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v2 design: independent masks + affinity-aware Wiener demultiplexer

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Redesign after the independent-mask dominance finding: the affinity
now parameterizes the receiver (closed-form Wiener) instead of the
mask ensemble. New Theorem 1 (spectral closed form), floors
sqrt(1-b^2)/2 vs 1/2, full-cooperation bound with equality at b=1.
GPU (torch) Monte Carlo backend, decision-directed SIC baseline,
TikZ block diagram source, verification suite V1-V11.
This commit is contained in:
KiHoLee
2026-08-17 02:12:10 +09:00
parent b8b853e62e
commit 358faecc0c
29 changed files with 1777 additions and 1514 deletions
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data/floor_validation.csv
+35 -35
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@@ -1,35 +1,35 @@
d,snr_db,mse_mc,mse_theory,mse_ideal
256,0.0,283.9142603214685,284.4533071258869,283.41188049318094
256,2.5,160.10089036917105,160.41563908393022,159.37421245122425
256,5.0,90.47776215634474,90.66413246369561,89.62270583098966
256,7.5,51.32748447743017,51.439977796849504,50.398551164143555
256,10.0,29.312928645832216,29.38261468202405,28.3411880493181
256,12.5,16.934181412329476,16.978847877828375,15.937421245122422
256,15.0,9.973810638369487,10.00369721580492,8.962270583098967
256,17.5,6.060239200519523,6.081281749120308,5.039855116414356
256,20.0,3.85987571082472,3.8755454376377614,2.8341188049318093
256,22.5,2.622819942039895,2.6351687572181945,1.5937421245122423
256,25.0,1.9273969939302285,1.9376536910158488,0.8962270583098966
256,27.5,1.5365003821408372,1.5454121443473878,0.5039855116414356
256,30.0,1.3168093834480725,1.3248385131991331,0.28341188049318095
256,32.5,1.1933627827422904,1.2008008451571766,0.15937421245122424
256,35.0,1.1240146926635879,1.131049338536942,0.08962270583098966
256,37.5,1.085070664488797,1.0918251838700959,0.05039855116414356
256,40.0,1.0632107739660197,1.0697678207552703,0.028341188049318098
768,0.0,853.4623064741292,851.2770681122488,850.2356414795429
768,2.5,480.3951698733645,479.1640639863787,478.12263735367276
768,5.0,270.60393697803266,269.9095441256749,268.86811749296896
768,7.5,152.62953339008442,152.23708012513663,151.19565349243067
768,10.0,86.28755819977675,86.06499078066025,85.0235641479543
768,12.5,48.98065441173488,48.85369036807322,47.81226373536727
768,15.0,28.001388546341435,27.928238382002856,26.886811749296903
768,17.5,16.203841270734593,16.160991981949017,15.119565349243066
768,20.0,9.569563575405624,9.543783047501382,8.502356414795429
768,22.5,5.838813072859685,5.822653006242679,4.781226373536727
768,25.0,3.7408413998745558,3.730107807635642,2.6886811749296897
768,27.5,2.5610528622492597,2.553383167630259,1.5119565349243067
768,30.0,1.8975997387446928,1.8916622741854952,0.8502356414795429
768,32.5,1.5245056756935615,1.519549270059625,0.4781226373536727
768,35.0,1.314694250809021,1.3102947501989213,0.268868117492969
768,37.5,1.1967047053652895,1.1926222861983828,0.15119565349243066
768,40.0,1.1303513753850125,1.1264501968539065,0.0850235641479543
d,snr_db,mse_mc,mse_theory,mse_blind
256,0.0,0.9958906187265965,0.9957520371754321,0.9961240310077519
256,2.5,0.9926509086327597,0.9924951337006896,0.993148778755109
256,5.0,0.9869671196373861,0.9868069561728815,0.9879451709874938
256,7.5,0.9771456527581006,0.9770064578879146,0.9789579793127183
256,10.0,0.9605855179298334,0.9605076750198117,0.9637681159420289
256,12.5,0.9337484810109989,0.9337823722702523,0.9390092836053628
256,15.0,0.8928736458420425,0.8930612771894957,0.9009452871484813
256,17.5,0.8360494261292735,0.8363998816883345,0.8473840548704382
256,20.0,0.7661668636283875,0.7666566714783413,0.7807017543859648
256,22.5,0.691947677239615,0.6925661718278007,0.709267994905624
256,25.0,0.6243632968967908,0.6251571720537481,0.6440702380534542
256,27.5,0.5709153641061163,0.571972710197798,0.5927077630509127
256,30.0,0.5331897043219835,0.53458472828743,0.5567375886524822
256,32.5,0.5086536205122679,0.5104122867933932,0.5335732525163734
256,35.0,0.4935273743565432,0.4956303135714446,0.5194512459464362
256,37.5,0.4844975136532381,0.48689966319840416,0.5111276997838433
256,40.0,0.4792009242590312,0.48184935117050987,0.5063191153238548
768,0.0,0.9986765012793098,0.9985760128125698,0.9987012987012988
768,2.5,0.9976163216681129,0.9974733083167204,0.9976952053744985
768,5.0,0.9957307732307438,0.9955242936982399,0.9959160824250755
768,7.5,0.9923981843904192,0.992095537514675,0.9927835275542491
768,10.0,0.9865629253484912,0.9861129415585025,0.9873096446700508
768,12.5,0.9764985106901773,0.9758221660225336,0.9778701398348755
768,15.0,0.9595662490049409,0.9585462259188507,0.9619573584726929
768,17.5,0.9322122252329521,0.9306888249982047,0.9361315623151921
768,20.0,0.8907470407123728,0.8885385986762078,0.8966942148760331
768,22.5,0.8334967999962878,0.8304680517855016,0.8417416365176289
768,25.0,0.7637208092945489,0.759888721537542,0.7741964962231777
768,27.5,0.6903787748107578,0.6859650675890866,0.7028866275721191
768,30.0,0.6242938905723492,0.6196325851274082,0.638728323699422
768,32.5,0.5725413154691661,0.5679130695479454,0.5887951848908111
768,35.0,0.5363309035044117,0.5318795970416631,0.554141276684715
768,37.5,0.5129687106701781,0.5087260331425658,0.5319605114462806
768,40.0,0.498680130948561,0.4946227489687355,0.5184899845916795
1 d snr_db mse_mc mse_theory mse_ideal mse_blind
2 256 0.0 283.9142603214685 0.9958906187265965 284.4533071258869 0.9957520371754321 283.41188049318094 0.9961240310077519
3 256 2.5 160.10089036917105 0.9926509086327597 160.41563908393022 0.9924951337006896 159.37421245122425 0.993148778755109
4 256 5.0 90.47776215634474 0.9869671196373861 90.66413246369561 0.9868069561728815 89.62270583098966 0.9879451709874938
5 256 7.5 51.32748447743017 0.9771456527581006 51.439977796849504 0.9770064578879146 50.398551164143555 0.9789579793127183
6 256 10.0 29.312928645832216 0.9605855179298334 29.38261468202405 0.9605076750198117 28.3411880493181 0.9637681159420289
7 256 12.5 16.934181412329476 0.9337484810109989 16.978847877828375 0.9337823722702523 15.937421245122422 0.9390092836053628
8 256 15.0 9.973810638369487 0.8928736458420425 10.00369721580492 0.8930612771894957 8.962270583098967 0.9009452871484813
9 256 17.5 6.060239200519523 0.8360494261292735 6.081281749120308 0.8363998816883345 5.039855116414356 0.8473840548704382
10 256 20.0 3.85987571082472 0.7661668636283875 3.8755454376377614 0.7666566714783413 2.8341188049318093 0.7807017543859648
11 256 22.5 2.622819942039895 0.691947677239615 2.6351687572181945 0.6925661718278007 1.5937421245122423 0.709267994905624
12 256 25.0 1.9273969939302285 0.6243632968967908 1.9376536910158488 0.6251571720537481 0.8962270583098966 0.6440702380534542
13 256 27.5 1.5365003821408372 0.5709153641061163 1.5454121443473878 0.571972710197798 0.5039855116414356 0.5927077630509127
14 256 30.0 1.3168093834480725 0.5331897043219835 1.3248385131991331 0.53458472828743 0.28341188049318095 0.5567375886524822
15 256 32.5 1.1933627827422904 0.5086536205122679 1.2008008451571766 0.5104122867933932 0.15937421245122424 0.5335732525163734
16 256 35.0 1.1240146926635879 0.4935273743565432 1.131049338536942 0.4956303135714446 0.08962270583098966 0.5194512459464362
17 256 37.5 1.085070664488797 0.4844975136532381 1.0918251838700959 0.48689966319840416 0.05039855116414356 0.5111276997838433
18 256 40.0 1.0632107739660197 0.4792009242590312 1.0697678207552703 0.48184935117050987 0.028341188049318098 0.5063191153238548
19 768 0.0 853.4623064741292 0.9986765012793098 851.2770681122488 0.9985760128125698 850.2356414795429 0.9987012987012988
20 768 2.5 480.3951698733645 0.9976163216681129 479.1640639863787 0.9974733083167204 478.12263735367276 0.9976952053744985
21 768 5.0 270.60393697803266 0.9957307732307438 269.9095441256749 0.9955242936982399 268.86811749296896 0.9959160824250755
22 768 7.5 152.62953339008442 0.9923981843904192 152.23708012513663 0.992095537514675 151.19565349243067 0.9927835275542491
23 768 10.0 86.28755819977675 0.9865629253484912 86.06499078066025 0.9861129415585025 85.0235641479543 0.9873096446700508
24 768 12.5 48.98065441173488 0.9764985106901773 48.85369036807322 0.9758221660225336 47.81226373536727 0.9778701398348755
25 768 15.0 28.001388546341435 0.9595662490049409 27.928238382002856 0.9585462259188507 26.886811749296903 0.9619573584726929
26 768 17.5 16.203841270734593 0.9322122252329521 16.160991981949017 0.9306888249982047 15.119565349243066 0.9361315623151921
27 768 20.0 9.569563575405624 0.8907470407123728 9.543783047501382 0.8885385986762078 8.502356414795429 0.8966942148760331
28 768 22.5 5.838813072859685 0.8334967999962878 5.822653006242679 0.8304680517855016 4.781226373536727 0.8417416365176289
29 768 25.0 3.7408413998745558 0.7637208092945489 3.730107807635642 0.759888721537542 2.6886811749296897 0.7741964962231777
30 768 27.5 2.5610528622492597 0.6903787748107578 2.553383167630259 0.6859650675890866 1.5119565349243067 0.7028866275721191
31 768 30.0 1.8975997387446928 0.6242938905723492 1.8916622741854952 0.6196325851274082 0.8502356414795429 0.638728323699422
32 768 32.5 1.5245056756935615 0.5725413154691661 1.519549270059625 0.5679130695479454 0.4781226373536727 0.5887951848908111
33 768 35.0 1.314694250809021 0.5363309035044117 1.3102947501989213 0.5318795970416631 0.268868117492969 0.554141276684715
34 768 37.5 1.1967047053652895 0.5129687106701781 1.1926222861983828 0.5087260331425658 0.15119565349243066 0.5319605114462806
35 768 40.0 1.1303513753850125 0.498680130948561 1.1264501968539065 0.4946227489687355 0.0850235641479543 0.5184899845916795