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matlab-model-serdes-systems

Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox.

Install / Use

npx skills add matlab/matlab-agentic-toolkit --skill matlab-model-serdes-systems

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About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Supported Platforms

Universal

Our assessment of matlab-model-serdes-systems

matlab-model-serdes-systems scores 86/100 on our quality scale, 2058th of 4,646 Development & Engineering skills we index (top 45%).

Its SKILL.md is 16 KB long, well organised into 23 sections and no code examples: a thorough specification that gives an agent plenty to work with.

With 1,098 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
13/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 18 days ago, so matlab-model-serdes-systems is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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Frequently asked questions

How do I install matlab-model-serdes-systems?
Run npx skills add matlab/matlab-agentic-toolkit --skill matlab-model-serdes-systems. The install tabs above show the steps for each supported agent.
Which AI agents does matlab-model-serdes-systems work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
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It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is matlab-model-serdes-systems still maintained?
The repository was last updated 18 days ago, so matlab-model-serdes-systems is actively maintained.

name: matlab-model-serdes-systems description: > Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox. Design NRZ and PAM-N links (PAM3 through PAM16) — explore equalization architectures (FFE, CTLE, DFE), sweep or optimize parameters with genetic algorithms, and characterize channels from loss models, S-parameter files, or crosstalk scenarios. Process captured waveforms through equalization chains, build eye diagrams, and decompose jitter. Deliver IBIS-AMI models for Tx, Rx, Redriver, or Retimer by exporting to Simulink and compiling .ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"

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/.so
  • Scripting 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/RxModel are Transmitter/Receiver objects — not cell arrays. Construct with Transmitter('Blocks', {block1, block2}). Transmitter requires single-quoted property names — Transmitter("Blocks", ...) throws an ismember error. Receiver and all other classes accept double quotes
  • Signal conversion functions require column vectors — impulse2pulse, pulse2stateye, etc. error on row vectors
  • Include AnalogModel and JitterAndNoise for realistic results — bare Transmitter/Receiver without analog models produce optimistic COM (1-2 dB higher). See reference/equalization-tuning.md for parameter guidance (rise time, parasitic C, termination R)

Equalization

  • Set WaveType explicitly 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. After analysis(), sys.RxModel.Blocks{k}.TapWeights still 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 outparams with Mode=1 for instant convergence, or use Mode=2 with 10x EqualizationGain (9.6e-04) for self-converging chains
  • Set Modulation on 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.EW is in picoseconds (already scaled) — do NOT multiply by 1e12. EH is 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 using filter() for time-domain convolution, multiply by dt: filter(impulse * dt, 1, wave). Without scaling, amplitudes blow up by ~10^11
  • pulse2wave operates 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.AMI runner and the AMI Simulink block need both SerDes Toolbox and Signal Integrity Toolbox
  • AMI GetWave: call in a chunked loop — serdes.AMI passes BlockSize (default 1024) to AMI_GetWave, so only BlockSize samples are processed per call. You must call the object in a for loop with BlockSize-length chunks. State is preserved between calls via the DLL memory handle
  • AMI GetWave: set SkipFirstBlock = false when calling from MATLAB — the default (true) is for Simulink's internal signal buffering and causes the first block to pass through unprocessed
  • AMI Init: RowSize must match impulse length — serdes.AMI crashes MATLAB (process termination, no error) if RowSize doesn't match numel(impulse)
  • AMI generation requires Simulink model — use IbisAmiManager GUI or serdes.AMIExport with export() 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.

  1. Design — Create a SerdesSystem with Tx/Rx blocks and channel (loss model or S-parameters)
  2. Analyze — Run analysis for statistical results, plotStatEye for eye diagrams, analysisReport for metrics
  3. Sweep — Vary channel loss, FFE taps, CTLE gain, DFE taps, or jitter to map the design space
  4. Compare — Evaluate architectures (FFE-only vs FFE+CTLE vs FFE+CTLE+DFE) using COM, eye height, eye width
  5. 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:

  1. Load — Import the waveform and define timing (SampleInterval, SymbolTime)
  2. Equalize — Stream through datapath blocks (FFE, CTLE, DFECDR) with WaveType = "Sample"
  3. Analyze — Build an eye diagram with eyeDiagramSI, extract metrics (eye height, COM, VEC)
  4. 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:

  1. Export — Call exportToSimulink(sys) to generate a Simulink model from the frozen design
  2. Configure — Set AMI parameters, IBIS component/pin data, and model type via IbisAmiManager or serdes.AMIExport
  3. Generate — Build .ami/.ibs and compile .dll/.so via serdes.AMIExport with export()
  4. Validate — Load compiled DLL/SO with serdes.AMI, compare against behavioral reference (Init for impulse, GetWave for waveform)
  5. Cross-check — The Simulink path (sim with Rx WaveOut) is the preferred time-domain reference. Compare against: statistical analysis(), system objects direct chain, and compiled AMI DLLs. See reference/simulink-serdes-simulation.md
  6. Iterate — 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 warn

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars1.1k
CategoryDevelopment
Updated18d ago
Forks134

Languages

MATLAB

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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