FFE now has a automatic optimization of the mu-parameters -> enables the fast comparison of LMS, NLMS and RLS and also good for very long filters (1000+ taps) which might be unstable else.
Minor changes here and there
This commit is contained in:
Silas Oettinghaus
@@ -15,7 +15,7 @@ classdef FFE < handle
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e
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e_tr
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error
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debug_struct
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len_tr
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mu_tr
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@@ -31,6 +31,13 @@ classdef FFE < handle
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constellation % symbol constellation
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decide %wether to return the (hard) decisions or the result after FFE (soft)
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save_debug = 0;
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debug_struct
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optmize_mus = 0;
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mu_optimization
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mu_optimization_iter = 0;
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end
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methods
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@@ -51,6 +58,9 @@ classdef FFE < handle
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options.decide = false;
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options.save_debug = 0;
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options.optmize_mus = 0;
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end
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fn = fieldnames(options);
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@@ -75,6 +85,12 @@ classdef FFE < handle
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delta = 0.05;
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obj.P = (1/delta) * eye(obj.order);
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if obj.optmize_mus
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obj.optimizeMus(X.signal,D.signal);
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obj.e = zeros(obj.order,1);
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obj.P = (1/delta) * eye(obj.order);
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end
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% Training Mode
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training = 1;
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showviz = 0;
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@@ -131,7 +147,6 @@ classdef FFE < handle
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mask = ones(obj.order,1);
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maincursor_pos=ceil(length(obj.e)/2);
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always_ideal_decision = 0;
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save_debug = 0;
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grad =0;
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weight = 0;
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update = 0;
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@@ -205,21 +220,88 @@ classdef FFE < handle
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end
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if save_debug
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if obj.save_debug
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obj.debug_struct.error(epoch,symbol) = err(symbol) * err(symbol)'; % Instantaneous square error
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if training
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obj.debug_struct.error_tr(epoch,symbol) = err(symbol) * err(symbol)'; % Instantaneous square error
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obj.debug_struct.update_tr(epoch,symbol) = update.'*update ./ rms(obj.e);
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else
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% if symbol == length(d)
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% M = numel(unique(d));
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% bits_ref = PAMmapper(M,0).demap(d);
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% bits_eq = PAMmapper(M,0).demap(d_hat);
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% [~,~,obj.debug_struct.ber(epoch)] = calc_ber(bits_eq,bits_ref);
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% end
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end
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obj.debug_struct.main_cursor(epoch,symbol) = abs(obj.e(maincursor_pos));
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obj.debug_struct.mu_nlms(epoch,symbol) = weight;
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obj.debug_struct.update_gradient(epoch,symbol) = grad.'*grad;
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obj.debug_struct.update(epoch,symbol) = update.'*update ./ rms(obj.e);
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% obj.debug_struct.main_cursor(epoch,symbol) = abs(obj.e(maincursor_pos));
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% obj.debug_struct.mu_nlms(epoch,symbol) = weight;
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% obj.debug_struct.update_gradient(epoch,symbol) = grad.'*grad;
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% obj.debug_struct.update(epoch,symbol) = update.'*update ./ rms(obj.e);
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end
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end
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end
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end
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function optimizeMus(obj,x,d)
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switch obj.adaption_technique
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case adaption_method.lms
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mu_range = [1e-5, 1e-2];
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case adaption_method.nlms
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mu_range = [1e-3, 5e-1];
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case adaption_method.rls
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mu_range = [0.98, 0.99999];
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end
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mu_tr_var = optimizableVariable("mu_tr",mu_range,"Transform","log");
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vars = mu_tr_var;
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if obj.dd_mode
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vars = [vars, optimizableVariable("mu_dd",mu_range,"Transform","log")];
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end
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obj.mu_optimization_iter = 0;
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obj.mu_optimization = bayesopt(@(p)obj.muObjective(p,x,d),vars, ...
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"MaxObjectiveEvaluations",10, ...
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"AcquisitionFunctionName","expected-improvement-plus", ...
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"IsObjectiveDeterministic",false, ...
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"Verbose",0, ...
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"PlotFcn",[]);
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obj.mu_tr = obj.mu_optimization.XAtMinObjective.mu_tr;
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if obj.dd_mode
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obj.mu_dd = obj.mu_optimization.XAtMinObjective.mu_dd;
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end
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fprintf("\nFFE mu opt done: mu_tr=%9.3e, mu_dd=%9.3e, metric=%9.3e\n", ...
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obj.mu_tr,obj.mu_dd,obj.mu_optimization.MinObjective);
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end
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function objective = muObjective(obj,params,x,d)
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old_debug = obj.save_debug;
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obj.save_debug = 1;
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obj.e = zeros(obj.order,1);
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obj.P = (1/0.05) * eye(obj.order);
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obj.debug_struct = struct();
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obj.equalize(x,d,params.mu_tr,obj.epochs_tr,obj.len_tr,1,0);
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if obj.dd_mode
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obj.equalize(x,d,params.mu_dd,obj.epochs_dd,numel(x),0,0);
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objective = mean(obj.debug_struct.error(end,:),"omitnan");
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else
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objective = mean(obj.debug_struct.error_tr(end,:),"omitnan");
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end
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if ~isfinite(objective)
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objective = inf;
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end
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obj.mu_optimization_iter = obj.mu_optimization_iter + 1;
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if obj.dd_mode
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fprintf("\rFFE mu opt %02d: mu_tr=%9.3e, mu_dd=%9.3e, metric=%9.3e", ...
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obj.mu_optimization_iter,params.mu_tr,params.mu_dd,objective);
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else
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fprintf("\rFFE mu opt %02d: mu_tr=%9.3e, metric=%9.3e", ...
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obj.mu_optimization_iter,params.mu_tr,objective);
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end
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obj.save_debug = old_debug;
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end
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end
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end
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end
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@@ -54,7 +54,7 @@ classdef DBHandler < handle
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options.password, ... % Password (or getSecret)
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"Vendor", "MySQL", ...
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"Server", options.server, ...
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"PortNumber", 3306, ...
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"PortNumber", options.port, ...
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"JDBCDriverLocation", "C:\Users\Silas\Documents\mysql-connector-j-9.3.0\mysql-connector-j-9.3.0.jar");
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end
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