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Matlab Model Serdes Systems

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From the author

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.
— the description by MathWorks

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

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/matlab/matlab-model-serdes-systems/download
  2. Unzip 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/.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)

  • 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:

TypeInit_Returns_ImpulseGetWave_ExistsUse For
Init-OnlytruefalseLTI equalization (fixed FFE, CTLE). Supports statistical analysis
GetWave-OnlyfalsetrueTime-domain only. No statistical analysis
DualtruetrueAdaptive 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

ClassPurpose
SerdesSystemTop-level system. Methods: analysis, plotStatEye, plotImpulse, plotPulse, plotAlignedPulse, plotWavePattern, analysisReport, exportToSimulink
TransmitterTx container. Construct: Transmitter('Blocks', {serdes.FFE(...)})
ReceiverRx container. Construct: Receiver('Blocks', {serdes.CTLE(...), serdes.DFECDR(...)})
ChannelDataChannel spec. Props: ChannelLossdB, ChannelLossFreq (default 5 GHz — must override to Nyquist), ChannelDifferentialImpedance, or Impulse/dt
JitterAndNoiseIBIS 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.AMIRun compiled AMI DLLs/SOs. Call: [waveOut, impulseOut] = ami(waveIn, impulseIn, clockIn)
serdes.AMIExportProgrammatic AMI export (R2026a+). Methods: export, getExportSettings. Props: ModelTypeTx, DLLFiles, LinuxCrossCompile
SParameterChannelS-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
eyeDiagramSIWaveform eye diagram (R2024a+). Step: eyeObj(wave) — no output. Metrics: eyeHeight, eyeWidth, com, vec, margin
ctlefitCTLE pole/zero fitter. Import: ctlefit.readcsv. Output: GPZ matrix for serdes.CTLE("Specification", "GPZ Matrix")
Datapath Blocks
BlockRoleMode ValuesKey Properties
serdes.FFEFeed-forward equalizer0, 1TapWeights, TapSpacing, Normalize
serdes.CTLEContinuous-time linear EQ0, 1, 2Specification, DCGain, ACGain, PeakingGain, GPZ
serdes.DFECDRDFE + clock recovery0, 1, 2TapWeights, CDRMode, PhaseDetector, Count
serdes.DFEStandalone DFE0, 1, 2TapWeights, EqualizationGain, EqualizationStep
serdes.CDRStandalone CDR0, 1CDRMode, Count, Step, Sensitivity. Mode is deprecated
serdes.AGCAuto gain control0, 1TargetRMSVoltage, MaxGain, AveragingLength
serdes.VGAVariable gain amplifier0, 1Gain
serdes.SaturatingAmplifierLimiting amplifier0, 1Limit, LinearGain, Specification
serdes.PassThroughNo-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 SerdesSystem for programmatic design; serdesDesigner for interactive exploration. Always run analysis/plotStatEye before exporting

  • CRITICAL: ChannelLossFreq defaults 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. Use SParameterChannel for real channels

  • analysis() does not auto-optimize FFE taps — use canonical de-emphasis with sum(abs(taps)) ≈ 1.0

  • DFE taps initialized to zero are optimized by the statistical solver automatically

  • Industry reference designs: serdesDesigner or openExample('serdes/PCIe5TransmitterReceiverIBISAMIModelExample'). See reference/equalization-tuning.md for starting-point configurations

Visualization and Metrics
  • All SerdesSystem plot methods (plotStatEye, plotImpulse, plotPulse, plotAlignedPulse, plotWavePattern) render into the current axes — use tiledlayout/nexttile or subplot for multi-panel layouts

  • eyeDiagramSI (R2024a+) for waveform eye diagrams; jitter (R2024b+) for jitter decomposition

  • DFECDR/DFE in "Sample" WaveType require scalar (sample-by-sample) input; FFE/CTLE accept full vectors

  • When generating PRBS waveforms via pulse2wave, ask the user for PRBS order and symbol count — default PRBS-10 (1023 symbols) if unspecified

  • Use serdes.utilities.SignalIntegrityColorMap (not hot/parula) for pulse2stateye plots. For compliance, use margin(eyeObj, eyeMask)

  • See reference/visualization-and-metrics.md for all plot methods, metrics fields/units, eyeDiagramSI, and jitter

AMI Export and Validation
  • Use serdes.AMIExport with export() for programmatic AMI generation — not slbuild (legacy, R2025b and earlier only)

  • Validate compiled DLLs/SOs with serdes.AMI before 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 paths

  • AMI export parameters on Simulink blocks use *AMI suffix ('ModeAMI', 'TapWeightsAMI'); model-level settings go through IbisAmiManager or serdes.AMIExport

  • No compiled DLLs/SOs ship with the toolbox. Cross-compile for Linux .so via serdes.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.

  1. Create a .m file (e.g., serdes_pam4_design.m), run via run_matlab_file, iterate by editing and re-running

  2. Deliver a polished script — %% Parameters block at top, %% Section headers, summary fprintf at end

References
Load when...Reference
Building or modifying a SerdesSystemreference/serdes-api-reference.md
Debugging wrong API names or silent failuresreference/common-mistakes.md
Working with S-parameter files or crosstalkreference/channel-modeling.md
Tuning CTLE, FFE, DFE, or fitting transfer functionsreference/equalization-tuning.md
Sweeping parameters or running GA optimizationreference/optimization.md
Plotting eyes, reading metrics, or decomposing jitterreference/visualization-and-metrics.md
Equalizing captured or imported waveforms directlyreference/waveform-processing.md
Exporting to Simulink, compiling AMI DLLs, or validating AMI modelsreference/programmatic-ami-generation.md
Scripting Simulink simulations or parsim sweepsreference/simulink-serdes-simulation.md
Building custom datapath blocksreference/custom-datapath-blocks.md
Looking up utility functions (SNR, ICN, resample)reference/serdes-utilities.md

Files

reference/equalization-tuning.md

Equalization Tuning

CTLE Configuration via poleZeroDefine

serdes.utilities.poleZeroDefine generates a GPZ (Gain-Pole-Zero) matrix from DC Gain + AC Gain specifications, suitable for serdes.CTLE in "GPZ Matrix" mode.

% Generate GPZ matrix from gain specifications
nyquistFreq = baudRate / 2;

gpzMatrix = serdes.utilities.poleZeroDefine( ...
    "PeakingFrequency", nyquistFreq, ...
    "DCGain", [0 -1 -2 -3 -4 -5 -6], ...
    "ACGain", 0);
% Returns Nx4 matrix: [Gain(dB) Pole1(Hz) Zero1(Hz) Pole2(Hz)]

ctle = serdes.CTLE("Specification", "GPZ Matrix", ...
    "GPZ", gpzMatrix, ...
    "Mode", 1, ...                       % REQUIRED for ConfigSelect to work
    "ConfigSelect", 3);                  % Select row 3 (0-indexed)

For fitting measured CTLE frequency response data (e.g., from CSV), use ctlefit instead — see reference/serdes-api-reference.md for the ctlefit class API.

CTLE Specification Modes
ModeProperties SetWhen to Use
"DC Gain and Peaking Gain"DCGain, PeakingGainQuick exploration
"DC Gain and AC Gain"DCGain, ACGainDatasheet specs
"AC Gain and Peaking Gain"ACGain, PeakingGainRelative gain control
"GPZ Matrix"GPZ, Mode, ConfigSelectMulti-config sweeps, compliance

Key rule: Set Specification BEFORE setting gain properties. Post-hoc changes to Specification may silently ignore previously set values.

ConfigSelect Requires Mode=1

ConfigSelect only works when Mode = 1 (fixed configuration). With the default Mode = 0 (bypass/auto), row 0 is always used regardless of ConfigSelect value. This is a silent failure — no error, no warning.

FFE Optimization: MMSE vs ZF Tradeoff

Two conceptual strategies for FFE tap weight selection:

StrategyObjectiveProsCons
Zero-Forcing (ZF)Minimize ISI at sample pointsMaximum ISI cancellation, best for high-SNRAmplifies noise at low SNR, can over-equalize
MMSEMinimize mean-squared error (ISI + noise)Better noise performance, robust at low SNRSlightly higher residual ISI

When to use which:

  • ZF approach: Low-loss channels (< 15 dB), NRZ, high SNR — maximize pre/post tap magnitude

  • MMSE approach: High-loss channels (> 20 dB), PAM4, noisy links — keep main cursor higher

  • At mid-loss (15-20 dB), MMSE-like taps typically yield 0.5-1.0 dB better COM than ZF

SerDes Toolbox serdes.FFE does not have a built-in ZF/MMSE mode selector. Instead, implement the tradeoff through tap weight selection:

% ZF-like taps: aggressive pre/post for maximum ISI cancellation
ffeZF = serdes.FFE("TapWeights", [-0.15 0.55 -0.30]);

% MMSE-like taps: conservative pre/post, preserves signal amplitude
ffeMMSE = serdes.FFE("TapWeights", [-0.08 0.77 -0.15]);

Best practice: Use GA optimization (see reference/optimization.md) to find optimal taps for the specific channel and noise environment. GA naturally finds the MMSE-optimal point by maximizing COM (which includes both ISI and noise effects). This is preferred over manually choosing ZF vs MMSE tap weights.

Multi-Lane Simulation

SerDes Toolbox simulates one lane at a time. For multi-lane links (e.g., PCIe x16, 100GBASE-CR4), loop over lanes individually:

% Multi-lane simulation — one lane at a time
sParamFiles = {"lane1.s4p", "lane2.s4p", "lane3.s4p", "lane4.s4p"};
comResults = zeros(numel(sParamFiles), 1);

for lane = 1:numel(sParamFiles)
    spCh = SParameterChannel("FileName", sParamFiles{lane}, ...
        "SampleInterval", symbolTime / 16);
    channel = ChannelData("Impulse", spCh.ImpulseResponse, "dt", spCh.SampleInterval);
    sys = SerdesSystem('ChannelData', channel, ...
        'TxModel', Transmitter('Blocks', {ffe}), ...
        'RxModel', Receiver('Blocks', {ctle, dfecdr}), ...
        'SymbolTime', symbolTime, 'SamplesPerSymbol', 16, ...
        'Modulation', modulation);
    analysis(sys);
    comResults(lane) = sys.Metrics.summary.COMestimate;
end
fprintf("Worst-lane COM: %.2f dB\n", min(comResults));

Crosstalk between lanes is modeled via multi-port S-parameters on a per-victim basis, not as a simultaneous multi-lane simulation. See reference/channel-modeling.md.

FFE Tap Count and Weight Selection

Tap Naming Convention
TapIndexRole
Pre-cursor1Compensates pre-cursor ISI (negative weight)
Main cursor2Signal amplitude (positive, largest weight)
Post-cursor(s)3+Compensates post-cursor ISI (negative weights)

A 3-tap FFE has [pre, main, post]. A 5-tap FFE has [pre2, pre1, main, post1, post2].

Normalization Constraint

FFE taps must satisfy sum(abs(taps)) = 1.0 (energy conservation). For a 3-tap FFE, the main cursor is derived: main = 1 - |pre| - |post|.

Practical Guidelines
  • 3 taps (1 pre + 1 post): Sufficient for most channels up to 25 dB loss

  • 5 taps (2 pre + 2 post): Needed for channels > 25 dB or with significant reflections

  • 7+ taps: Rarely needed; adds complexity without proportional benefit

  • Quantization: Real hardware quantizes taps (e.g., 0.02 resolution). Include in optimization.

  • Main cursor floor: Keep main >= 0.4 to avoid excessive signal attenuation

Tap Weight Starting Points by Loss
Channel LossPreMainPostNotes
5-10 dB-0.050.90-0.05Minimal equalization needed
10-20 dB-0.100.70-0.20Moderate ISI compensation
20-30 dB-0.150.55-0.30Aggressive post-cursor emphasis
30+ dB-0.180.44-0.38Near main-cursor floor

DFE Tap Count Selection

DFE taps cancel post-cursor ISI that FFE cannot reach. More taps = longer ISI cancellation, but diminishing returns after the channel impulse decays.

  • 5 taps: Standard for most links up to 25 dB

  • 10-15 taps: High-loss channels (25-30 dB) with long impulse tails

  • 30-40 taps: Extreme cases (PAM8, very high loss) — last resort

  • Adaptive mode (Mode = 2 on serdes.DFECDR): Let the DFE find its own taps

Key finding: For PAM8 and higher modulation orders, DFE with many taps and NO CTLE (AC Gain = 0 dB) outperforms conventional CTLE + DFE. CTLE amplifies inter-level noise that is critical for PAM8's tight eye levels.

Tx/Rx Analog Parameter Guidance

Include AnalogModel on both Tx and Rx for realistic COM — omitting it inflates COM by 1-2 dB. Analog parameters span three classes:

Default Values and Sensitivities
ParameterSet OnDefaultSensitivityNotes
RiseTimeTransmitter9.6 psHighOptimal: 0.3-0.4 x SymbolTime. Too fast or too slow hurts.
C (Tx)AnalogModel100 fFHigh at > 500 fF1 pF → -2.5 dB COM, 2 pF → -7 dB
C (Rx)AnalogModel200 fFHigh at > 500 fF1 pF → -2.3 dB COM, 2 pF → -5.5 dB
R (Tx)AnalogModel50 ohmLow+-0.5 dB over 25-100 ohm range
R (Rx)AnalogModel50 ohmLow+-0.5 dB over 25-100 ohm range
VoltageSwingIdealTransmitter1.0 VNone (COM)Scales EH linearly, COM is a ratio

AnalogModel accepts only R (single-ended termination resistance) and C (single-ended parasitic capacitance). RiseTime and VoltageSwingIdeal are Transmitter properties.

Setting Analog Parameters in SerdesSystem
sys = SerdesSystem("ChannelData", channel, ...
    'TxModel', Transmitter('Blocks', {ffe}, ...
        'AnalogModel', AnalogModel("R", 50, "C", 150e-15), ...
        'RiseTime', 12e-12, 'VoltageSwingIdeal', 1.0), ...
    'RxModel', Receiver('Blocks', {ctle, dfecdr}, ...
        'AnalogModel', AnalogModel("R", 50, "C", 200e-15)));
Design Insight: CTLE Counterproductive for High-Order PAM

At PAM8 and above, CTLE high-frequency boost amplifies inter-level noise more than it improves the eye. The optimal strategy is often AC Gain = 0 dB with many DFE taps.

56 Gbps PAM8 at 15 dB loss:

  • CTLE AC=12 dB + 5-tap DFE: COM = 0.8 dB (closed eye)

  • CTLE AC=0 dB + 40-tap DFE: COM = 4.9 dB (open eye)

This is the opposite of conventional NRZ/PAM4 wisdom where CTLE is essential.

Industry Reference Designs

Starting-point configurations for common standards. Adjust based on channel characteristics and margin requirements.

56 Gbps PAM4 (28 GBaud)
symbolTime = 1 / 28e9;
ffe = serdes.FFE("TapWeights", [-0.1 0.7 -0.2]);
ctle = serdes.CTLE("Specification", "DC Gain and AC Gain", ...
    "DCGain", 0, "ACGain", 12, "PeakingFrequency", 14e9);
dfecdr = serdes.DFECDR("Mode", 2, "TapWeights", zeros(1, 5), ...
    "SymbolTime", symbolTime, "Modulation", 4);
112 Gbps PAM4 (56 GBaud)
symbolTime = 1 / 56e9;
ffe = serdes.FFE("TapWeights", [-0.15 0.55 -0.30]);
ctle = serdes.CTLE("Specification", "DC Gain and AC Gain", ...
    "DCGain", 0, "ACGain", 15, "PeakingFrequency", 28e9);
dfecdr = serdes.DFECDR("Mode", 2, "TapWeights", zeros(1, 10), ...
    "SymbolTime", symbolTime, "Modulation", 4);
28 Gbps NRZ (28 GBaud)
symbolTime = 1 / 28e9;
ffe = serdes.FFE("TapWeights", [-0.05 0.85 -0.10]);
ctle = serdes.CTLE("Specification", "DC Gain and AC Gain", ...
    "DCGain", 0, "ACGain", 8, "PeakingFrequency", 14e9);
dfecdr = serdes.DFECDR("Mode", 2, "TapWeights", zeros(1, 5), ...
    "SymbolTime", symbolTime, "Modulation", 2);

Fitting CTLE from Measured Data (ctlefit)

When you have measured CTLE frequency response data (e.g., from lab equipment or vendor datasheets as CSV), use ctlefit to generate a GPZ matrix:

% Import measured CTLE data from CSV
% CSV format: freq,real,imag,real,imag,... (one column pair per config)
[f, H] = ctlefit.readcsv("ctle_measured.csv");

% Fit pole-zero model — returns object with GPZ property
obj = ctlefit("f", f, "H", H, "SampleInterval", dt, "MaxNumberOfPoles", 2);
truncateAbove(obj, 2 * nyquistFreq);  % cut fitting noise above 2x Nyquist

% Extract GPZ matrix for SerDes CTLE
gpzMatrix = obj.GPZ;

% Use in SerdesSystem
ctle = serdes.CTLE("Specification", "GPZ Matrix", ...
    "GPZ", gpzMatrix, "Mode", 1, "ConfigSelect", 0);

ctlefit produces a GPZ matrix in the same [Gain(dB) Pole1(Hz) Zero1(Hz) Pole2(Hz)] format as serdes.utilities.poleZeroDefine. Use ctlefit when fitting real measurements; use poleZeroDefine when synthesizing from DC/AC gain specs. See reference/serdes-api-reference.md for ctlefit properties and preprocessing methods.

Extracting Combined Equalization Transfer Function

To visualize the combined equalization transfer function programmatically:

% Get the combined equalization transfer function from a configured system
results = analysis(sys);
eqImpulse = results.impulse(:, 2);     % equalized impulse
unEqImpulse = results.impulse(:, 1);   % unequalized impulse

% Compute transfer function as ratio of FFTs
nfft = 2^nextpow2(numel(eqImpulse));
freq = (0:nfft/2-1) / (nfft * sys.dt);
H_eq = fft(eqImpulse, nfft);
H_uneq = fft(unEqImpulse, nfft);
H_combined = H_eq(1:nfft/2) ./ H_uneq(1:nfft/2);

figure;
plot(freq / 1e9, 20*log10(abs(H_combined)));
xlabel("Frequency (GHz)"); ylabel("Gain (dB)");
title("Effective Equalization Transfer Function");
xlim([0 freq(end)/2e9]);

Note: This shows the combined equalization response (FFE + CTLE + DFE), not the CTLE alone. To isolate the CTLE, run two systems — one with CTLE enabled and one with CTLE bypassed (Mode=0) — and compare their impulse responses.


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MathWorks
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matlab/matlab-agentic-toolkit · skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems · commit 2a7f215
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