ADR-042: Coherent Human Channel Imaging (CHCI) — Beyond WiFi CSI

Status: Proposed Date: 2026-03-03 Deciders: @ruvnet Supersedes: None Related: ADR-014, ADR-017, ADR-029, ADR-039, ADR-040, ADR-041

Context

WiFi-DensePose currently relies on passive Channel State Information (CSI) extracted from standard 802.11 traffic frames. CSI is one specific way of estimating a channel response, but it is fundamentally constrained by a protocol designed for throughput and interoperability — not for sensing.

Fundamental Limitations of Passive WiFi CSI

These constraints impose a hard floor on sensing fidelity. Breathing detection (4–12 mm chest displacement) is reliable, but heartbeat detection (0.2–0.5 mm) is marginal. Pose estimation accuracy is limited by amplitude-only tomography rather than coherent phase imaging.

What We Actually Want

The real objective is coherent multipath sensing — measuring the complex-valued impulse response of the human-occupied channel with sufficient phase stability and temporal resolution to reconstruct body surface geometry and sub-millimeter physiological motion.

WiFi is optimized for throughput and interoperability. DensePose is optimized for phase stability and micro-Doppler fidelity. Those goals are not aligned.

IEEE 802.11bf Changes the Landscape

IEEE Std 802.11bf-2025 was published on September 26, 2025, defining WLAN Sensing as a first-class MAC/PHY capability. Key provisions:

• Null Data PPDU (NDP) sounding: Deterministic, known waveforms with no data payload — purpose-built for channel measurement
• Sensing Measurement Setup (SMS): Negotiation protocol between sensing initiator and responder with unique session IDs
• Trigger-Based Sensing Measurement Exchange (TB SME): AP-coordinated sounding with Sensing Availability Windows (SAW)
• Multiband support: Sub-7 GHz (2.4, 5, 6 GHz) plus 60 GHz mmWave
• Bistatic and multistatic modes: Standard-defined multi-node sensing

This transforms WiFi sensing from passive traffic sniffing into an intentional, standards-compliant sensing protocol. The question is whether to adopt 802.11bf incrementally or to design a purpose-built coherent sensing architecture that goes beyond what 802.11bf specifies.

ESPARGOS Proves Phase Coherence at ESP32 Cost

The ESPARGOS project (University of Stuttgart, IEEE 2024) demonstrates that phase-coherent WiFi sensing is achievable with commodity ESP32 hardware:

• 8 antennas per board, each on an ESP32-S2
• Phase coherence via shared 40 MHz reference clock + 2.4 GHz phase reference signal distributed over coaxial cable
• Multiple boards combinable into larger coherent arrays
• Public datasets with reference positioning labels
• Ultra-low cost compared to commercial radar platforms

This proves the hardware architecture described in this ADR is feasible at the ESP32-S3 price point ($3–5 per node).

SOTA Displacement Sensitivity

The gap between passive WiFi CSI (~0.87 mm) and coherent phase processing (~0.1 mm) represents a 9x improvement in displacement sensitivity — the difference between marginal and reliable heartbeat detection at ISM bands.

Decision

We define Coherent Human Channel Imaging (CHCI) — a purpose-built coherent RF sensing protocol optimized for structural human motion, vital sign extraction, and body surface reconstruction. CHCI is not WiFi in the traditional sense. It is a sensing protocol that operates within ISM band regulatory constraints and can optionally maintain backward compatibility with 802.11bf.

Architecture Overview

┌─────────────────────────────────────────────────────────────────────────┐
│                    CHCI System Architecture                             │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                         │
│  ┌─────────────┐     ┌─────────────┐     ┌─────────────┐              │
│  │  CHCI Node  │     │  CHCI Node  │     │  CHCI Node  │              │
│  │  (TX + RX)  │     │  (TX + RX)  │     │  (TX + RX)  │              │
│  │  ESP32-S3   │     │  ESP32-S3   │     │  ESP32-S3   │              │
│  └──────┬──────┘     └──────┬──────┘     └──────┬──────┘              │
│         │                   │                   │                      │
│         └───────────┬───────┴───────────────────┘                      │
│                     │                                                   │
│            ┌────────┴────────┐                                         │
│            │  Reference Clock │  ← 40 MHz TCXO + PLL distribution     │
│            │  Distribution    │  ← 2.4/5 GHz phase reference          │
│            └────────┬────────┘                                         │
│                     │                                                   │
│  ┌──────────────────┴──────────────────────────────┐                   │
│  │          Waveform Controller                      │                  │
│  │  ┌────────────┐  ┌────────────┐  ┌────────────┐ │                  │
│  │  │ NDP Sound  │  │ Micro-Burst│  │ Chirp Gen  │ │                  │
│  │  │ (802.11bf) │  │ (5 kHz)    │  │ (Multi-BW) │ │                  │
│  │  └────────────┘  └────────────┘  └────────────┘ │                  │
│  │         │              │               │          │                  │
│  │         └──────────────┼───────────────┘          │                  │
│  │                        ▼                          │                  │
│  │              ┌─────────────────┐                  │                  │
│  │              │ Cognitive Engine │ ← Scene state   │                  │
│  │              │ (Waveform Adapt) │   feedback loop │                  │
│  │              └─────────────────┘                  │                  │
│  └───────────────────────────────────────────────────┘                  │
│                        │                                                │
│                        ▼                                                │
│  ┌───────────────────────────────────────────────────┐                  │
│  │          Signal Processing Pipeline                │                 │
│  │  ┌──────────┐  ┌───────────┐  ┌────────────────┐ │                 │
│  │  │ Coherent  │  │ Multi-Band│  │ Diffraction    │ │                 │
│  │  │ Phase     │  │ Fusion    │  │ Tomography     │ │                 │
│  │  │ Alignment │  │ (2.4+5+6) │  │ (Complex CSI)  │ │                 │
│  │  └──────────┘  └───────────┘  └────────────────┘ │                 │
│  │         │              │               │          │                 │
│  │         └──────────────┼───────────────┘          │                 │
│  │                        ▼                          │                 │
│  │              ┌─────────────────┐                  │                 │
│  │              │ Body Model      │                  │                 │
│  │              │ Reconstruction  │ ── DensePose UV  │                 │
│  │              └─────────────────┘                  │                 │
│  └───────────────────────────────────────────────────┘                  │
│                                                                         │
└─────────────────────────────────────────────────────────────────────────┘

1. Intentional OFDM Sounding (Replaces Passive CSI Sniffing)

What changes: Instead of waiting for random WiFi packets and extracting CSI as a side effect, transmit deterministic OFDM sounding frames at a fixed cadence with known pilot symbol structure.

Waveform specification:

Phase stability improvement:

Passive CSI:     σ_φ ≈ 5° per subcarrier (random MCS, no averaging)
NDP Sounding:    σ_φ ≈ 5° / √N  where N = coherent averages per epoch
                 At 50 Hz cadence, 10-frame average: σ_φ ≈ 1.6°
                 Displacement floor: 0.87 mm → 0.28 mm at 2.4 GHz

Implementation: New ESP32-S3 firmware mode alongside existing passive CSI. Uses esp_wifi_80211_tx() for NDP transmission and existing CSI callback for reception. Sounding schedule coordinated by the Waveform Controller.

2. Phase-Locked Dual-Radio Architecture

What changes: All CHCI nodes share a common reference clock, eliminating per-node LO phase drift that currently requires statistical correction in phase_align.rs.

Clock distribution design (based on ESPARGOS architecture):

┌──────────────────────────────────────────────────┐
│              Reference Clock Module               │
│                                                    │
│  ┌──────────┐     ┌──────────────┐               │
│  │ 40 MHz   │────▶│ PLL          │               │
│  │ TCXO     │     │ Synthesizer  │               │
│  │ (±0.5ppm)│     │ (SI5351A)    │               │
│  └──────────┘     └──────┬───────┘               │
│                          │                        │
│           ┌──────────────┼──────────────┐        │
│           ▼              ▼              ▼        │
│     ┌──────────┐   ┌──────────┐   ┌──────────┐ │
│     │ 40 MHz   │   │ 40 MHz   │   │ 40 MHz   │ │
│     │ to Node 1│   │ to Node 2│   │ to Node 3│ │
│     └──────────┘   └──────────┘   └──────────┘ │
│                                                    │
│     ┌──────────┐   ┌──────────┐   ┌──────────┐ │
│     │ 2.4 GHz  │   │ 2.4 GHz  │   │ 2.4 GHz  │ │
│     │ Phase Ref│   │ Phase Ref│   │ Phase Ref│ │
│     │ to Node 1│   │ to Node 2│   │ to Node 3│ │
│     └──────────┘   └──────────┘   └──────────┘ │
│                                                    │
│  Distribution: coaxial cable with power splitters  │
│  Phase ref: CW tone at center of operating band    │
└──────────────────────────────────────────────────┘

Components per node (incremental cost ~$2):

Acceptance metric: Phase variance per subcarrier under static conditions ≤ 0.5° RMS over 10 minutes (vs current ~5° with statistical correction).

Impact on displacement sensitivity:

Current (incoherent):     δ_min ≈ λ/(4π) × σ_φ = 12.5cm/(4π) × 5° × π/180 ≈ 0.87 mm
Coherent (shared clock):  δ_min ≈ λ/(4π) × 0.5° × π/180 ≈ 0.087 mm

With 8-antenna coherent averaging:
  δ_min ≈ 0.087 mm / √8 ≈ 0.031 mm

This puts heartbeat detection (0.2–0.5 mm chest displacement) well within the sensitivity envelope.

3. Multi-Band Coherent Fusion

What changes: Transmit sounding frames simultaneously at 2.4 GHz and 5 GHz (optionally 6 GHz with WiFi 6E), fusing them as projections of the same latent motion field in RuVector embedding space.

Band characteristics for coherent fusion:

Fusion architecture:

2.4 GHz CSI ──▶ ┌───────────────────┐
                │ Band-Specific      │     ┌─────────────────────┐
                │ Phase Alignment    │────▶│                     │
                │ (per-band ref)     │     │ Contrastive         │
                └───────────────────┘     │ Cross-Band          │
                                          │ Fusion              │
5 GHz CSI ────▶ ┌───────────────────┐     │                     │
                │ Band-Specific      │────▶│ Body model priors   │
                │ Phase Alignment    │     │ constrain phase     │
                │ (per-band ref)     │     │ relationships       │
                └───────────────────┘     │                     │
                                          │ Output: unified     │
6 GHz CSI ────▶ ┌───────────────────┐     │ complex channel     │
  (optional)    │ Band-Specific      │────▶│ response            │
                │ Phase Alignment    │     │                     │
                └───────────────────┘     └─────────────────────┘
                                                    │
                                                    ▼
                                          ┌─────────────────────┐
                                          │ RuVector Contrastive │
                                          │ Embedding Space      │
                                          │ (body surface latent)│
                                          └─────────────────────┘

Key insight: Lower frequency penetrates better (through-wall sensing, NLOS paths). Higher frequency provides finer spatial resolution. By treating each band as a projection of the same physical scene, the fusion model can achieve super-resolution beyond any single band — using body model priors (known human dimensions, joint angle constraints) to constrain the phase relationships across bands.

Integration with existing code: Extends multiband.rs from independent per-channel fusion to coherent cross-band phase alignment. The existing CrossViewpointAttention mechanism in ruvector/src/viewpoint/attention.rs provides the attention-weighted fusion foundation.

4. Time-Coded Micro-Bursts

What changes: Replace continuous WiFi packet streams with very short deterministic OFDM bursts at high cadence, maximizing temporal resolution of Doppler shifts without 802.11 frame overhead.

Burst specification:

Doppler resolution comparison:

Passive WiFi CSI (random, ~30 Hz):
  Doppler resolution: Δf_D = 1/T_obs = 1/33ms ≈ 30 Hz
  Minimum detectable velocity: v_min = λ × Δf_D / 2 ≈ 1.9 m/s at 2.4 GHz

CHCI micro-burst (5 kHz cadence):
  Doppler resolution: Δf_D = 1/(N × T_burst) = 1/(256 × 0.2ms) ≈ 20 Hz
  BUT: unambiguous Doppler: ±2500 Hz → v_max = ±156 m/s
  Minimum detectable velocity: v_min ≈ λ × 20 / 2 ≈ 1.25 m/s

  With coherent integration over 1 second (5000 bursts):
  Δf_D = 1/1s = 1 Hz → v_min ≈ 0.063 m/s (6.3 cm/s)
  Chest wall velocity during breathing: ~1–5 cm/s ✓
  Chest wall velocity during heartbeat: ~0.5–2 cm/s ✓

Regulatory compliance: At 5 kHz burst cadence with 4 μs bursts, duty cycle is 2%. ETSI EN 300 328 allows up to 10 ms continuous transmission followed by mandatory idle. A 4 μs burst followed by 196 μs idle is well within limits. FCC Part 15.247 requires digital modulation (OFDM qualifies) or spread spectrum.

5. MIMO Geometry Optimization

What changes: Instead of 2×2 WiFi-style antenna layout (optimized for throughput diversity), design antenna spacing tuned for human-scale wavelengths and chest wall displacement sensitivity.

Antenna geometry design:

Current WiFi-DensePose (throughput-optimized):
  ┌─────────────────┐
  │  ANT1      ANT2 │  ← λ/2 spacing = 6.25 cm at 2.4 GHz
  │                  │     Optimized for spatial diversity
  │  ESP32-S3       │
  └─────────────────┘

Proposed CHCI (sensing-optimized):
  ┌───────────────────────────────────────┐
  │                                        │
  │  ANT1    ANT2    ANT3    ANT4         │  ← λ/4 spacing = 3.125 cm
  │   ●───────●───────●───────●           │     at 2.4 GHz
  │                                        │     Linear array for 1D AoA
  │  ESP32-S3 (Node A)                    │
  └───────────────────────────────────────┘
        λ/4 = 3.125 cm

  Alternative: L-shaped for 2D AoA:
  ┌────────────────────┐
  │  ANT4              │
  │   ●                │
  │   │ λ/4            │
  │  ANT3              │
  │   ●                │
  │   │ λ/4            │
  │  ANT2              │
  │   ●                │
  │   │ λ/4            │
  │  ANT1──●──ANT5──●──ANT6──●──ANT7    │
  │                                       │
  │  ESP32-S3 (Node A)                   │
  └────────────────────┘

Design rationale:

Virtual aperture synthesis: With 4 nodes × 4 antennas = 16 physical elements, MIMO virtual aperture provides 16 × 16 = 256 virtual channels. Combined with MUSIC or ESPRIT algorithms, this enables sub-degree angle-of-arrival estimation — sufficient to resolve individual body segments.

6. Cognitive Waveform Adaptation

What changes: The sensing waveform adapts in real-time based on the current scene state, driven by delta coherence feedback from the body model.

Cognitive sensing modes:

┌───────────────────────────────────────────────────────────────┐
│                    Cognitive Waveform Engine                    │
│                                                                │
│  Scene State ─────▶ ┌────────────────┐ ─────▶ Waveform Config │
│  (from body model)  │ Mode Selector  │        (to TX nodes)    │
│                     └───────┬────────┘                         │
│                             │                                  │
│              ┌──────────────┼──────────────────┐              │
│              ▼              ▼                  ▼              │
│     ┌────────────┐  ┌────────────┐    ┌────────────┐         │
│     │   IDLE     │  │   ALERT    │    │   ACTIVE   │         │
│     │            │  │            │    │            │         │
│     │ 1 Hz NDP   │  │ 10 Hz NDP  │    │ 50-200 Hz  │         │
│     │ Single band│  │ Dual band  │    │ All bands  │         │
│     │ Low power  │  │ Med power  │    │ Full power │         │
│     │            │  │            │    │            │         │
│     │ Presence   │  │ Tracking   │    │ DensePose  │         │
│     │ detection  │  │ + coarse   │    │ + vitals   │         │
│     │ only       │  │ pose       │    │ + micro-   │         │
│     │            │  │            │    │ Doppler    │         │
│     └────────────┘  └────────────┘    └────────────┘         │
│           │              │                  │                 │
│           ▼              ▼                  ▼                 │
│     ┌────────────┐  ┌────────────┐    ┌────────────┐         │
│     │   VITAL    │  │   GESTURE  │    │   SLEEP    │         │
│     │            │  │            │    │            │         │
│     │ 100 Hz     │  │ 200 Hz     │    │ 20 Hz      │         │
│     │ Subset of  │  │ Full band  │    │ Single     │         │
│     │ optimal    │  │ Max bursts │    │ band       │         │
│     │ subcarriers│  │            │    │ Low power  │         │
│     │            │  │            │    │            │         │
│     │ Breathing, │  │ DTW match  │    │ Apnea,     │         │
│     │ HR, HRV    │  │ + classify │    │ movement,  │         │
│     │            │  │            │    │ stages     │         │
│     └────────────┘  └────────────┘    └────────────┘         │
│                                                                │
│  Transition triggers:                                          │
│    IDLE → ALERT:   Coherence delta > threshold                │
│    ALERT → ACTIVE: Person detected with confidence > 0.8      │
│    ACTIVE → VITAL: Static person, body model stable           │
│    ACTIVE → GESTURE: Motion spike with periodic structure     │
│    ACTIVE → SLEEP: Supine pose detected, low ambient motion   │
│    * → IDLE:       No detection for 30 seconds                │
│                                                                │
└───────────────────────────────────────────────────────────────┘

Power efficiency: Cognitive adaptation reduces average power consumption by 60–80% compared to constant full-rate sounding. In IDLE mode (1 Hz, single band, low power), the system draws <10 mA from the ESP32-S3 radio — enabling battery-powered deployment.

Integration with ADR-039: The cognitive waveform modes map directly to ADR-039 edge processing tiers. Tier 0 (raw CSI) corresponds to IDLE/ALERT. Tier 1 (phase unwrap, stats) corresponds to ACTIVE. Tier 2 (vitals, fall detection) corresponds to VITAL/SLEEP. The cognitive engine adds the waveform adaptation feedback loop that ADR-039 lacks.

7. Coherent Diffraction Tomography

What changes: Current tomography (tomography.rs) uses amplitude-only attenuation for voxel reconstruction. With coherent phase data from CHCI, we upgrade to diffraction tomography — resolving body surfaces rather than volumetric shadows.

Mathematical foundation:

Current (amplitude tomography):
  I(x,y,z) = Σ_links |H_measured(f)| × W_link(x,y,z)
  Output: scalar opacity per voxel (shadow image)

Proposed (coherent diffraction tomography):
  O(x,y,z) = F^{-1}[ Σ_links H_measured(f,θ) / H_reference(f,θ) ]
  Where:
    H_measured = complex channel response with human present
    H_reference = complex channel response of empty room (calibration)
    f = frequency (across all bands)
    θ = link angle (across all node pairs)
  Output: complex permittivity contrast per voxel (body surface)

Key advantage: Diffraction tomography produces body surface geometry, not just occupancy maps. This directly feeds the DensePose UV mapping pipeline with geometric constraints — reducing the neural network's burden from "guess the surface from shadows" to "refine the surface from holographic reconstruction."

Performance projection (based on ESPARGOS results and multi-band coverage):

Acceptance Test

Primary acceptance criterion: Demonstrate 0.1 mm displacement detection repeatably at 2 meters in a static controlled room.

Full acceptance test protocol:

Backward Compatibility

Question 1: Do you want backward compatibility with normal WiFi routers?

CHCI supports a dual-mode architecture:

The firmware can switch between modes at runtime. The signal processing pipeline (signal/src/ruvsense/) accepts CSI from any mode — the coherent processing path activates when shared-clock metadata is present in the CSI frame header.

Question 2: Are you willing to own both transmitter and receiver hardware?

Yes. CHCI requires owning both TX and RX to achieve phase coherence. The system is deployed as a self-contained sensing mesh — not parasitic on existing WiFi infrastructure. This is the fundamental architectural trade: compatibility for control. For sensing, that is a good trade.

Hardware Bill of Materials (per CHCI node)

This is 10× cheaper than the nearest comparable coherent sensing platform (Novelda X4 at $50/node, Vayyar at $200+).

Implementation Phases

Crate Architecture

New and modified crates:

Module Impact Matrix

Consequences

Positive

• 9× displacement sensitivity improvement: From 0.87 mm (incoherent) to 0.031 mm (coherent 8-antenna) at 2.4 GHz, enabling reliable heartbeat detection at ISM bands
• Standards-compliant path: 802.11bf NDP sounding is a published IEEE standard (September 2025), providing regulatory clarity
• 10× cost advantage: $4.25/node vs $50+ for nearest comparable coherent sensing platform
• Through-wall preservation: Operates at 2.4/5 GHz ISM bands, maintaining the through-wall sensing advantage that mmWave systems lack
• Backward compatible: Dual-mode firmware supports legacy CSI, 802.11bf NDP, and native CHCI — deployable incrementally
• Privacy-preserving: No cameras, no audio — same RF-only sensing paradigm as current WiFi-DensePose
• Power-efficient: Cognitive waveform adaptation reduces average power 60–80% vs constant-rate sounding
• Body surface reconstruction: Coherent diffraction tomography produces geometric constraints for DensePose, reducing neural network inference burden
• Proven feasibility: ESPARGOS demonstrates phase-coherent WiFi sensing at ESP32 cost point (IEEE 2024)

Negative

• Custom hardware required: Cannot parasitically sense from existing WiFi routers in CHCI Native mode (802.11bf mode can use compliant APs)
• PCB design needed: Reference clock distribution requires custom PCB — not a pure firmware upgrade
• Calibration burden: Coherent diffraction tomography requires empty-room reference scan — adds deployment friction
• Clock distribution complexity: Coaxial cable distribution limits deployment flexibility vs fully wireless mesh
• Two-phase deployment: Full CHCI requires Phases 1–6 (~24 weeks). Intermediate modes (NDP-only, Phase 1) provide incremental value.

Risks

References

Standards

1. IEEE Std 802.11bf-2025, "Standard for Information Technology — Telecommunications and Information Exchange between Systems — Local and Metropolitan Area Networks — Specific Requirements — Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications — Amendment: Enhancements for Wireless Local Area Network (WLAN) Sensing," IEEE, September 2025.
2. ETSI EN 300 328 V2.2.2, "Wideband transmission systems; Data transmission equipment operating in the 2.4 GHz band," ETSI, July 2019.
3. FCC 47 CFR Part 15.247, "Operation within the bands 902–928 MHz, 2400–2483.5 MHz, and 5725–5850 MHz."

Research Papers

4. Euchner, F., et al., "ESPARGOS: An Ultra Low-Cost, Realtime-Capable Multi-Antenna WiFi Channel Sounder for Phase-Coherent Sensing," IEEE, 2024. [arXiv:2502.09405]
5. Restuccia, F., "IEEE 802.11bf: Toward Ubiquitous Wi-Fi Sensing," IEEE Communications Standards Magazine, 2024. [arXiv:2310.05765]
6. Pegoraro, J., et al., "Sensing Performance of the IEEE 802.11bf Protocol," IEEE, 2024. [arXiv:2403.19825]
7. Chen, Y., et al., "Multi-Band Wi-Fi Neural Dynamic Fusion for Sensing," IEEE ICASSP, 2024. [arXiv:2407.12937]
8. Samsung Research, "Optimal Preprocessing of WiFi CSI for Sensing Applications," IEEE, 2024. [arXiv:2307.12126]
9. Yan, Y., et al., "Person-in-WiFi 3D: End-to-End Multi-Person 3D Pose Estimation with Wi-Fi," CVPR 2024.
10. Geng, J., et al., "DensePose From WiFi," Carnegie Mellon University, 2023. [arXiv:2301.00250]
11. Pegoraro, J., et al., "802.11bf Multiband Passive Sensing," IEEE, 2025. [arXiv:2507.22591]
12. Liu, J., et al., "Monitoring Vital Signs and Postures During Sleep Using WiFi Signals," MobiCom, 2020.

Commercial Systems

13. Vayyar Imaging, "4D Imaging Radar Technology Platform," https://vayyar.com/technology/
14. Infineon Technologies, "BGT60TR13C 60 GHz Radar Sensor IC Datasheet," 2024.
15. Novelda AS, "X4 UWB Radar SoC Datasheet," https://novelda.com/technology/
16. Texas Instruments, "IWR6843 Single-Chip 60-GHz mmWave Sensor," 2024.
17. ESPARGOS Project, https://espargos.net/

Related ADRs

18. ADR-014: SOTA Signal Processing (phase alignment, coherence scoring)
19. ADR-017: RuVector Signal + MAT Integration (embedding fusion)
20. ADR-029: RuvSense Multistatic Sensing Mode (multi-node coordination)
21. ADR-039: ESP32 Edge Intelligence (tiered processing, power management)
22. ADR-040: WASM Programmable Sensing (edge compute architecture)
23. ADR-041: WASM Module Collection (algorithm registry)