Added:

- Class folder 'Timing Recovery' with different timing recoveries
- Minimal example for the timing recovery on the FSO data
- New evaluation scripts in the FSO project folder

Classes/04_DSP/Timing Recovery/MaxVar_Timing_Recovery.m

@@ -0,0 +1,111 @@
+classdef MaxVar_Timing_Recovery < handle
+
+    properties(Access=public)
+        mode
+        sps
+        fsym
+        fadc
+        num_tau
+        comp_signal
+        comp_mode
+    end
+
+    methods(Access=public)
+        function obj = MaxVar_Timing_Recovery(options)
+            arguments(Input)
+
+                options.mode = 0;
+                options.sps = 2;
+                options.fsym = 32e9;
+                options.fadc = 80e9;
+                options.num_tau = 64;
+                options.comp_signal = 0;
+                options.comp_mode = 0;
+            end
+
+            fn = fieldnames(options);
+            for n = 1:numel(fn)
+                obj.(fn{n}) = options.(fn{n});
+            end
+
+            %obj-Initialization here%
+
+        end
+
+        function [data_out] = process(obj, data_in)
+
+            data_out = data_in;
+            x = data_in.signal;
+
+            if obj.comp_mode
+                our_signal = data_in;
+                their_signal = obj.comp_signal;
+            end
+
+            if obj.mode == 0
+                vars = zeros(obj.sps,1);
+                for phi = 1:obj.sps
+
+                    % Test variance for different start samples
+                    y_phi = x(phi:obj.sps:end);
+                    vars(phi) = var(y_phi);
+
+                    % Comparison to reference signal
+                    if obj.comp_mode
+                        our_signal.signal = x(phi:obj.sps:end);
+                        our_signal.fs = 6e9;
+                        our_signal.normalize("mode","rms").plot("displayname",['Our signal, ' num2str(vars(phi))],'fignum',1231+phi);
+                        their_signal.normalize("mode","rms").plot("displayname",'Their signal','fignum',1231+phi);
+                    end
+
+                end
+                
+                % Choose signal configuration with the maximum variance
+                [~,phi_opt] = max(vars);
+                
+                y = x(phi_opt:obj.sps:end).';   
+
+            elseif obj.mode == 1
+                % Create a grid with different (sub)sample starting points
+                T = 1/obj.fsym;
+                t = (0:length(x)-1)/obj.fadc;
+                tauGrid = linspace(0, T, obj.num_tau);
+                
+                % Interpolate the signal starting from every defined point
+                % and calculate the MMSE/variance
+                vars = zeros(size(tauGrid));
+                for i = 1:numel(tauGrid)
+                    tau = tauGrid(i);
+                    % tk = linspace(tau, t(end), length(x)/obj.sps);
+                    tk = tau : T : t(end)+tau;
+                    xk = interp1(t, x, tk, 'linear', 'extrap');
+                    if obj.comp_mode % MMSE
+                        e = xk.' - obj.comp_signal.signal;
+                        vars(i) = mean(abs(e).^2);
+                    else % Variance
+                        vars(i) = var(xk, 1);
+                    end
+                end
+                
+                if obj.comp_mode % MMSE
+                    [~,idx] = min(vars);
+                else % Variance
+                    [~,idx] = max(vars);
+                end
+                tau_opt = tauGrid(idx);
+                
+                % Choosing the signal at optimum
+                % tk = linspace(tau_opt, t(end), length(x)/obj.sps);
+                tk = tau_opt : T : t(end)+tau_opt;
+                y = interp1(t, x, tk, 'linear', 'extrap');
+            end
+            % if length(y) ~= length(x)/obj.sps
+            %     y = [y 0];
+            % end
+            data_out.signal = y.';
+        end
+
+
+    end
+end
+