NaN(1,n_symbols);
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obj.debug_struct.dc_level_symbol_idx = NaN(1,n_symbols);
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obj.debug_struct.dc_level_decision_level = NaN(1,n_symbols);
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obj.debug_struct.dc_level_y_raw = NaN(1,n_symbols);
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if training
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obj.debug_struct.error_tr = NaN(1,n_symbols);
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obj.debug_struct.update_tr = NaN(1,n_symbols);
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else
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obj.debug_struct.error_dd = NaN(1,n_symbols);
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obj.debug_struct.update = NaN(1,n_symbols);
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end
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end
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for epoch = 1:epochs
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symbol = 0;
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for sample = 1:obj.sps:N
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symbol = symbol + 1;
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dc_level_offset = 0;
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dc_level_weight = 0;
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dc_level_valid_count = 0;
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U = x(obj.order+sample-1:-1:sample);
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y(symbol,1) = (obj.e.*mask).' * U;
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y_raw = y(symbol);
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if training
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d_hat(symbol,1) = d(symbol);
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[~,symbol_idx] = min(abs(d_hat(symbol) - constellation));
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dc_level_decision_level = constellation(symbol_idx);
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else
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if dc_level_enabled
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dc_level_ramp_by_level = min(dc_level_valid_count_by_level / dc_level_buffer_len,1);
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dc_level_decision_constellation = constellation + ...
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dc_level_weight_by_level .* dc_level_ramp_by_level .* dc_level_offset_by_level;
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[~,symbol_idx] = min(abs(y_raw - dc_level_decision_constellation));
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dc_level_decision_level = dc_level_decision_constellation(symbol_idx);
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else
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[~,symbol_idx] = min(abs(y_raw - constellation));
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dc_level_decision_level = constellation(symbol_idx);
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end
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d_hat(symbol,1) = constellation(symbol_idx);
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end
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dc_level_symbol_idx = symbol_idx;
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if dc_level_enabled
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dc_level_offset = dc_level_offset_by_level(symbol_idx);
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dc_level_valid_count = dc_level_valid_count_by_level(symbol_idx);
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dc_level_weight = dc_level_weight_by_level(symbol_idx) * ...
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min(dc_level_valid_count / dc_level_buffer_len,1);
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[dc_level_buffer,dc_level_buffer_pos_by_level,dc_level_sum_by_level, ...
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dc_level_buffer_valid_count_by_level,dc_level_offset_by_level, ...
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dc_level_valid_count_by_level] = obj.updateTrackedLevelBuffer( ...
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dc_level_buffer,dc_level_buffer_pos_by_level,dc_level_sum_by_level, ...
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dc_level_buffer_valid_count_by_level,dc_level_offset_by_level, ...
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dc_level_valid_count_by_level,y_raw,symbol_idx,symbol, ...
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dc_level_update_blocklength,constellation);
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end
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err(symbol) = d_hat(symbol) - y(symbol);
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if training || obj.dd_mode
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switch adaption_code
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case 1
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normU = (U.'*U) + eps;
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weight = mu / normU;
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grad = err(symbol) * U;
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update = grad * weight;
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obj.e = obj.e + update;
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case 2
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weight = mu;
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grad = err(symbol) * U;
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update = grad * weight;
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obj.e = obj.e + update;
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case 3
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denom = lambda + U.' * obj.P * U;
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k = (obj.P * U) / denom;
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update = k * err(symbol);
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obj.e = obj.e + update;
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obj.P = (1/lambda) * (obj.P - k * (U.' * obj.P));
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end
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end
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if debug_enabled && epoch == 1
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obj.debug_struct.error_first_epoch(1,symbol) = err(symbol) * err(symbol)';
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end
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if debug_enabled && epoch == epochs
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error_power = err(symbol) * err(symbol)';
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update_power = update.'*update ./ (sqrt((obj.e.'*obj.e) / obj.order) + eps);
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obj.debug_struct.error(1,symbol) = error_power;
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obj.debug_struct.main_cursor(1,symbol) = abs(obj.e(maincursor_pos));
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obj.debug_struct.mu_nlms(1,symbol) = weight;
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obj.debug_struct.update_gradient(1,symbol) = grad.'*grad;
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obj.debug_struct.dc_level_mpi_est(1,symbol) = dc_level_offset;
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obj.debug_struct.dc_level_weight(1,symbol) = dc_level_weight;
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obj.debug_struct.dc_level_valid_count(1,symbol) = dc_level_valid_count;
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obj.debug_struct.dc_level_symbol_idx(1,symbol) = dc_level_symbol_idx;
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obj.debug_struct.dc_level_decision_level(1,symbol) = dc_level_decision_level;
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obj.debug_struct.dc_level_y_raw(1,symbol) = y_raw;
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if training
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obj.debug_struct.error_tr(1,symbol) = error_power;
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obj.debug_struct.update_tr(1,symbol) = update_power;
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else
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obj.debug_struct.error_dd(1,symbol) = error_power;
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obj.debug_struct.update(1,symbol) = update_power;
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end
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end
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end
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end
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if ~adaption_is_rls
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obj.P = [];
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end
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end
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end
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methods (Access = private)
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function adaption_code = adaptionCode(obj)
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if obj.adaption_technique == adaption_method.nlms
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adaption_code = 1;
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elseif obj.adaption_technique == adaption_method.lms
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adaption_code = 2;
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elseif obj.adaption_technique == adaption_method.rls
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adaption_code = 3;
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else
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builtin("error","FFE_A2TrackedLevels:InvalidAdaptionTechnique", ...
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"Unsupported FFE adaption technique.");
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end
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end
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end
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methods (Static, Access = private)
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function [buffer,buffer_pos_by_level,level_sum_by_level,buffer_valid_count_by_level, ...
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offset_by_level,valid_count_by_level] = updateTrackedLevelBuffer( ...
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buffer,buffer_pos_by_level,level_sum_by_level,buffer_valid_count_by_level, ...
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offset_by_level,valid_count_by_level,new_value,symbol_idx,symbol, ...
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update_blocklength,constellation)
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buffer_pos = buffer_pos_by_level(symbol_idx) + 1;
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if buffer_pos > size(buffer,2)
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buffer_pos = 1;
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end
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buffer_pos_by_level(symbol_idx) = buffer_pos;
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old_value = buffer(symbol_idx,buffer_pos);
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if isfinite(old_value)
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level_sum_by_level(symbol_idx) = level_sum_by_level(symbol_idx) - old_value;
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buffer_valid_count_by_level(symbol_idx) = buffer_valid_count_by_level(symbol_idx) - 1;
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end
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if isfinite(new_value)
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buffer(symbol_idx,buffer_pos) = new_value;
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level_sum_by_level(symbol_idx) = level_sum_by_level(symbol_idx) + new_value;
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buffer_valid_count_by_level(symbol_idx) = buffer_valid_count_by_level(symbol_idx) + 1;
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else
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buffer(symbol_idx,buffer_pos) = NaN;
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end
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if mod(symbol,update_blocklength) == 0
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valid_count_by_level = buffer_valid_count_by_level;
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has_valid = valid_count_by_level > 0;
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offset_by_level(:) = 0;
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offset_by_level(has_valid) = ...
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level_sum_by_level(has_valid) ./ valid_count_by_level(has_valid) - ...
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constellation(has_valid);
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end
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end
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end
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end
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