Status: Proposed Date: 2026-03-03 Deciders: @ruvnet Supersedes: None Related: ADR-014, ADR-017, ADR-029, ADR-039, ADR-040, ADR-041
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.
| Constraint | Root Cause | Impact on Sensing |
|---|---|---|
| MAC-layer jitter | CSMA/CA random backoff, retransmissions | Non-uniform sample timing, aliased Doppler |
| Rate adaptation | MCS selection varies bandwidth and modulation | Inconsistent subcarrier count per frame |
| LO phase drift | Independent oscillators at TX and RX | Phase noise floor ~5° on ESP32, limiting displacement sensitivity to ~0.87 mm at 2.4 GHz |
| Frame overhead | 802.11 preamble, headers, FCS | Wasted airtime that could carry sensing symbols |
| Bandwidth fragmentation | Channel bonding decisions by AP | Variable spectral coverage per observation |
| Multi-node asynchrony | No shared timing reference | TDM coordination requires statistical phase correction (current phase_align.rs) |
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.
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 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.
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).
| Technology | Frequency | Displacement Resolution | Range | Cost/Node |
|---|---|---|---|---|
| Passive WiFi CSI (current) | 2.4/5 GHz | ~0.87 mm (limited by 5° phase noise) | 1–8 m | $3 |
| 802.11bf NDP sounding | 2.4/5/6 GHz | ~0.4 mm (coherent averaging) | 1–8 m | $3 |
| ESPARGOS phase-coherent | 2.4 GHz | ~0.1 mm (8-antenna coherent) | Room-scale | $5 |
| CW Doppler radar (ISM) | 2.4 GHz | ~10 μm | 1–5 m | $15 |
| Infineon BGT60TR13C | 58–63.5 GHz | Sub-mm | Up to 15 m | $20 |
| Vayyar 4D imaging | 3–81 GHz | High (4D imaging) | Room-scale | $200+ |
| Novelda X4 UWB | 7.29/8.748 GHz | Sub-mm | 0.4–10 m | $15–50 |
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.
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.
┌─────────────────────────────────────────────────────────────────────────┐
│ 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 │ │
│ │ └─────────────────┘ │ │
│ └───────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────┘
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:
| Parameter | Value | Rationale |
|---|---|---|
| Symbol type | 802.11bf NDP (Null Data PPDU) | Standards-compliant, no data payload overhead |
| Sounding cadence | 50–200 Hz (configurable) | 50 Hz minimum for heartbeat Doppler; 200 Hz for gesture |
| Bandwidth | 20/40/80 MHz (per band) | 20 MHz default; 80 MHz for maximum range resolution |
| Pilot structure | L-LTF + HT-LTF (standard) | Known phase structure enables coherent processing |
| Burst duration | ≤10 ms per sounding event | ETSI EN 300 328 burst limit compliance |
| Subcarrier count | 56 (20 MHz) / 114 (40 MHz) / 242 (80 MHz) | Standard OFDM subcarrier allocation |
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.
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):
| Component | Part | Cost | Purpose |
|---|---|---|---|
| TCXO | SiT8008 40 MHz ±0.5 ppm | $0.50 | Reference oscillator (1 per system) |
| PLL synthesizer | SI5351A | $1.00 | Generates 40 MHz + 2.4 GHz references (1 per system) |
| Coax splitter | Mini-Circuits PSC-4-1+ | $0.30/port | Distributes reference to nodes |
| SMA connector | Edge-mount | $0.20 | Reference clock input on each node |
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.
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:
| Property | 2.4 GHz | 5 GHz | 6 GHz |
|---|---|---|---|
| Wavelength | 12.5 cm | 6.0 cm | 5.0 cm |
| Wall penetration | Excellent | Good | Moderate |
| Displacement sensitivity (0.5° phase) | 0.087 mm | 0.042 mm | 0.035 mm |
| Range resolution (20 MHz) | 7.5 m | 7.5 m | 7.5 m |
| Fresnel zone radius (2 m) | 22.4 cm | 15.5 cm | 14.1 cm |
| Subcarrier spacing (20 MHz) | 312.5 kHz | 312.5 kHz | 312.5 kHz |
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.
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:
| Parameter | Value | Rationale |
|---|---|---|
| Burst cadence | 1–5 kHz | 5 kHz enables 2.5 kHz Doppler bandwidth (Nyquist) |
| Burst duration | 4–20 μs | Single OFDM symbol + CP = 4 μs minimum |
| Symbols per burst | 1–4 | Minimal overhead per measurement |
| Duty cycle | 0.4–10% | Compliant with ETSI 10 ms burst limit |
| Inter-burst gap | 196–996 μs | Available for normal WiFi traffic |
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.
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:
| Design parameter | WiFi (throughput) | CHCI (sensing) |
|---|---|---|
| Spacing | λ/2 (6.25 cm) | λ/4 (3.125 cm) |
| Goal | Maximize diversity gain | Maximize angular resolution |
| Array factor | Broad main lobe | Narrow main lobe, grating lobe suppression |
| Geometry | Dual-antenna diversity | Linear or L-shaped phased array |
| Target signal | Far-field plane wave | Near-field chest wall displacement |
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.
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.
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):
| Metric | Current (Amplitude) | Proposed (Coherent Diffraction) |
|---|---|---|
| Spatial resolution | ~15 cm (limited by wavelength) | ~3 cm (multi-band synthesis) |
| Body segment discrimination | Coarse (torso vs limb) | Fine (individual limbs) |
| Surface vs volume | Volumetric opacity | Surface geometry |
| Through-wall capability | Yes (amplitude penetrates) | Partial (phase coherence degrades) |
| Calibration requirement | None | Empty room reference scan |
Primary acceptance criterion: Demonstrate 0.1 mm displacement detection repeatably at 2 meters in a static controlled room.
Full acceptance test protocol:
| Test | Metric | Target | Method |
|---|---|---|---|
| AT-1: Phase stability | σ_φ per subcarrier, static, 10 min | ≤ 0.5° RMS | Record CSI, compute variance |
| AT-2: Displacement | Detectable displacement at 2 m | ≤ 0.1 mm | Precision linear stage, sinusoidal motion |
| AT-3: Breathing rate | BPM error, 3 subjects, 5 min each | ≤ 0.2 BPM | Reference: respiratory belt |
| AT-4: Heart rate | BPM error, 3 subjects, seated, 2 min | ≤ 3 BPM | Reference: pulse oximeter |
| AT-5: Multi-person | Pose detection, 3 persons, 4×4 m room | ≥ 90% keypoint detection | Reference: camera ground truth |
| AT-6: Power | Average draw in IDLE mode | ≤ 10 mA (radio) | Current meter on 3.3 V rail |
| AT-7: Latency | End-to-end pose update latency | ≤ 50 ms | Timestamp injection |
| AT-8: Regulatory | Conducted emissions, 2.4 GHz ISM | FCC 15.247 + ETSI 300 328 | Spectrum analyzer |
Question 1: Do you want backward compatibility with normal WiFi routers?
CHCI supports a dual-mode architecture:
| Mode | Description | When to Use |
|---|---|---|
| Legacy CSI | Passive sniffing of existing WiFi traffic | Retrofit into existing WiFi environments, no hardware changes |
| 802.11bf NDP | Standard-compliant NDP sounding | WiFi AP supports 802.11bf, moderate improvement over legacy |
| CHCI Native | Full coherent sounding with shared clock | Purpose-deployed sensing mesh, maximum fidelity |
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.
| Component | Part | Quantity | Unit Cost | Purpose |
|---|---|---|---|---|
| ESP32-S3-WROOM-1 | Espressif | 1 | $2.50 | Main MCU + WiFi radio |
| External antenna | 2.4/5 GHz dual-band | 2–4 | $0.30 each | Sensing antennas (λ/4 spacing) |
| SMA connector | Edge-mount | 1 | $0.20 | Reference clock input |
| Coax cable | RG-174 | 1 m | $0.15 | Clock distribution |
| PCB | Custom 4-layer | 1 | $0.50 | Integration (at volume) |
| Node total | $4.25 | |||
| Reference clock module | SI5351A + TCXO + splitter | 1 per system | $3.00 | Shared clock source |
| 4-node system total | $20.00 |
This is 10× cheaper than the nearest comparable coherent sensing platform (Novelda X4 at $50/node, Vayyar at $200+).
| Phase | Timeline | Deliverables | Dependencies |
|---|---|---|---|
| Phase 1: NDP Sounding | 4 weeks | ESP32-S3 firmware for 802.11bf NDP TX/RX, sounding scheduler, CSI extraction from NDP frames | ESP-IDF 5.2+, existing firmware |
| Phase 2: Clock Distribution | 6 weeks | Reference clock PCB design, SI5351A driver, phase reference distribution, phase_align.rs upgrade |
Phase 1, PCB fabrication |
| Phase 3: Coherent Processing | 4 weeks | Coherent diffraction tomography in tomography.rs, complex-valued CSI pipeline, calibration procedure |
Phase 2 |
| Phase 4: Multi-Band Fusion | 4 weeks | Simultaneous 2.4+5 GHz sounding, cross-band phase alignment, contrastive fusion in RuVector space | Phase 1, Phase 3 |
| Phase 5: Cognitive Engine | 3 weeks | Waveform adaptation state machine, coherence delta feedback, power management modes | Phase 3, Phase 4 |
| Phase 6: Acceptance Testing | 3 weeks | AT-1 through AT-8, precision displacement rig, regulatory pre-scan | Phase 5 |
New and modified crates:
| Crate | Type | Description |
|---|---|---|
wifi-densepose-chci |
New | CHCI protocol definition, waveform specs, cognitive engine |
wifi-densepose-signal |
Modified | Add coherent diffraction tomography, upgrade phase_align.rs |
wifi-densepose-hardware |
Modified | Reference clock driver, NDP sounding firmware, antenna geometry config |
wifi-densepose-ruvector |
Modified | Cross-band contrastive fusion in viewpoint attention |
wifi-densepose-wasm-edge |
Modified | New WASM modules for CHCI-specific edge processing |
| Existing Module | Current Function | CHCI Upgrade |
|---|---|---|
phase_align.rs |
Statistical LO offset estimation | Replace with shared-clock phase reference alignment |
multiband.rs |
Independent per-channel fusion | Coherent cross-band phase alignment with body priors |
coherence.rs |
Z-score coherence scoring | Complex-valued coherence metric (phasor domain) |
coherence_gate.rs |
Accept/Reject gate decisions | Add waveform adaptation feedback to cognitive engine |
tomography.rs |
Amplitude-only ISTA L1 solver | Coherent diffraction tomography with complex CSI |
multistatic.rs |
Attention-weighted fusion | Add PLL-disciplined synchronization path |
field_model.rs |
SVD room eigenstructure | Coherent room transfer function model with phase |
intention.rs |
Pre-movement lead signals | Enhanced micro-Doppler from high-cadence bursts |
gesture.rs |
DTW template matching | Phase-domain gesture features (higher discrimination) |
- 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)
- 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.
| Risk | Likelihood | Impact | Mitigation |
|---|---|---|---|
| ESP32-S3 WiFi hardware does not support NDP TX at 802.11bf spec | Medium | High | Fall back to raw 802.11 frame injection with known preamble; validate with esp_wifi_80211_tx() |
| Phase coherence degrades over cable length >2 m | Low | Medium | Use matched-length cables; add per-node phase calibration step |
| ETSI/FCC regulatory rejection of custom sounding cadence | Low | High | Stay within 802.11bf NDP specification; use standard-compliant waveforms only |
| Coherent diffraction tomography computationally exceeds ESP32 | Medium | Medium | Run tomography on aggregator (Rust server), not on edge. ESP32 sends coherent CSI only |
| Multi-band simultaneous TX causes self-interference | Medium | Medium | Time-division between bands (alternating 2.4/5 GHz per burst slot) or frequency planning |
| Body model priors over-constrain fusion, missing novel poses | Low | Medium | Use priors as soft constraints (regularization) not hard constraints |
- 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.
- ETSI EN 300 328 V2.2.2, "Wideband transmission systems; Data transmission equipment operating in the 2.4 GHz band," ETSI, July 2019.
- FCC 47 CFR Part 15.247, "Operation within the bands 902–928 MHz, 2400–2483.5 MHz, and 5725–5850 MHz."
- 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]
- Restuccia, F., "IEEE 802.11bf: Toward Ubiquitous Wi-Fi Sensing," IEEE Communications Standards Magazine, 2024. [arXiv:2310.05765]
- Pegoraro, J., et al., "Sensing Performance of the IEEE 802.11bf Protocol," IEEE, 2024. [arXiv:2403.19825]
- Chen, Y., et al., "Multi-Band Wi-Fi Neural Dynamic Fusion for Sensing," IEEE ICASSP, 2024. [arXiv:2407.12937]
- Samsung Research, "Optimal Preprocessing of WiFi CSI for Sensing Applications," IEEE, 2024. [arXiv:2307.12126]
- Yan, Y., et al., "Person-in-WiFi 3D: End-to-End Multi-Person 3D Pose Estimation with Wi-Fi," CVPR 2024.
- Geng, J., et al., "DensePose From WiFi," Carnegie Mellon University, 2023. [arXiv:2301.00250]
- Pegoraro, J., et al., "802.11bf Multiband Passive Sensing," IEEE, 2025. [arXiv:2507.22591]
- Liu, J., et al., "Monitoring Vital Signs and Postures During Sleep Using WiFi Signals," MobiCom, 2020.
- Vayyar Imaging, "4D Imaging Radar Technology Platform," https://vayyar.com/technology/
- Infineon Technologies, "BGT60TR13C 60 GHz Radar Sensor IC Datasheet," 2024.
- Novelda AS, "X4 UWB Radar SoC Datasheet," https://novelda.com/technology/
- Texas Instruments, "IWR6843 Single-Chip 60-GHz mmWave Sensor," 2024.
- ESPARGOS Project, https://espargos.net/
- ADR-014: SOTA Signal Processing (phase alignment, coherence scoring)
- ADR-017: RuVector Signal + MAT Integration (embedding fusion)
- ADR-029: RuvSense Multistatic Sensing Mode (multi-node coordination)
- ADR-039: ESP32 Edge Intelligence (tiered processing, power management)
- ADR-040: WASM Programmable Sensing (edge compute architecture)
- ADR-041: WASM Module Collection (algorithm registry)