PR stuff
This commit is contained in:
Silas Oettinghaus
12
.vscode/launch.json
vendored
Normal file
12
.vscode/launch.json
vendored
Normal file
@@ -0,0 +1,12 @@
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{
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// Verwendet IntelliSense zum Ermitteln möglicher Attribute.
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// Zeigen Sie auf vorhandene Attribute, um die zugehörigen Beschreibungen anzuzeigen.
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// Weitere Informationen finden Sie unter https://go.microsoft.com/fwlink/?linkid=830387
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"version": "0.2.0",
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"configurations": [
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{
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"type": "matlab",
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"name": "Debug MATLAB"
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}
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]
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}
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@@ -136,6 +136,7 @@ classdef PAMsource
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%%%%%% Duobinary %%%%%%%%%%%
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% this is translation from user input to db_mode which was added later... "precode" und "encode" sind auch besser zu verstehen an dieser stelle daher hab ichs gelassen
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if obj.db_precode
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obj.duobinary_mode = db_mode.db_precoded;
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end
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@@ -148,10 +149,13 @@ classdef PAMsource
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case db_mode.no_db
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case db_mode.db_precoded
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symbols = Duobinary().precode(symbols);
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% symbols = Duobinary().precode(symbols);
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symbols = Partialresponse().precode(symbols);
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case db_mode.db_encoded
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symbols = Duobinary().precode(symbols);
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symbols = Duobinary().encode(symbols);
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% symbols = Duobinary().precode(symbols);
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% symbols = Duobinary().encode(symbols);
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symbols = Partialresponse().precode(symbols);
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symbols = Partialresponse().encode(symbols);
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end
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@@ -191,8 +191,9 @@ classdef Signalgenerator
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% PAMsource behavior. If length is omitted, it sets the
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% output length. Internally it is converted to the PRMS
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% order per stream.
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% Default output length is 2^(order-1), except for
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% PAM-6-style dimension = 5 where it is 2^(order-2).
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% Default output length is 2^(order-1) for all mapper
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% shapes. PAM-6 still reduces the internal PRMS order
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% to keep the register length manageable.
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% skip Number of PRMS symbols to advance before output. This
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% is useful when different blocks should use shifted
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% sections of the same deterministic sequence.
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@@ -275,6 +276,10 @@ classdef Signalgenerator
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switch obj.form
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case {signalform.random, signalform.prms}
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if obj.is_pam6_shape()
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% PAM-6 consumes 5 input bits for 2 output symbols.
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% To keep the symbol count aligned with the other
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% PAM formats, reduce the number of generated rows
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% before flattening to the mapper-ready bit vector.
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length = 2^max(0, obj.order - 2);
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else
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length = 2^max(0, obj.order - 1);
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@@ -291,19 +296,16 @@ classdef Signalgenerator
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end
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function prms_order = internal_prms_order(obj)
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bits_per_symbol = obj.prms_bits_per_symbol();
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bits_per_symbol = obj.prms_parallel_width();
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prms_order = max(1, floor(obj.order / bits_per_symbol));
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end
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function bits_per_symbol = prms_bits_per_symbol(obj)
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if (~isempty(obj.M) && obj.M == 6) || (isempty(obj.M) && obj.dimension == 5)
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% PAM-6 mapping in this repo consumes 5 bits for 2 symbols.
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bits_per_symbol = 2.5;
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elseif ~isempty(obj.M)
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bits_per_symbol = log2(obj.M);
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function width = prms_parallel_width(obj)
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if ~isempty(obj.M)
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width = obj.mapper_bit_dimension();
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else
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bits_per_symbol = obj.dimension;
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width = obj.dimension;
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end
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end
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@@ -2,16 +2,21 @@ classdef Partialresponse
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%PARTIALRESPONSE Generalized symbol-domain partial-response coding.
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properties
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M = []
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order = 1
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end
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methods
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function obj = Partialresponse(varargin)
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parser = inputParser;
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parser.addParameter("order", 1);
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parser.parse(varargin{:});
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function obj = Partialresponse(options)
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arguments
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options.M = [];
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options.order = 1;
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end
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obj.order = parser.Results.order;
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fn = fieldnames(options);
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for n = 1:numel(fn)
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obj.(fn{n}) = options.(fn{n});
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end
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end
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function signal = precode(obj, signal, options)
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@@ -134,13 +139,19 @@ classdef Partialresponse
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end
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end
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function M = resolveM(~, data, M)
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function M = resolveM(obj, data, M)
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if isempty(M)
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M = obj.M;
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end
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if isempty(M)
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M = numel(unique(round(data, 12)));
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end
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end
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function M = resolveEncodedM(obj, data, M)
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if isempty(M)
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M = obj.M;
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end
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if isempty(M)
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I = numel(unique(round(data, 12)));
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if obj.order == 1
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@@ -36,7 +36,7 @@ end
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received_sd(lvl,ref_symbols==constellation(lvl)) = eq_signal(ref_symbols==constellation(lvl));
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end
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scaling = PAMmapper(numel(constellation),0).get_scaling;
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% scaling = PAMmapper(numel(constellation),0).get_scaling;
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%%% FFE histogram
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clf
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@@ -6,10 +6,10 @@ repoRoot = fileparts(fileparts(fileparts(mfilename("fullpath"))));
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addpath(genpath(repoRoot));
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orders = [2 4 6 8];
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userOrder = 7;
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userOrder = 18;
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fprintf("PAM | bits checked | errors | BER\n");
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fprintf("----+--------------+--------+-----\n");
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fprintf("PAM | bits shape |symbols shape | bits checked | errors | BER\n");
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fprintf("----+--------------+----------------+--------------+------\n");
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for M = orders
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bitSignal = Signalgenerator( ...
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@@ -23,5 +23,5 @@ for M = orders
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[checkedBits, errors, ber] = calc_ber(rxBits.signal, bitSignal.signal);
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fprintf("%3d | %12d | %6d | %.1e\n", M, checkedBits, errors, ber);
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fprintf("%3d | %3d x %3d |%3d x %3d | %12d | %6d | %.1e\n", M, size(bitSignal.signal, 1),size(bitSignal.signal, 2),size(txSymbols.signal, 1),size(txSymbols.signal, 2), checkedBits, errors, ber);
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end
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@@ -2,7 +2,7 @@
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dsp_options.append_to_db = 0;
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dsp_options.max_occurences = 1;
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experiment = "highspeed_2024";
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experiment = "highspeed_2024";
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dsp_options.mode = "load_run_id"; % 'simulate' & 'load_files'
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dsp_options.load_file_path = struct();
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@@ -11,10 +11,12 @@ if dsp_options.mode == "load_run_id"
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if experiment == "highspeed_2024"
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dsp_options.database_type = "mysql";
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dsp_options.dataBase = 'labor_highspeed';%'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\silas_labor_newdsp_newstructure.db';
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dsp_options.storage_path = 'Z:\2024\sioe_labor\';
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dsp_options.dataBase = 'labor_highspeed';%'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\silas_labor_newdsp_newstructure.db';
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dsp_options.storage_path = 'W:\labdata\sioe_labor\';
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db = DBHandler("dataBase", [dsp_options.dataBase],...
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"type", dsp_options.database_type,"server","134.245.243.254","user","silas","password","silas");
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"type", dsp_options.database_type,...
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"server","192.168.178.192",...% "server","134.245.243.254",...
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"user","silas","password","silas");
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elseif experiment == "mpi_ecoc_2025"
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@@ -1,7 +1,7 @@
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% minimal example IM/DD
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M = 4;
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fsym = 112e9;
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fsym = 160e9;
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apply_pulsef = 1;
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fdac = 256e9;
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@@ -50,21 +50,34 @@ mu_dc = 0.005;
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mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3];
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mu_dfe = 0.0004;
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sf = signalform.prms;
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Tx_bits = Signalgenerator( ...
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"form", sf, ...
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"M", M, ...
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"order", 16).process();
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Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
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Symbols = PAMmapper(M,0).map(Tx_bits);
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Symbols.fs = fsym;
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Symbols_plain = Symbols;
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pr = Partialresponse("order", 1,"M",M);
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Symbols = pr.precode(Symbols);
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pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha);
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Digi_sig = pform.process(Symbols);
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n = 10;
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Digi_sig = Digi_sig.resample("fs_in",Digi_sig.fs,"fs_out",fdac,"n",n,"beta",5);
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[Digi_sig,Symbols,Tx_bits] = PAMsource(...
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"fsym",fsym,"M",M,"order",18,"useprbs",0,...
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"fs_out",fdac,...
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"applyclipping",0,"clipfactor",1.5,...
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"applypulseform",apply_pulsef,"pulseformer",Pform,...
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"randkey",random_key,...
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'duobinary_mode',duob_mode,...
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"mrds_code",0,"mrds_blocklength",512).process();
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%%%%% AWG
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% El_sig = M8199A("kover",kover).process(Digi_sig);
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El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",0,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
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El_sig = M8199A("kover",kover).process(Digi_sig);
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% El_sig = AWG("fdac",fdac,"f_cutoff",fsym*0.4,"lpf_active",1,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1).process(Digi_sig);
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tx_bwl = fsym*0.3;
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El_sig = Filter('filtdegree',4,"f_cutoff",tx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
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El_sig.spectrum("displayname",'Digi Spectrum','fignum',1,'normalizeTo0dB',1);
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xlim([0,130]);
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ylim([-30,5]);
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@@ -73,7 +86,7 @@ ylim([-30,5]);
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%%%%% Electrical Driver Amplifier %%%%%%
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% El_sig = Amplifier("amp_mode","ideal_no_noise","gain_mode","gain","amplification_db",3).process(El_sig);
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El_sig = El_sig.normalize("mode","oneone");
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scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2));
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scaling = 0.8*(u_pi/2-abs(vbias-u_pi/2));
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El_sig = El_sig .* scaling;
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%%%%% MODULATE E/O CONVERSION %%%%%%
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@@ -109,29 +122,63 @@ Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,...
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% pulse is symmetric, hence we can use pulsef firectly as matched filter.
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% It feels off (bit I think correct) that the fsym is now the output freq.!!
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% -> output 2 sps to omit timing recovery!?
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Pform = Pulseformer("fsym",fsym,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha,"matched",1);
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Scpe_sig = Pform.process(Scpe_sig);
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Scpe_sig.spectrum("displayname",'Signal after matched filter','fignum',1,'normalizeTo0dB',1);
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if 0
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Pform = Pulseformer("fsym",fsym,"fdac",2*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha,"matched",1);
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Scpe_sig = Pform.process(Scpe_sig);
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end
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% Scpe_sig.spectrum("displayname",'Signal after matched filter','fignum',1,'normalizeTo0dB',1);
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%
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% %%
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% %%%%%% Sample to 2x fsym %%%%%%
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% Scpe_sig = Scpe_sig.resample("fs_out",2*fsym);
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% Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
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Scpe_sig = Scpe_sig.resample("fs_out",2*fsym);
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Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
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%%
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%%%%%% Sync Rx signal with reference %%%%%%
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[Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",1);
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Scpe_sig.spectrum("displayname",'Opt Spectrum','fignum',11,'normalizeTo0dB',1);
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[Scpe_sig,~] = Scpe_sig.tsynch("reference",Symbols,"fs_ref",fsym,"debug_plots",0);
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% Scpe_sig.spectrum("displayname",'Opt Spectrum','fignum',11,'normalizeTo0dB',1);
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% Scpe_sig = Filter('filtdegree',4,"f_cutoff",Symbols.fs.*0.5,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);
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Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
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Scpe_sig.signal = Scpe_sig.signal(1:2*length(Symbols));
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%%
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%% -------------------- MLSE --------------------
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mlse_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
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ffe_order = [50, 2, 2];
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eq_ = EQ("Ne",ffe_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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% -------------------- FFE --------------------
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%Duobinary Targeting
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db_ref_sequence = Duobinary().encode(Symbols);
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[eq_signal, eq_noise] = eq_.process(Scpe_sig,db_ref_sequence);
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showLevelHistogram(eq_signal,db_ref_sequence)
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[mlse_sig_sd,LLR,GMI_MLSE] = mlse_.process(eq_signal,Symbols);
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Rx_bits = PAMmapper(M,0).demap(mlse_sig_sd);
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Tx_bits_omitprecode = PAMmapper(M,0).demap(Symbols);
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[bits,errors,ber_wo,errorIndice] = calc_ber(Rx_bits.signal,Tx_bits_omitprecode.signal);
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fprintf(["BER w/o precode: %.2d \n"],ber_wo);
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showErrorBurstCount(mlse_sig_sd, Symbols,"displayname",'MLSE DB w/o Precode','fignum',4); % prior to coding
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%%
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mlse_sig_sd = pr.encode(mlse_sig_sd);
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mlse_sig_sd = pr.decode(mlse_sig_sd);
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Rx_bits = PAMmapper(M,0).demap(mlse_sig_sd);
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[bits,errors,ber,errorIndice] = calc_ber(Rx_bits.signal,Tx_bits.signal);
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fprintf(["BER w/ precode: %.2d \n"],ber);
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showErrorBurstCount(mlse_sig_sd, Symbols_plain,"displayname",'MLSE DB w/ Precode','fignum',5);
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%% -------------------- FFE --------------------
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ffe_order = [50, 0, 0];
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eq_ = EQ("Ne",ffe_order,"Nb",[2,0,0], ...
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"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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@@ -139,44 +186,24 @@ eq_ = EQ("Ne",ffe_order,"Nb",[2,0,0], ...
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"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
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% eq_ = FFE("epochs_tr",4,"epochs_dd",5,"len_tr",4096,"mu_dd",0.01,"mu_tr",0.01,"order",50,"sps",2,"decide",0, "adaption",adaption_method.nlms,"dd_mode",1);
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eq_ = FFE_DFE("epochs_tr",5,"epochs_dd",5,"len_tr",512,"ffe_mu_dd",1e-4,"dfe_mu_dd",5e-4,"ffe_mu_tr",0,"dfe_mu_tr",0,"ffe_order",99,"dfe_order",99,"sps",2,"decide",0);
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% eq_ = FFE_DFE("epochs_tr",5,"epochs_dd",5,"len_tr",512,"ffe_mu_dd",1e-4,"dfe_mu_dd",5e-4,"ffe_mu_tr",0,"dfe_mu_tr",0,"ffe_order",99,"dfe_order",99,"sps",2,"decide",0);
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[eq_signal_sd, eq_noise] = eq_.process(Scpe_sig, Symbols);
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output.ffe_results = ffe(eq_,M,Scpe_sig,Symbols,Tx_bits, ...
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"precode_mode",duob_mode,'showAnalysis',1,"postFFE",[], ...
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"eth_style_symbol_mapping",0);
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eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
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output.ffe_results.metrics.print("description",'DFE');
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Rx_bits = PAMmapper(M,0).demap(eq_signal_hd);
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Tx_bits_omitprecode = PAMmapper(M,0).demap(Symbols);
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[bits,errors,ber_wo,errorIndice] = calc_ber(Rx_bits.signal,Tx_bits_omitprecode.signal);
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fprintf(["BER w/o precode: %.2d \n"],ber_wo);
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%%
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% -------------------- VNLE + MLSE --------------------
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pf_ncoeffs = 1;
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ffe_order3 = [50, 5, 5];
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eq_v = EQ("Ne",ffe_order3,"Nb",dfe_order, ...
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"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
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"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005, ...
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"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
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pf_ = Postfilter("ncoeff",pf_ncoeffs,"useBurg",1);
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mlse_ = MLSE("duobinary_output",0,'M',M,'trellis_states',PAMmapper(M,0).levels);
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[output.vnle_results, output.mlse_results] = vnle_postfilter_mlse(eq_v, pf_, mlse_, M, Scpe_sig, Symbols, Tx_bits, ...
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"precode_mode", duob_mode, 'showAnalysis', 1, "postFFE", [], "eth_style_symbol_mapping", 0);
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output.mlse_results.metrics.print("description",'MLSE');
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%%
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% -------------------- DB target --------------------
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mlse_db_ = MLSE("DIR",[1,1],"duobinary_output",0,"M",M,'trellis_states',PAMmapper(M,0).levels);
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||||
ffe_order = [50, 5, 5];
|
||||
eq_ = EQ("Ne",ffe_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5, ...
|
||||
"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
|
||||
output.dbt_results = duobinary_target(eq_,mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
|
||||
"precode_mode", duob_mode, 'showAnalysis', 0, "postFFE", []);
|
||||
|
||||
output.dbt_results.metrics.print("description",'Duobinary');
|
||||
showErrorBurstCount(eq_signal_hd, Symbols,"displayname",'No Precode','fignum',8); % prior to coding
|
||||
|
||||
eq_signal_hd = pr.encode(eq_signal_hd);
|
||||
eq_signal_hd = pr.decode(eq_signal_hd);
|
||||
Rx_bits = PAMmapper(M,0).demap(eq_signal_hd);
|
||||
[bits,errors,ber,errorIndice] = calc_ber(Rx_bits.signal,Tx_bits.signal);
|
||||
fprintf(["BER w/ precode: %.2d \n"],ber);
|
||||
|
||||
showErrorBurstCount(eq_signal_hd, Symbols_plain,"displayname",'Incl. Precode','fignum',7);
|
||||
|
||||
|
||||
Reference in New Issue
Block a user