558 lines
22 KiB
Matlab
558 lines
22 KiB
Matlab
classdef FFE_test < IMDDTestCase
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methods (Test, TestTags = {'unit', 'fast', 'dsp', 'ffe'})
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function constructorStoresDefaultsAndInitialState(testCase)
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ffe = FFE();
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testCase.verifyEqual(ffe.sps, 2);
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testCase.verifyEqual(ffe.order, 15);
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testCase.verifyEqual(ffe.len_tr, 4096);
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testCase.verifyEqual(ffe.mu_tr, 0);
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testCase.verifyEqual(ffe.epochs_tr, 5);
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testCase.verifyEqual(ffe.adaption_technique, adaption_method.lms);
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testCase.verifyEqual(ffe.dd_mode, 1);
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testCase.verifyEqual(ffe.mu_dd, 1e-5);
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testCase.verifyEqual(ffe.epochs_dd, 5);
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testCase.verifyFalse(logical(ffe.optimize_dc_tracking_params));
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testCase.verifyEqual(ffe.dc_tracking_optimization_delay_weight, 1e-3);
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testCase.verifyEqual(ffe.dc_tracking_persistence_gain, 0);
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testCase.verifyEqual(ffe.dc_tracking_power_exponent, 2);
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testCase.verifyEqual(ffe.dc_avg_bufferlength_a1, 0);
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testCase.verifyEqual(ffe.dc_avg_update_blocklength_a1, 0);
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testCase.verifyEqual(ffe.dc_smoothing_a1, 0);
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testCase.verifyEqual(ffe.dc_level_avg_bufferlength_a2, 0);
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testCase.verifyEqual(ffe.dc_level_update_blocklength_a2, 0);
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testCase.verifyEqual(ffe.dc_smoothing_a2, 0);
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testCase.verifyEqual(ffe.dc_level_decision_mode_a2, "residual");
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testCase.verifyEqual(ffe.dc_level_weights_a2, 0);
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testCase.verifyEqual(ffe.dc_tracking_buffer_len, 1);
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testCase.verifyEqual(ffe.ffe_update_buffer_len, 1);
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testCase.verifyFalse(logical(ffe.optimize_a2_level_weights));
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testCase.verifyEqual(ffe.a2_level_weight_optimization_max_evals, 30);
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testCase.verifyEqual(ffe.a2_level_weight_max, 1);
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testCase.verifyFalse(ffe.decide);
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testCase.verifyEqual(ffe.e, zeros(ffe.order, 1));
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testCase.verifyEqual(ffe.error, 0);
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end
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function noUpdateModeKeepsWeightsAtZeroAndPreservesSamplingRate(testCase)
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x = makeSignal([-1; 1; -1; 1], 32e9);
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d = makeSignal([-1; 1; -1; 1], 8e9);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"len_tr", length(x), ...
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"mu_tr", 0, ...
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"epochs_tr", 1, ...
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"mu_dd", 0, ...
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"epochs_dd", 1, ...
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"dd_mode", 0, ...
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"decide", false, ...
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"adaption_technique", adaption_method.lms);
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[y, noi] = ffe.process(x, d);
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testCase.verifyEqual(ffe.e, 0);
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testCase.verifyEqual(ffe.e_tr, 0);
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testCase.verifyEqual(y.signal, zeros(size(x.signal)), "AbsTol", 1e-12);
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testCase.verifyEqual(y.fs, d.fs);
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testCase.verifyEqual(noi.signal, -d.signal, "AbsTol", 1e-12);
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testCase.verifyEqual(length(y.signal), length(x.signal));
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end
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function trainingModeLearnsFromTinySyntheticChannel(testCase)
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x = makeSignal([1; -1; 1; -1], 16e9);
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d = makeSignal([1; -1; 1; -1], 4e9);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"len_tr", length(x), ...
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"mu_tr", 0.5, ...
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"epochs_tr", 1, ...
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"mu_dd", 0, ...
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"epochs_dd", 1, ...
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"dd_mode", 0, ...
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"decide", false, ...
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"adaption_technique", adaption_method.lms);
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[y, noi] = ffe.process(x, d);
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testCase.verifyEqual(y.fs, d.fs);
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testCase.verifyClass(y, 'Informationsignal');
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testCase.verifyClass(noi, 'Informationsignal');
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testCase.verifyNotEqual(ffe.e, 0);
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testCase.verifyNotEqual(ffe.e_tr, 0);
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testCase.verifyNotEqual(y.signal, zeros(size(x.signal)));
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testCase.verifyEqual(length(y.signal), length(x.signal));
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end
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function dcTrackingBufferDelaysDcUpdateUntilBlockBoundary(testCase)
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x = zeros(4, 1);
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d = ones(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0.1, ...
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"dc_tracking_buffer_len", 2, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.constellation = unique(d);
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ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(ffe.e_dc, 0.19, "AbsTol", 1e-12);
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end
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function dcTrackingUnbufferedPathUpdatesEverySymbol(testCase)
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x = zeros(4, 1);
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d = ones(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0.1, ...
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"dc_tracking_buffer_len", 1, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.constellation = unique(d);
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ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(ffe.e_dc, 1 - 0.9^4, "AbsTol", 1e-12);
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end
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function dcTrackingBlockUpdateUsesMeanBlockError(testCase)
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ffe = FFE("dc_tracking_mu", 0.1);
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[e_dc_next,stats] = ffe.dcTrackingBlockUpdate(0.5, [1; 2; 3]);
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testCase.verifyEqual(e_dc_next, 0.7, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.err_mean, 2, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.mu_eff, 0.1, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.update, 0.2, "AbsTol", 1e-12);
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end
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function dcTrackingBlockUpdateDoesNotSuppressLargeErrorPower(testCase)
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ffe = FFE("dc_tracking_mu", 0.1);
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[e_dc_next,stats] = ffe.dcTrackingBlockUpdate(0, [10; 10]);
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testCase.verifyEqual(e_dc_next, 1, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.err_mean, 10, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.mu_eff, 0.1, "AbsTol", 1e-12);
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end
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function dcTrackingBlockUpdateCanBoostPersistentMean(testCase)
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ffe = FFE("dc_tracking_mu", 0.1);
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[e_dc_next,stats] = ffe.dcTrackingBlockUpdate(0, [2; 2; 2], ...
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"persistence_gain", 1);
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testCase.verifyEqual(e_dc_next, 0.4, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.persistence_scale, 1, "AbsTol", 1e-12);
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testCase.verifyEqual(stats.mu_eff, 0.2, "AbsTol", 1e-12);
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end
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function dcTrackingLoopUsesBlockPersistenceGain(testCase)
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x = zeros(4, 1);
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d = ones(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0.1, ...
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"dc_tracking_adaptive_enabled", true, ...
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"dc_tracking_persistence_gain", 1, ...
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"dc_tracking_buffer_len", 2, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.constellation = unique(d);
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ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(ffe.e_dc, 0.36, "AbsTol", 1e-12);
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end
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function ffeDcTrackingClassMatchesFullUnbufferedPath(testCase)
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x = zeros(4, 1);
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d = ones(4, 1);
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settings = { ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0.1, ...
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"dc_tracking_buffer_len", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms};
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full = FFE(settings{:});
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tracking = FFE_DCTracking(settings{:});
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full.constellation = unique(d);
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tracking.constellation = unique(d);
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[y_full,d_hat_full] = full.equalize(x, d, 0, 1, numel(x), true, false);
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[y_tracking,d_hat_tracking] = tracking.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y_tracking, y_full, "AbsTol", 1e-12);
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testCase.verifyEqual(d_hat_tracking, d_hat_full, "AbsTol", 1e-12);
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testCase.verifyEqual(tracking.e_dc, full.e_dc, "AbsTol", 1e-12);
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testCase.verifyEqual(tracking.debug_struct.dc_tracking_est, ...
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full.debug_struct.dc_tracking_est, "AbsTol", 1e-12);
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end
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function ffeDcTrackingClassMatchesFullBufferedPersistencePath(testCase)
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x = zeros(4, 1);
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d = ones(4, 1);
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settings = { ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0.1, ...
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"dc_tracking_adaptive_enabled", true, ...
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"dc_tracking_persistence_gain", 1, ...
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"dc_tracking_buffer_len", 2, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms};
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full = FFE(settings{:});
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tracking = FFE_DCTracking(settings{:});
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full.constellation = unique(d);
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tracking.constellation = unique(d);
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[y_full,d_hat_full] = full.equalize(x, d, 0, 1, numel(x), true, false);
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[y_tracking,d_hat_tracking] = tracking.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y_tracking, y_full, "AbsTol", 1e-12);
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testCase.verifyEqual(d_hat_tracking, d_hat_full, "AbsTol", 1e-12);
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testCase.verifyEqual(tracking.e_dc, full.e_dc, "AbsTol", 1e-12);
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testCase.verifyEqual(tracking.debug_struct.dc_tracking_mu_eff, ...
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full.debug_struct.dc_tracking_mu_eff, "AbsTol", 1e-12);
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testCase.verifyEqual(tracking.debug_struct.dc_tracking_est, ...
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full.debug_struct.dc_tracking_est, "AbsTol", 1e-12);
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end
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function ffeBufferDelaysTapUpdateUntilBlockBoundary(testCase)
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x = ones(4, 1);
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d = ones(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_tracking_mu", 0, ...
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"ffe_update_buffer_len", 2, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.constellation = unique(d);
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ffe.equalize(x, d, 0.1, 1, numel(x), true, false);
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testCase.verifyEqual(ffe.e, 0.19, "AbsTol", 1e-12);
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end
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function dcAvgA1BufferlengthOneLeavesInputUnchanged(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_avg_bufferlength_a1", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, x, "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_avg_offset, zeros(1,4), "AbsTol", 1e-12);
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end
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function dcAvgA1SubtractsCausalMovingAverageByDefault(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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expected_offset = [0, 0, 0, 2];
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expected_y = [1; 2; 3; 2];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_avg_bufferlength_a1", 3, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, expected_y, "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_avg_offset, expected_offset, "AbsTol", 1e-12);
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end
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function dcAvgA1SmoothingIsReservedForOfflineVariants(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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expected_offset = [0, 0, 0, 2];
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expected_y = [1; 2; 3; 2];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_avg_bufferlength_a1", 3, ...
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"dc_smoothing_a1", 0.5, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, expected_y, "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_avg_offset, expected_offset, "AbsTol", 1e-12);
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end
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function dcAvgA1UpdateBlocklengthOneRefreshesEverySymbol(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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expected_offset = [0, 1, 1.5, 2];
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expected_y = [1; 1; 1.5; 2];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_avg_bufferlength_a1", 3, ...
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"dc_avg_update_blocklength_a1", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, expected_y, "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_avg_offset, expected_offset, "AbsTol", 1e-12);
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end
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function dcAvgA1WarnsWhenCombinedWithDcTracking(testCase)
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testCase.verifyWarning(@() FFE( ...
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"dc_avg_bufferlength_a1", 3, ...
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"dc_tracking_mu", 0.1), "FFE:DCAvgWithDcTracking");
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end
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function dcLevelAvgA2SubtractsScalarWeightedResidual(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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expected_y = [1; 2; 1.5; 2.5];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_level_avg_bufferlength_a2", 2, ...
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"dc_level_weights_a2", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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ffe.constellation = 0;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, expected_y, "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_mpi_est, [0, 0, 1.5, 1.5], "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_weight, [0, 0, 1, 1], "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_valid_count, [0, 0, 2, 2]);
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end
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function dcLevelAvgA2UpdateBlocklengthOneRefreshesEverySymbol(testCase)
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x = (1:4).';
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d = zeros(4, 1);
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_level_avg_bufferlength_a2", 2, ...
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"dc_level_update_blocklength_a2", 1, ...
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"dc_level_weights_a2", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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ffe.constellation = 0;
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, [1; 1.5; 1.5; 1.5], "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_mpi_est, [0, 1, 1.5, 2.5], "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_weight, [0, 0.5, 1, 1], "AbsTol", 1e-12);
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testCase.verifyEqual(ffe.debug_struct.dc_level_valid_count, [0, 1, 2, 2]);
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end
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function dcLevelAvgA2UsesVectorWeightsInConstellationOrder(testCase)
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x = [1; 3; 1; 4];
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d = [0; 2; 0; 2];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_level_avg_bufferlength_a2", 2, ...
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"dc_level_weights_a2", [0, 1], ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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ffe.constellation = [0; 2];
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[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
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testCase.verifyEqual(y, [1; 3; 1; 3.5], "AbsTol", 1e-12);
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end
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function dcLevelAvgA2TrackedLevelsUseAdaptiveDecision(testCase)
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x = [0.5; 2.5; 0.5; 2.5; 1.3];
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d = [0; 2; 0; 2; 0];
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ffe = FFE( ...
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"sps", 1, ...
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"order", 1, ...
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"dc_level_avg_bufferlength_a2", 2, ...
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"dc_level_update_blocklength_a2", 1, ...
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"dc_level_decision_mode_a2", "tracked_levels", ...
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"dc_level_weights_a2", 1, ...
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"save_debug", true, ...
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"dd_mode", 0, ...
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"adaption_technique", adaption_method.lms);
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ffe.e = 1;
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ffe.constellation = [0; 2];
|
|
|
|
[y,d_hat] = ffe.equalize(x, d, 0, 1, numel(x), false, false);
|
|
|
|
testCase.verifyEqual(y, x, "AbsTol", 1e-12);
|
|
testCase.verifyEqual(d_hat, d, "AbsTol", 1e-12);
|
|
testCase.verifyEqual( ...
|
|
ffe.debug_struct.dc_level_decision_level, ...
|
|
[0, 2, 0.25, 2.25, 0.5], ...
|
|
"AbsTol", 1e-12);
|
|
end
|
|
|
|
function ffeA2ResidualClassSubtractsScalarWeightedResidual(testCase)
|
|
x = (1:4).';
|
|
d = zeros(4, 1);
|
|
|
|
ffe = FFE_A2Residual( ...
|
|
"sps", 1, ...
|
|
"order", 1, ...
|
|
"dc_level_avg_bufferlength_a2", 2, ...
|
|
"dc_level_weights_a2", 1, ...
|
|
"save_debug", true, ...
|
|
"dd_mode", 0, ...
|
|
"adaption_technique", adaption_method.lms);
|
|
ffe.e = 1;
|
|
ffe.constellation = 0;
|
|
|
|
[y,~] = ffe.equalize(x, d, 0, 1, numel(x), true, false);
|
|
|
|
testCase.verifyEqual(y, [1; 2; 1.5; 2.5], "AbsTol", 1e-12);
|
|
testCase.verifyEqual(ffe.debug_struct.dc_level_mpi_est, [0, 0, 1.5, 1.5], "AbsTol", 1e-12);
|
|
testCase.verifyEqual(ffe.debug_struct.dc_level_weight, [0, 0, 1, 1], "AbsTol", 1e-12);
|
|
testCase.verifyEqual(ffe.debug_struct.dc_level_valid_count, [0, 0, 2, 2]);
|
|
end
|
|
|
|
function ffeA2ResidualClassMatchesFullResidualPath(testCase)
|
|
x = [1; 3; 1; 4; 2; 5];
|
|
d = [0; 2; 0; 2; 0; 2];
|
|
settings = { ...
|
|
"sps", 1, ...
|
|
"order", 1, ...
|
|
"dc_level_avg_bufferlength_a2", 2, ...
|
|
"dc_level_update_blocklength_a2", 1, ...
|
|
"dc_level_weights_a2", [0.25, 0.75], ...
|
|
"save_debug", true, ...
|
|
"dd_mode", 0, ...
|
|
"adaption_technique", adaption_method.lms};
|
|
|
|
full = FFE(settings{:});
|
|
residual = FFE_A2Residual(settings{:});
|
|
full.e = 1;
|
|
residual.e = 1;
|
|
full.constellation = [0; 2];
|
|
residual.constellation = [0; 2];
|
|
|
|
[y_full,d_hat_full] = full.equalize(x, d, 0, 1, numel(x), true, false);
|
|
[y_residual,d_hat_residual] = residual.equalize(x, d, 0, 1, numel(x), true, false);
|
|
|
|
testCase.verifyEqual(y_residual, y_full, "AbsTol", 1e-12);
|
|
testCase.verifyEqual(d_hat_residual, d_hat_full, "AbsTol", 1e-12);
|
|
testCase.verifyEqual(residual.debug_struct.dc_level_mpi_est, ...
|
|
full.debug_struct.dc_level_mpi_est, "AbsTol", 1e-12);
|
|
testCase.verifyEqual(residual.debug_struct.dc_level_weight, ...
|
|
full.debug_struct.dc_level_weight, "AbsTol", 1e-12);
|
|
end
|
|
|
|
function dcLevelAvgA2RejectsUnknownDecisionMode(testCase)
|
|
testCase.verifyError(@() FFE("dc_level_decision_mode_a2", "unknown"), ...
|
|
"FFE:InvalidA2DecisionMode");
|
|
end
|
|
|
|
function ffeA2TrackedLevelsClassUsesAdaptiveDecision(testCase)
|
|
x = [0.5; 2.5; 0.5; 2.5; 1.3];
|
|
d = [0; 2; 0; 2; 0];
|
|
|
|
ffe = FFE_A2TrackedLevels( ...
|
|
"sps", 1, ...
|
|
"order", 1, ...
|
|
"dc_level_avg_bufferlength_a2", 2, ...
|
|
"dc_level_update_blocklength_a2", 1, ...
|
|
"dc_level_weights_a2", 1, ...
|
|
"save_debug", true, ...
|
|
"dd_mode", 0, ...
|
|
"adaption_technique", adaption_method.lms);
|
|
ffe.e = 1;
|
|
ffe.constellation = [0; 2];
|
|
|
|
[y,d_hat] = ffe.equalize(x, d, 0, 1, numel(x), false, false);
|
|
|
|
testCase.verifyEqual(y, x, "AbsTol", 1e-12);
|
|
testCase.verifyEqual(d_hat, d, "AbsTol", 1e-12);
|
|
testCase.verifyEqual( ...
|
|
ffe.debug_struct.dc_level_decision_level, ...
|
|
[0, 2, 0.25, 2.25, 0.5], ...
|
|
"AbsTol", 1e-12);
|
|
end
|
|
|
|
function dcLevelAvgA2WarnsWhenCombinedWithDcTracking(testCase)
|
|
testCase.verifyWarning(@() FFE( ...
|
|
"dc_level_avg_bufferlength_a2", 2, ...
|
|
"dc_level_weights_a2", 1, ...
|
|
"dc_tracking_mu", 0.1), "FFE:DCLevelAvgWithOtherDcSuppression");
|
|
end
|
|
|
|
function a2InitialWeightGuessFollowsLevelVarianceSlope(testCase)
|
|
x = [ ...
|
|
0.98; 1.02; 1.00; 1.01; ...
|
|
1.90; 2.10; 2.00; 2.08; ...
|
|
2.50; 3.50; 3.00; 3.40];
|
|
d = [ ...
|
|
ones(4,1); ...
|
|
2*ones(4,1); ...
|
|
3*ones(4,1)];
|
|
|
|
ffe = FFE("sps", 1, "a2_level_weight_max", 1);
|
|
ffe.constellation = [1; 2; 3];
|
|
|
|
[weights,stats] = ffe.a2LevelWeightInitialGuess(x,d);
|
|
|
|
testCase.verifySize(weights, [3, 1]);
|
|
testCase.verifyGreaterThan(weights(3), weights(2));
|
|
testCase.verifyGreaterThan(weights(2), weights(1));
|
|
testCase.verifyEqual(max(weights), 0.7, "AbsTol", 1e-12);
|
|
testCase.verifyGreaterThan(stats.variance_slope, 0);
|
|
end
|
|
end
|
|
end
|
|
|
|
function sig = makeSignal(values, fs)
|
|
base = Signal(values);
|
|
sig = Informationsignal(values, "fs", fs, "logbook", base.logbook);
|
|
end
|