Matlab Model Serdes Systems
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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://mp-staging.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/serdes-utilities.md
SerDes Utility Functions
Utility functions in the serdes.utilities namespace for signal quality
metrics, signal manipulation, CTLE pole/zero generation, and formatting.
All functions are called as serdes.utilities.<FunctionName>(...).
Signal Quality Metrics
SER (Symbol Error Rate)
Class that calculates symbol error rate from stimulus and equalized waveforms.
ser = serdes.utilities.SER;
ser.SymbolTime = symbolTime;
ser.SampleInterval = dt;
ser.Modulation = modulation; % 2 = NRZ, 4 = PAM4, etc.
ser.IgnoreSymbols = 100; % skip CDR convergence period
% Inputs: stimulus (1 sample/symbol), equalized wave, clock, thresholds
calculateSER(ser, stimulusSymbols, equalizedWave, clock, thresholds);
% Read results
fprintf("SER = %g\n", ser.SymbolErrorRate);
plotComparison(ser); % overlay stimulus vs latched symbolsProperties:
| Property | Description |
|---|---|
SymbolTime | Symbol period (seconds) |
SampleInterval | Sample interval (seconds) |
Modulation | Number of symbol levels (2, 3, 4, ...) |
IgnoreSymbols | Symbols to skip before counting errors |
SymbolErrorRate | Read-only. Computed SER after calculateSER |
Critical: The clock input must come from pulseRecoverClock or a CDR
object — do not use arbitrary sample indices. The clock waveform has
rising/falling edges that signal the latch point.
SNR (Signal-to-Noise Ratio)
Computes SNR from a pulse response. Returns a ratio, not dB.
m = serdes.utilities.SNR(pulse, samplesPerSymbol);
fprintf("SNR = %g (%.1f dB)\n", m, 10*log10(m));The algorithm finds the energy under the cursor portion of the pulse and
divides by the energy of the remainder (ISI). Uses pulseRecoverClock
internally to find the cursor location.
Input: pulse — column vector pulse response, samplesPerSymbol — integer.
Output: m — SNR as a linear ratio. Apply 10*log10(m) for dB.
WaveEyeHeight
Finds the maximum eye height of a symbol-rate waveform by folding.
maxEH = serdes.utilities.WaveEyeHeight(waveIn, samplesPerSymbol);
[maxEH, upperBound, lowerBound] = serdes.utilities.WaveEyeHeight(waveIn, samplesPerSymbol);Inputs:
waveIn— time-domain waveform (column vector)samplesPerSymbol— integer SPS
Outputs:
maxEH— maximum eye height (volts). ReturnsNaNif waveform too shortupperBound— upper eye boundary voltagelowerBound— lower eye boundary voltage
The function folds the waveform at symbol boundaries and measures the
vertical opening at each sample phase. The output is a vector (one
value per sample phase within a symbol) — use max(maxEH) for the best
phase. For jitter-aware eye height, use eyeDiagramSI instead
(see reference/visualization-and-metrics.md).
icn (Integrated Crosstalk Noise)
Computes integrated crosstalk noise per OIF-CEI-04.0 Section 12.2.1.2.
Returns volts RMS (consistent with ChannelData.FEXTICN/NEXTICN).
% Basic: frequency vector, crosstalk S-parameter matrix, baud rate
Y = serdes.utilities.icn(f, Sxt, fb);
% Full: with aggressor amplitude (Vpp), rise time (s), start frequency (Hz)
Y = serdes.utilities.icn(f, Sxt, fb, A, Tr, fStart);
% Multi-output: MDXT = multi-disturber crosstalk, W = weighting function
[Y, MDXT, W] = serdes.utilities.icn(f, Sxt, fb);Inputs:
| Parameter | Description |
|---|---|
f | Frequency vector (Hz), same length as Sxt |
Sxt | Crosstalk S-parameter column matrix [Xt1, Xt2, ...] |
fb | Baud frequency (Hz). For NRZ: 1 / (2 * SymbolTime) |
A | (Optional) Aggressor Vpp differential amplitude (V) |
Tr | (Optional) Aggressor 20-80% rise time (s) |
fStart | (Optional) Integration start frequency (Hz) |
Multiple crosstalk waveforms are power-summed to yield multi-disturber crosstalk, then windowed by the weighting function.
CTLE Pole/Zero Generation
poleZeroDefine
Generates CTLE poles and zeros from peaking specifications. Three calling conventions (any two of DCGain, ACGain, PeakingGain plus PeakingFrequency):
% Convention 1: DCGain + PeakingGain
[G, P, Z] = serdes.utilities.poleZeroDefine(...
'PeakingFrequency', 7e9, 'DCGain', -6, 'PeakingGain', 6);
% Convention 2: DCGain + ACGain (PeakingGain = ACGain - DCGain)
[G, P, Z] = serdes.utilities.poleZeroDefine(...
'PeakingFrequency', 7e9, 'DCGain', -6, 'ACGain', 0);
% Convention 3: ACGain + PeakingGain (DCGain = ACGain - PeakingGain)
[G, P, Z] = serdes.utilities.poleZeroDefine(...
'PeakingFrequency', 7e9, 'PeakingGain', 6, 'ACGain', 0);Output forms:
| Syntax | Output |
|---|---|
[G, P, Z] = poleZeroDefine(...) | Separate: gain (dB), poles (Hz), zeros (Hz) |
GPZ = poleZeroDefine(...) | Single output: [G P1 Z1 P2; ...] matrix for serdes.CTLE |
poleZeroDefine(...) | No output: plots magnitude and phase |
Vector inputs: PeakingFrequency, DCGain, PeakingGain, ACGain can
be vectors (same length or scalar) to generate multiple CTLE configurations
at once. The single-output GPZ matrix then has one row per configuration.
Usage with CTLE:
GPZ = serdes.utilities.poleZeroDefine(...
'PeakingFrequency', 7e9, 'DCGain', [-8 -6 -4 -2 0], 'ACGain', 0);
ctle = serdes.CTLE('Specification', "GPZ Matrix", 'GPZ', GPZ);Signal Manipulation
resampleImpulse
Resamples an impulse response to a new sample interval.
Y = serdes.utilities.resampleImpulse(X, dtIn, dtOut, normalize);All four arguments are required (including
normalize)Upsampling: spline interpolation
Downsampling: raised-cosine anti-aliasing filter first, then decimation
normalize— set to0to skip normalization,1to normalizeXmust be a column matrix (each column is an impulse response)
Warning: Assumes samples before and after X are zero. Large deviations
from zero at endpoints can cause inaccuracies at boundaries.
shiftPulse
Circular-shifts a pulse response so the cursor aligns to the center of a folded eye diagram.
[pulse, cursorNdx, shift1] = serdes.utilities.shiftPulse(pulse, N);
[pulse, cursorNdx, shift1] = serdes.utilities.shiftPulse(pulse, N, ClockIndex);N— samples per symbolClockIndex— (optional) directly specify cursor position instead of using the hula-hoop algorithmcursorNdx— recovered clock location in symbol unitsshift1— number of samples shifted
SoftClipper
Creates a cubic soft-clipper voltage transfer curve for serdes.SaturatingAmplifier.
VinVout = serdes.utilities.SoftClipper(linearGain, limit);
VinVout = serdes.utilities.SoftClipper(linearGain, limit, npts);
VinVout = serdes.utilities.SoftClipper(linearGain, limit, x);linearGain— small-signal gain (V/V)limit— clipping voltage (V)npts— number of points (default: 63)x— custom Vin vector (overrides npts)Output:
[Nx2]matrix[Vin, Vout]
Usage with SaturatingAmplifier:
VinVout = serdes.utilities.SoftClipper(2, 0.8);
amp = serdes.SaturatingAmplifier('Specification', "VinVout", ...
'VinVout', VinVout);floatingTaps
Applies floating tap group constraints to DFE tap vectors.
taps = serdes.utilities.floatingTaps(optimizedTaps, fixedTaps, groups, groupSize);Searches left-to-right for the position where each floating tap group has the largest sum. Fixed leading taps (pre-taps + main) are excluded from the search.
optimizedTaps— vector of tap weights before constraintsfixedTaps— number of leading taps to skipgroups— number of floating tap groupsgroupSize— size of each group
IBIS Rise Time Conversion
dt2Trf / trf2dt
Convert between IBIS ramp dV/dt rise time and LTI 20-80% rise time.
Trf = serdes.utilities.dt2Trf(dt, R, C, rLoad);
dt = serdes.utilities.trf2dt(Trf, R, C, rLoad);dt— IBIS ramp rise time (fromdV/dt_rrecord)Trf— 20-80% LTI rise timeR— driver impedance (ohms)C— parasitic capacitance (F)rLoad— load impedance (ohms)
Based on M. Steinberger's IBISRiseTime derivation.
Formatting and Conversion
db
Converts linear magnitude to decibels: 20*log10(abs(x)). Code-generation
compatible.
y = serdes.utilities.db(x);
% Equivalent to: y = 20*log10(abs(x))num2prefix
Converts a numeric value to a string with SI prefix.
str = serdes.utilities.num2prefix(100e-12); % "100 ps"
str = serdes.utilities.num2prefix(14.125e9, "Hz"); % "14.125 GHz"
[str, prefixStr, Y] = serdes.utilities.num2prefix(X, UNIT);Outputs:
str— formatted string with value and prefix+unitprefixStr— prefix and unit string only (e.g.,"ps","GHz")Y— scale factor used (e.g.,1e12for pico)
Prefix range: yocto (y, 10^-24) through Tera (T, 10^12).
SignalIntegrityColorMap
Standard colormap for statistical eye diagrams (not a utility function but
in the serdes.utilities namespace):
cmap = serdes.utilities.SignalIntegrityColorMap;
colormap(cmap);Common Mistakes
1. SNR Returns Ratio, Not dB
% WRONG — treating SNR output as dB
m = serdes.utilities.SNR(pulse, 16);
fprintf("SNR = %.1f dB\n", m); % Incorrect — m is a linear ratio
% CORRECT — convert to dB manually
fprintf("SNR = %.1f dB\n", 10*log10(m));2. icn Returns Volts RMS, Not dB
% WRONG — treating icn output as dB
icnVal = serdes.utilities.icn(f, Sxt, fb);
fprintf("ICN = %.1f dB\n", icnVal); % Incorrect — icnVal is in V RMS
% CORRECT — display in mV RMS (consistent with ChannelData.FEXTICN)
fprintf("ICN = %.2f mV RMS\n", icnVal * 1e3);3. resampleImpulse Requires Column Matrix and normalize Argument
% WRONG — row vector input and missing normalize argument
impulse = zeros(1, 128);
Y = serdes.utilities.resampleImpulse(impulse, 1e-12, 6.25e-12); % Error
% CORRECT — column vector with normalize argument
impulse = zeros(128, 1);
Y = serdes.utilities.resampleImpulse(impulse, 1e-12, 6.25e-12, 0);4. SER Needs Clock from pulseRecoverClock
% WRONG — using arbitrary sample indices as clock
clock = (0:N-1) * dt; % Not a valid clock waveform
% CORRECT — use pulseRecoverClock or CDR output
clockIdx = pulseRecoverClock(pulse, samplesPerSymbol);
% Or use serdes.CDR to generate clock waveform with rising edgesCopyright 2026 The MathWorks, Inc.
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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
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