Matlab Model Serdes SystemsSAFE

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---
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)`
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SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

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Gates applied: no_behavioural_pass.