Matlab Model Serdes Systems
MathWorksOfficialCreated by MathWorks
- Skill
- Tool integration
- Science and research
- BSD-2-Clause
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a comprehensive framework for designing and validating Serializer/Deserializer (SerDes) systems. It covers the full development lifecycle, from initial architecture exploration and channel characterization to parameter optimization and the generation of industry-standard IBIS-AMI models. Users can simulate NRZ and PAM-N links, evaluate equalization architectures like FFE, CTLE, and DFE, and perform compliance testing using statistical and time-domain analysis.
What it does
- Models and simulates high-speed serial and parallel links including NRZ and PAM-N signaling.
- Characterizes channels using loss models, S-parameter files, and crosstalk scenarios.
- Optimizes equalization architectures such as FFE, CTLE, and DFE using genetic algorithms.
- Performs statistical and time-domain analysis including eye diagrams and jitter decomposition.
- Exports designs to Simulink for IBIS-AMI model generation and compilation.
- Validates compiled models against behavioral baselines for compliance and performance.
When to use it
- When designing SerDes links for specific data rates and channel loss profiles.
- When evaluating and tuning equalization architectures to meet signal integrity targets.
- When you need to generate IBIS-AMI models for Tx, Rx, Redriver, or Retimer components.
- When performing compliance checks using eye masks and jitter budgets.
- When analyzing captured waveforms from oscilloscopes or simulations.
Advantages
- Full-arc workflow from design exploration to compiled model delivery.
- Supports advanced PAM-N modulation schemes up to PAM16.
- Enables programmatic parameter sweeps and optimization for design space exploration.
- Provides robust validation tools to ensure compiled models match behavioral references.
- Integrates seamlessly with Simulink for complex time-domain system simulations.
Usage examples
- “Create a SerdesSystem object for a PAM4 link and run a statistical analysis.”
- The agent initializes a SerdesSystem with specified Tx/Rx blocks, configures the channel, and executes the analysis() method to generate eye diagrams and performance metrics.
- “Export my current SerDes design to a Simulink model for AMI generation.”
- The agent uses exportToSimulink(sys) to generate the Simulink representation and prepares the IbisAmiManager settings for model compilation.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/matlab/matlab-model-serdes-systems/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip matlab-model-serdes-systems.zip -d .agents/skills
Documentation by MathWorks
Modeling and Simulating SerDes Systems
Design, analyze, and deliver high-speed serial link models using SerDes Toolbox. From architecture exploration through IBIS-AMI model generation, covers the full workflow for NRZ and PAM-N links (PAM3 through PAM16).
When to Use
System design and architecture exploration
Designing SerDes links for a target data rate, signaling scheme (NRZ, PAM4, PAM-N), and channel loss
Evaluating equalization architectures (FFE, CTLE, DFE) and optimizing tap settings
Sweeping design parameters to find optimal configurations
Using industry reference designs (PCIe, USB4, DDR5, CEI, UCIe) as starting points
Characterizing Tx/Rx analog effects (parasitic capacitance, rise time, termination impedance)
Building custom datapath blocks for nonstandard equalization
Channel modeling and characterization
Loading S-parameter Touchstone files into SerdesSystem
Modeling channels with loss profiles, crosstalk (FEXT/NEXT), and aggressors
Fitting CTLE transfer functions from measured data via
ctlefit
IBIS-AMI model generation
Building IBIS-AMI models for Tx, Rx, Redriver, or Retimer configurations
Exporting to Simulink, configuring AMI parameters, and compiling
.ami/.ibs/.dll/.soScripting Simulink simulations and parameter sweeps with
sim/parsim
Analysis and validation
Running statistical and time-domain simulations
Processing eye diagrams (eye height, eye width, COM, VEC, bathtub curves)
Decomposing jitter (TJ, RJ, DJ, DDJ, DCD, ISI)
Validating compiled AMI models against behavioral baselines
Running compliance checks with eye masks and jitter budgets
When NOT to Use
RF/microwave circuit design, antenna modeling, or baseband DSP filter design
General Simulink model scripting unrelated to SerDes
Must-Follow Rules
System Setup
SymbolTime / SampleInterval must yield an integer SamplesPerSymbol — fractional ratios cause silent errors
TxModel/RxModelareTransmitter/Receiverobjects — not cell arrays. Construct withTransmitter('Blocks', {block1, block2}).Transmitterrequires single-quoted property names —Transmitter("Blocks", ...)throws anismembererror.Receiverand all other classes accept double quotesSignal conversion functions require column vectors —
impulse2pulse,pulse2stateye, etc. error on row vectorsInclude
AnalogModelandJitterAndNoisefor realistic results — bareTransmitter/Receiverwithout analog models produce optimistic COM (1-2 dB higher). Seereference/equalization-tuning.mdfor parameter guidance (rise time, parasitic C, termination R)
Equalization
Set
WaveTypeexplicitly when using datapath blocks directly in MATLAB — Simulink sets this automatically, but MATLAB defaults to"Sample"Adapted DFE/CTLE parameters are in
results.outparams— NOT on the block object. Afteranalysis(),sys.RxModel.Blocks{k}.TapWeightsstill holds initial values. In system objects chains, adapted taps are the second output:[y, taps] = dfecdr(x)DFECDR Mode=0 is passthrough in Sample mode — DFE only applies with Mode≥1. Pre-load adapted taps from
outparamswith Mode=1 for instant convergence, or use Mode=2 with 10xEqualizationGain(9.6e-04) for self-converging chainsSet
Modulationon DFECDR for PAM-N in system objects chains — Simulink inherits it from the model workspace, but MATLAB defaults to 2 (NRZ). Without this, PAM4 DFE adaptation fails silently
Metrics and Waveforms
Metrics.summary.EWis in picoseconds (already scaled) — do NOT multiply by 1e12.EHis in volts. PAM-N returns N-1 values per metric (e.g., PAM4 → 3 eyes, PAM8 → 7 eyes)Channel impulse from
analysis()is in V/s — when usingfilter()for time-domain convolution, multiply bydt:filter(impulse * dt, 1, wave). Without scaling, amplitudes blow up by ~10^11pulse2waveoperates on the stimulus provided — the output modulation depends on the input pattern (NRZ or PAM-N)
AMI and Simulink
Init-Only models cannot adapt — if DFE taps or CDR converge at runtime, you need a Dual model (both Init and GetWave)
AMI validation requires Signal Integrity Toolbox —
serdes.AMIrunner and the AMI Simulink block need both SerDes Toolbox and Signal Integrity ToolboxAMI GetWave: call in a chunked loop —
serdes.AMIpassesBlockSize(default 1024) toAMI_GetWave, so onlyBlockSizesamples are processed per call. You must call the object in aforloop withBlockSize-length chunks. State is preserved between calls via the DLL memory handleAMI GetWave: set
SkipFirstBlock = falsewhen calling from MATLAB — the default (true) is for Simulink's internal signal buffering and causes the first block to pass through unprocessedAMI Init:
RowSizemust match impulse length —serdes.AMIcrashes MATLAB (process termination, no error) ifRowSizedoesn't matchnumel(impulse)AMI generation requires Simulink model — use
IbisAmiManagerGUI orserdes.AMIExportwithexport()programmatically (see Programmatic AMI Generation)
Workflow
Design Exploration
Most projects start here. The goal is to find the right equalization architecture and settings for your channel.
Design — Create a
SerdesSystemwith Tx/Rx blocks and channel (loss model or S-parameters)Analyze — Run
analysisfor statistical results,plotStatEyefor eye diagrams,analysisReportfor metricsSweep — Vary channel loss, FFE taps, CTLE gain, DFE taps, or jitter to map the design space
Compare — Evaluate architectures (FFE-only vs FFE+CTLE vs FFE+CTLE+DFE) using COM, eye height, eye width
Select — Choose the configuration that meets margin targets, then freeze equalization settings
Use SerdesSystem for programmatic exploration; serdesDesigner for interactive GUI work.
Waveform Processing
When you have a captured or imported waveform (e.g., from an oscilloscope or simulation) and want to equalize and analyze it directly:
Load — Import the waveform and define timing (
SampleInterval,SymbolTime)Equalize — Stream through datapath blocks (FFE, CTLE, DFECDR) with
WaveType = "Sample"Analyze — Build an eye diagram with
eyeDiagramSI, extract metrics (eye height, COM, VEC)Decompose jitter — Run
jitter()on the equalized waveform for TJ, RJ, DJ, DDJ, ISI breakdown
DFECDR and DFE require a sample-by-sample for loop in Sample mode; FFE and CTLE accept full vectors. See reference/waveform-processing.md for the Direct Equalization pattern.
IBIS-AMI Model Delivery
When you need compiled models (.ami/.ibs/.dll/.so) for EDA tools or IP delivery:
Export — Call
exportToSimulink(sys)to generate a Simulink model from the frozen designConfigure — Set AMI parameters, IBIS component/pin data, and model type via
IbisAmiManagerorserdes.AMIExportGenerate — Build
.ami/.ibsand compile.dll/.soviaserdes.AMIExportwithexport()Validate — Load compiled DLL/SO with
serdes.AMI, compare against behavioral reference (Init for impulse, GetWave for waveform)Cross-check — The Simulink path (
simwith Rx WaveOut) is the preferred time-domain reference. Compare against: statisticalanalysis(), system objects direct chain, and compiled AMI DLLs. Seereference/simulink-serdes-simulation.mdIterate — Fix discrepancies, re-export, re-validate until all paths agree
AMI Model Types
Choose the model type based on which equalization blocks need to adapt at runtime:
| Type | Init_Returns_Impulse | GetWave_Exists | Use For |
|---|---|---|---|
| Init-Only | true | false | LTI equalization (fixed FFE, CTLE). Supports statistical analysis |
| GetWave-Only | false | true | Time-domain only. No statistical analysis |
| Dual | true | true | Adaptive equalization (DFE, CDR). All analysis types |
Every IBIS-AMI model implements AMI_Init (required), AMI_GetWave (optional), and AMI_Close (required) per the IBIS standard.
Key Classes
| Class | Purpose |
|---|---|
SerdesSystem | Top-level system. Methods: analysis, plotStatEye, plotImpulse, plotPulse, plotAlignedPulse, plotWavePattern, analysisReport, exportToSimulink |
Transmitter | Tx container. Construct: Transmitter('Blocks', {serdes.FFE(...)}) |
Receiver | Rx container. Construct: Receiver('Blocks', {serdes.CTLE(...), serdes.DFECDR(...)}) |
ChannelData | Channel spec. Props: ChannelLossdB, ChannelLossFreq (default 5 GHz — must override to Nyquist), ChannelDifferentialImpedance, or Impulse/dt |
JitterAndNoise | IBIS 7.0 jitter/noise. 4 groups: Tx jitter (Rj/Dj/DCD/Sj), Rx jitter, Rx clock recovery (5 params, active with RxClockMode='clocked', 'convolved', or 'normal'), Rx noise. Values in seconds (default) or UI. See reference/serdes-api-reference.md |
serdes.AMI | Run compiled AMI DLLs/SOs. Call: [waveOut, impulseOut] = ami(waveIn, impulseIn, clockIn) |
serdes.AMIExport | Programmatic AMI export (R2026a+). Methods: export, getExportSettings. Props: ModelTypeTx, DLLFiles, LinuxCrossCompile |
SParameterChannel | S-parameter to impulse response. Handles .s4p through .s16p (multi-port returns Nx(K) matrix: col 1=thru, cols 2+=aggressors). Props: FileName, SampleInterval, StopTime, PortOrder |
eyeDiagramSI | Waveform eye diagram (R2024a+). Step: eyeObj(wave) — no output. Metrics: eyeHeight, eyeWidth, com, vec, margin |
ctlefit | CTLE pole/zero fitter. Import: ctlefit.readcsv. Output: GPZ matrix for serdes.CTLE("Specification", "GPZ Matrix") |
Datapath Blocks
| Block | Role | Mode Values | Key Properties |
|---|---|---|---|
serdes.FFE | Feed-forward equalizer | 0, 1 | TapWeights, TapSpacing, Normalize |
serdes.CTLE | Continuous-time linear EQ | 0, 1, 2 | Specification, DCGain, ACGain, PeakingGain, GPZ |
serdes.DFECDR | DFE + clock recovery | 0, 1, 2 | TapWeights, CDRMode, PhaseDetector, Count |
serdes.DFE | Standalone DFE | 0, 1, 2 | TapWeights, EqualizationGain, EqualizationStep |
serdes.CDR | Standalone CDR | 0, 1 | CDRMode, Count, Step, Sensitivity. Mode is deprecated |
serdes.AGC | Auto gain control | 0, 1 | TargetRMSVoltage, MaxGain, AveragingLength |
serdes.VGA | Variable gain amplifier | 0, 1 | Gain |
serdes.SaturatingAmplifier | Limiting amplifier | 0, 1 | Limit, LinearGain, Specification |
serdes.PassThrough | No-op placeholder | — | — |
Mode values: 0 = Fixed (not exported), 1 = Fixed (exported as AMI parameter), 2 = Adaptive (GetWave). Only CTLE, DFECDR, and DFE support Mode=2.
Set CTLE Specification before setting gain properties — using ACGain with the default spec triggers a warning. GPZ Matrix requires Mode=1 for ConfigSelect to switch rows. See reference/equalization-tuning.md for the 4 specification options.
Patterns
Each reference file includes executable code patterns for its topic. Load the relevant reference before writing code — it contains correct calling conventions, constructor arguments, and property names. See the References table in Conventions below for the full routing map.
Common Mistakes
See reference/common-mistakes.md for 37 documented anti-patterns with wrong/correct code pairs covering API misuse, wrong property names, silent failures, and performance pitfalls.
Conventions
Design
Use
SerdesSystemfor programmatic design;serdesDesignerfor interactive exploration. Always runanalysis/plotStatEyebefore exportingCRITICAL:
ChannelLossFreqdefaults to 5 GHz — always override to Nyquist (1/(2*SymbolTime)). Without this, 15 dB at 5 GHz becomes 40+ dB at Nyquist and the eye appears closed. UseSParameterChannelfor real channelsanalysis()does not auto-optimize FFE taps — use canonical de-emphasis withsum(abs(taps)) ≈ 1.0DFE taps initialized to zero are optimized by the statistical solver automatically
Industry reference designs:
serdesDesigneroropenExample('serdes/PCIe5TransmitterReceiverIBISAMIModelExample'). Seereference/equalization-tuning.mdfor starting-point configurations
Visualization and Metrics
All
SerdesSystemplot methods (plotStatEye,plotImpulse,plotPulse,plotAlignedPulse,plotWavePattern) render into the current axes — usetiledlayout/nexttileorsubplotfor multi-panel layoutseyeDiagramSI(R2024a+) for waveform eye diagrams;jitter(R2024b+) for jitter decompositionDFECDR/DFE in
"Sample"WaveType require scalar (sample-by-sample) input; FFE/CTLE accept full vectorsWhen generating PRBS waveforms via
pulse2wave, ask the user for PRBS order and symbol count — default PRBS-10 (1023 symbols) if unspecifiedUse
serdes.utilities.SignalIntegrityColorMap(nothot/parula) forpulse2stateyeplots. For compliance, usemargin(eyeObj, eyeMask)See
reference/visualization-and-metrics.mdfor all plot methods, metrics fields/units, eyeDiagramSI, and jitter
AMI Export and Validation
Use
serdes.AMIExportwithexport()for programmatic AMI generation — notslbuild(legacy, R2025b and earlier only)Validate compiled DLLs/SOs with
serdes.AMIbefore sending to EDA tools — both Init (impulse correlation) and GetWave (waveform chain)Simulink is the preferred time-domain path —
sim()with Rx WaveOut is the ground truth for adaptive systems. Compare against system objects chain and compiled AMI DLLs as cross-checks. Use the same PRBS stimulus across all time-domain pathsAMI export parameters on Simulink blocks use
*AMIsuffix ('ModeAMI','TapWeightsAMI'); model-level settings go throughIbisAmiManagerorserdes.AMIExportNo compiled DLLs/SOs ship with the toolbox. Cross-compile for Linux
.soviaserdes.utilities.createCrossCompiler
Script-First Workflow
For design, analysis, or sweep tasks — write code to .m files on disk, not inline MCP snippets. For quick one-off checks, inline evaluate_matlab_code is fine.
Create a
.mfile (e.g.,serdes_pam4_design.m), run viarun_matlab_file, iterate by editing and re-runningDeliver a polished script —
%% Parametersblock at top,%% Sectionheaders, summaryfprintfat end
References
| Load when... | Reference |
|---|---|
Building or modifying a SerdesSystem | reference/serdes-api-reference.md |
| Debugging wrong API names or silent failures | reference/common-mistakes.md |
| Working with S-parameter files or crosstalk | reference/channel-modeling.md |
| Tuning CTLE, FFE, DFE, or fitting transfer functions | reference/equalization-tuning.md |
| Sweeping parameters or running GA optimization | reference/optimization.md |
| Plotting eyes, reading metrics, or decomposing jitter | reference/visualization-and-metrics.md |
| Equalizing captured or imported waveforms directly | reference/waveform-processing.md |
| Exporting to Simulink, compiling AMI DLLs, or validating AMI models | reference/programmatic-ami-generation.md |
Scripting Simulink simulations or parsim sweeps | reference/simulink-serdes-simulation.md |
| Building custom datapath blocks | reference/custom-datapath-blocks.md |
| Looking up utility functions (SNR, ICN, resample) | reference/serdes-utilities.md |
Copyright 2026 The MathWorks, Inc.
Files
- ATTRIBUTION.mdAdded by AutoGineer1.0 KiB
- LICENSELicence file added by AutoGineer1.4 KiB
- SKILL.md16.4 KiB
- manifest.yaml1000 B
- reference/channel-modeling.md7.8 KiB
- reference/common-mistakes.md28.5 KiB
- reference/custom-datapath-blocks.md12.8 KiB
- reference/equalization-tuning.md11.4 KiB
- reference/optimization.md9.0 KiB
- reference/programmatic-ami-generation.md25.4 KiB
- reference/serdes-api-reference.md28.4 KiB
- reference/serdes-utilities.md10.4 KiB
- reference/simulink-serdes-simulation.md19.4 KiB
- reference/visualization-and-metrics.md20.0 KiB
- reference/waveform-processing.md7.8 KiB
reference/custom-datapath-blocks.md
Custom Datapath Blocks for SerDes Toolbox
Create custom equalization or signal-processing blocks that integrate into the
SerDes Toolbox datapath alongside built-in blocks like serdes.FFE, serdes.CTLE,
and serdes.DFECDR.
When to Use
The built-in blocks don't cover your equalization algorithm
You need a custom Tx or Rx processing stage (e.g., nonlinear equalizer, custom AGC)
You want your custom block to export AMI parameters and compile into a DLL/SO
Architecture
Custom datapath blocks inherit from serdes.SerdesAbstractSystemObject, which
itself inherits from matlab.System. This base class provides the SerDes-specific
interface that the toolbox framework expects.
Class Hierarchy
matlab.System
└── serdes.SerdesAbstractSystemObject ← inherit from this
├── serdes.FFE (built-in examples)
├── serdes.CTLE
├── serdes.DFECDR
└── YourCustomBlock (your block)Required Interface
Properties
Inherited from base class (do not redefine):
| Property | Type | Purpose |
|---|---|---|
SymbolTime | double | Symbol duration (s) — set by framework |
SampleInterval | double | Sample interval (s) — set by framework |
Modulation | integer | Modulation levels (2=NRZ through 16) — set by framework |
Must define on your subclass:
| Property | Type | Attributes | Purpose |
|---|---|---|---|
Mode | integer | public | 0 = Fixed (not exported), 1 = Fixed (exported), 2 = Adaptive |
WaveType | char | public | 'Impulse' or 'Sample' — set by framework, drives stepImpl |
IsLinear | logical | Hidden, SetAccess = immutable | true if block is linear. Enables statistical (Init) analysis |
IsTimeInvariant | logical | Hidden, SetAccess = immutable | true if block parameters do not adapt over time |
Methods
| Method | Access | Required | Purpose |
|---|---|---|---|
stepImpl(obj, x) | protected | Yes | Core algorithm. Must handle both WaveType values |
resetImpl(obj) | protected | Yes | Reset internal states |
getAMIParameters(obj) | public | Yes (abstract) | Return AMI parameter definitions for .ami file |
getAMIInputNames(obj) | public | Yes (abstract) | Return input port names for AMI |
getAMIOutputNames(obj) | public | Yes (abstract) | Return output port names for AMI |
Class Template
classdef (StrictDefaults) CustomEQ < serdes.SerdesAbstractSystemObject
%CustomEQ Custom equalizer for SerDes datapath.
properties(Nontunable)
NumTaps (1,1) {mustBeInteger, mustBePositive} = 3
end
properties
TapWeights (1,:) double = [0 1 0]
Mode (1,1) {mustBeMember(Mode, [0 1 2])} = 1
end
properties(DiscreteState)
Buffer
end
properties(Access = private)
pSamplesPerSymbol
end
% WaveType: set by Simulink framework; set manually in standalone MATLAB
properties
WaveType (1,:) char {mustBeMember(WaveType, {'Impulse','Sample'})} = 'Sample'
end
% IsLinear/IsTimeInvariant: immutable — set once in constructor, cannot change
% IMPORTANT: no size spec or validators on inherited abstract properties
properties(Hidden, SetAccess = immutable)
IsLinear
IsTimeInvariant
end
methods
function obj = CustomEQ(varargin)
% Set immutable properties before setProperties
obj.IsLinear = true;
obj.IsTimeInvariant = true;
setProperties(obj, nargin, varargin{:});
end
end
methods (Access = protected)
function setupImpl(obj, x)
obj.pSamplesPerSymbol = round(obj.SymbolTime / obj.SampleInterval);
end
function y = stepImpl(obj, x)
switch obj.WaveType
case "Impulse"
% Init path: convolve with impulse response
% Input x is the channel impulse response (column vector)
h = upsample(obj.TapWeights(:), obj.pSamplesPerSymbol);
y = conv(x, h);
y = y(1:numel(x)); % truncate to input length
case "Sample"
% GetWave path: process time-domain samples
% Input x is a block of waveform samples
nTaps = obj.NumTaps;
nSamples = numel(x);
y = zeros(size(x));
for k = 1:nSamples
% Shift buffer
obj.Buffer = [x(k); obj.Buffer(1:end-1)];
% Apply FIR
y(k) = obj.TapWeights * obj.Buffer(1:nTaps);
end
end
end
function resetImpl(obj)
obj.Buffer = zeros(obj.NumTaps, 1);
end
end
% getAMI* methods are public (abstract on base class)
methods
function params = getAMIParameters(obj)
params = struct();
params.TapWeights = struct(...
'Usage', 'InOut', ...
'Type', 'Float', ...
'Default', obj.TapWeights, ...
'Description', 'FIR tap weights');
end
function names = getAMIInputNames(~)
names = {"in"};
end
function names = getAMIOutputNames(~)
names = {"out"};
end
end
methods (Access = protected, Static)
function simMode = getSimulateUsingImpl
simMode = "Code generation";
end
end
endWaveType: The Critical Dispatch
The WaveType property is the key to dual-mode (Init + GetWave) operation:
| WaveType | When Set | Input x Contains | Algorithm Should |
|---|---|---|---|
"Impulse" | Init path (statistical analysis) | Channel impulse response | Apply LTI transfer function via convolution |
"Sample" | GetWave path (time-domain) | Block of waveform samples | Process samples, update adaptive state |
Critical: Simulink sets WaveType automatically before each call. In standalone
MATLAB usage, you must set it explicitly:
eq = CustomEQ('TapWeights', [0.2 0.6 0.2]);
eq.SymbolTime = 100e-12;
eq.SampleInterval = 6.25e-12;
% For impulse processing
eq.WaveType = "Impulse";
yImpulse = eq(channelImpulse);
% For sample processing (reset first)
release(eq);
eq.WaveType = "Sample";
ySamples = eq(waveformBlock);Integration Workflow
Option A: Replace PassThrough in SerdesSystem
Design the system with
serdes.PassThroughas a placeholderExport to Simulink via
exportToSimulinkIn the Simulink model, replace the PassThrough MATLAB System block with your custom block
% Step 1: Design with placeholder
sys = SerdesSystem(...
'RxModel', Receiver('Blocks', ...
{serdes.CTLE, serdes.PassThrough, serdes.DFECDR}), ...
'SymbolTime', 100e-12, ...
'SamplesPerSymbol', 16);
% Step 2: Export
exportToSimulink(sys);
% Step 3: Replace PassThrough block in Simulink
% Open the model, find the PassThrough MATLAB System block,
% and change its System object name to 'CustomEQ'
% Or programmatically:
mdl = 'untitled';
blk = [mdl '/Rx/PassThrough'];
set_param(blk, 'System', 'CustomEQ');Option B: Direct Use in MATLAB (Without Simulink)
% Create and configure
eq = CustomEQ('NumTaps', 5, 'TapWeights', [-0.1 -0.05 0.8 -0.05 -0.1]);
eq.SymbolTime = 100e-12;
eq.SampleInterval = 6.25e-12;
% Process impulse (Init path)
eq.WaveType = "Impulse";
impulse = zeros(1024, 1);
impulse(1) = 1;
yInit = eq(impulse);
% Convert to pulse and analyze
pulse = impulse2pulse(yInit, 16, 6.25e-12);
metrics = optPulseMetric(pulse, 16, 6.25e-12, 1e-6);Example: Saturating Amplifier
The built-in serdes.SaturatingAmplifier provides a basic limiter. Here is how
to use it as a custom Rx stage for signal conditioning before DFE:
% Built-in saturating amplifier — no custom class needed
amp = serdes.SaturatingAmplifier;
amp.Limit = 0.4; % clip at ±400 mV
amp.LinearGain = 2; % 2x gain in linear region
amp.Specification = "Limit"; % "Limit" or "LinearGain"
amp.Mode = 1; % export as AMI parameter
% Place between CTLE and DFECDR in the Rx chain
sys = SerdesSystem(...
'RxModel', Receiver('Blocks', {ctle, amp, dfecdr}), ...
'TxModel', Transmitter('Blocks', {ffe}), ...
'SymbolTime', symbolTime, 'SamplesPerSymbol', 16);When to Write a Custom Block Instead
Use serdes.SaturatingAmplifier for simple clipping/limiting. Write a custom
serdes.SerdesAbstractSystemObject subclass when you need:
Nonstandard transfer functions (e.g., polynomial, piecewise)
State-dependent behavior (e.g., AGC with custom adaptation law)
Multiple interacting parameters not covered by built-in blocks
Common Mistakes
1. Inheriting from matlab.System Instead of serdes.SerdesAbstractSystemObject
% WRONG — won't integrate with SerDes framework
classdef CustomEQ < matlab.System
% CORRECT — inherits SerDes interface
classdef CustomEQ < serdes.SerdesAbstractSystemObject2. Not Handling Both WaveType Values
% WRONG — only handles samples, Init path gives wrong results
function y = stepImpl(obj, x)
y = filter(obj.TapWeights, 1, x, obj.Buffer);
end
% CORRECT — dispatch on WaveType
function y = stepImpl(obj, x)
switch obj.WaveType
case "Impulse"
y = conv(x, upsample(obj.TapWeights(:), obj.pSamplesPerSymbol));
y = y(1:numel(x));
case "Sample"
y = filter(obj.TapWeights, 1, x, obj.Buffer);
end
end3. Confusing IsLinear with IsTimeInvariant for Adaptive Blocks
% WRONG — adaptive linear equalizer marked as time-invariant
obj.IsLinear = true;
obj.IsTimeInvariant = true; % NO — adaptation means time-varying
% CORRECT — adaptive LINEAR blocks (DFE, adaptive FIR):
obj.IsLinear = true; % YES — it's a linear filter (Init uses optimal taps)
obj.IsTimeInvariant = false; % NO — taps change during GetWave
% For truly NONLINEAR blocks (limiter, decision feedback with slicing):
obj.IsLinear = false; % Disables statistical (Init) analysis
obj.IsTimeInvariant = false;Note: serdes.DFECDR uses IsLinear=true, IsTimeInvariant=false. The Init
path computes optimal DFE taps and applies them as a linear operation.
Adaptation (time-varying behavior) only matters during GetWave.
4. Forgetting to Set WaveType in Standalone MATLAB
% WRONG — WaveType defaults to "Sample", impulse processing is incorrect
eq = CustomEQ;
eq.SymbolTime = 100e-12;
eq.SampleInterval = 6.25e-12;
y = eq(impulseResponse); % Processes as samples, not impulse
% CORRECT — set WaveType before calling
eq.WaveType = "Impulse";
y = eq(impulseResponse); % Correct impulse-domain processing5. Impulse Convolution Boundary Effects
Custom blocks using conv(x, h) truncated to y(1:numel(x)) may produce
small boundary differences compared to built-in blocks like serdes.FFE.
The built-in blocks use optimized internal convolution that handles edge
samples differently. For most practical purposes the difference is negligible
(< 1e-15 in the main lobe), but it can appear in the trailing edge of the
impulse response. This is expected — not a bug in your block.
6. strjoin Fails on getAMIInputNames / getAMIOutputNames
getAMIInputNames and getAMIOutputNames return cell arrays of strings
(not char vectors). strjoin rejects this — wrap with string() first:
% WRONG — strjoin errors on cell of strings
inNames = eq.getAMIInputNames();
fprintf("%s\n", strjoin(inNames, ", ")); % ERROR: InvalidCellType
% CORRECT — convert to string array
fprintf("%s\n", strjoin(string(inNames), ", "));7. GetWave Produces NaN/Inf from Uninitialized Persistent Variables
Custom blocks using persistent variables in stepImpl for GetWave (Sample
mode) must initialize them in setupImpl or resetImpl. Uninitialized
persistent variables default to [], and arithmetic on [] propagates NaN/Inf
through the entire waveform. The DLL compiles and loads successfully — the
failure only appears at runtime as corrupted output.
% WRONG — persistent not initialized, first GetWave call produces NaN
function y = stepImpl(obj, x)
persistent prevSample
y = x - prevSample; % prevSample is [] on first call → NaN
prevSample = x;
end
% CORRECT — initialize in resetImpl
function resetImpl(obj)
obj.PrevSample = 0; % use DiscreteState property instead
endFile Placement
Place your custom System object .m file on the MATLAB path. For Simulink
integration, the file must be accessible when the model is opened and built.
Recommended location: alongside the Simulink model, or in a project src/ folder
added to the path via startup.m.
Copyright 2026 The MathWorks, Inc.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- MathWorks
- Publisher
- MathWorks (Official)
- Source
- matlab/matlab-agentic-toolkit · skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems · commit 2a7f215
- Licence
- BSD 2-Clause License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE.md)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by MathWorks or MathWorks.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download matlab-model-serdes-systems.zip