Minor Changes here and there
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@@ -140,6 +140,8 @@ classdef FFE < handle
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err(symbol) = y(symbol) - d_hat(symbol); % Instantaneous error
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true_err(symbol) = y(symbol) - d(symbol); % Instantaneous error
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if mio ~= 0
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obj.e = obj.e - (mio * err(symbol) * U) ; % Weight update rule of LMS
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else
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@@ -101,7 +101,7 @@ classdef FFE_DCremoval < handle
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err = 0;
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% e_dc_buffer = NaN(100,1);
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e_dc_buffer = NaN(10,1);
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e_dc_buffer = NaN(1,1);
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e_dc_est = 0;
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for epoch = 1 : epochs
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@@ -124,12 +124,15 @@ classdef FFE_FFDCAVG < handle
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ylim([-1 1])
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drawnow
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end
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for epoch = 1 : epochs
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symbol = 0;
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err_buffer = zeros(numel(obj.constellation),50);
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err_buffer = zeros(numel(obj.constellation),90);
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dc_err = zeros(numel(obj.constellation),1);
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dc_sto = NaN(numel(obj.constellation),N);
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for sample = 1 : obj.sps : N
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symbol = symbol+1;
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@@ -142,16 +145,29 @@ classdef FFE_FFDCAVG < handle
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[~,symbol_idx] = min(abs(d(symbol) - obj.constellation)); % decision for closest constellation point
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d_hat(symbol,1) = d(symbol);
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else
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[~,symbol_idx] = min(abs(y(symbol) - obj.constellation)); % decision for closest constellation point
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always_correct_decision = 0;
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if always_correct_decision
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[~,symbol_idx] = min(abs(d(symbol) - obj.constellation)); % decision for closest constellation point
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else
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[~,symbol_idx] = min(abs(y(symbol) - obj.constellation)); % decision for closest constellation point
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end
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d_hat(symbol,1) = obj.constellation(symbol_idx);
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end
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err(symbol) = y(symbol) - d_hat(symbol); % Instantaneous error
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err_buffer(symbol_idx,1) = err(symbol);
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err_buffer(symbol_idx,:) = circshift(err_buffer(symbol_idx,:),1);
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y(symbol) = y(symbol) - obj.mu_buff*mean(err_buffer(symbol_idx,:));
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if 1
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%use buffer for dc-error
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err_buffer(symbol_idx,1) = err(symbol);
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err_buffer(symbol_idx,:) = circshift(err_buffer(symbol_idx,:),1);
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dc_sto(symbol_idx,symbol) = obj.mu_buff*mean(err_buffer(symbol_idx,:));
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y(symbol) = y(symbol) - obj.mu_buff * mean(err_buffer(symbol_idx,:));
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else
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%or use 1+alpha*D as adaptive error
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dc_err(symbol_idx) = dc_err(symbol_idx) + obj.mu_buff * err(symbol);
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dc_sto(symbol_idx,symbol) = dc_err(symbol_idx);
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y(symbol) = y(symbol) - dc_err(symbol_idx);
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end
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if training
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[~,symbol_idx] = min(abs(d(symbol) - obj.constellation)); % decision for closest constellation point
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@@ -173,8 +189,10 @@ classdef FFE_FFDCAVG < handle
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if mod(sample,100) == 1 && showviz
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a2.XData = 1:2*numel(y);
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a2.YData = repelem(y, 2);
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a3.XData = 1:2*numel(d_hat);
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a3.YData = repelem(d_hat, 2);
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a4.Value = sample;
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% b.YData = x(symbol:symbol+500);
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c.YData = obj.e;
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