---
license: mit
pretty_name: Twin6G — Over-the-Air 5G NR PHY Dataset
tags:
  - 5g
  - 5g-nr
  - physical-layer
  - rf
  - iq
  - sigmf
  - srsran
  - open5gs
  - ran-telemetry
  - wireless
  - digital-twin
  - fake-base-station
size_categories:
  - 1K<n<10K
configs:
  - config_name: gnb_metrics
    data_files: "**/tier2_metrics/gnb_sched_ue.csv"
  - config_name: ue_nr
    data_files: "**/tier2_metrics/ue_nr_adb.csv"
---

# Twin6G — Over-the-Air 5G NR PHY Dataset

Real **over-the-air 5G NR** measurements for the Twin6G project: raw radio-frequency samples and
physical-layer telemetry of a live standalone 5G cell serving a commercial phone. Unlike simulator traces
(for example UERANSIM), every recording here is a genuine radio observation, so it carries true
physical-layer (Layer 1) information.

Each run is self-contained in a timestamped directory and provides two paired tiers captured in the **same
session**:

- **Tier 1 — raw IQ**: the rawest possible form, complex baseband samples of the cell sniffed off the air.
- **Tier 2 — PHY telemetry**: per-UE radio metrics from the base station and radio measurements reported by
  the phone, plus the control-plane and MAC packet captures.

## Provenance

All data is **measured, over the air**. It is collected on a software-defined radio testbed, not simulated.
Each run directory carries a `run_info.yaml` and a `timeline.ndjson` with exact timing, hardware serials,
configuration, and ground-truth events (attach, each IQ burst, teardown). The IQ and the base-station and
phone metrics are simultaneous observations of the same live cell.

## Runs

| run_id | duration | band / carrier | UE | label |
|---|---|---|---|---|
| `2026-10-15T1621Z_poco-n41-phy` | 20 min (2026-10-15 16:21:52–16:42:00 UTC) | n41 TDD, ARFCN 518670 = 2593.35 MHz, 20 MHz, 30 kHz SCS | Xiaomi Poco (COTS phone) | benign single-cell baseline |

### Testbed for this run

- **Core**: Open5GS (standalone 5G core), PLMN 99970.
- **gNB**: srsRAN Project (release 25.10), PCI 1, on a USRP B210.
- **UE**: a real Xiaomi Poco phone, SIM on PLMN 99970, attached over the air and kept RRC-connected with
  light background traffic.
- **Sniffer**: a second USRP B210 tuned to the same 2593.35 MHz carrier, recording raw IQ while the cell ran.

## Directory layout (per run)

```
<run_id>/
  tier1_iq/        raw IQ bursts (.sc16) + SigMF sidecars (.sigmf-meta)
  tier2_metrics/   gnb_sched_ue.csv, ue_nr_adb.csv, ue_adb.ndjson
  pcap/            gnb_mac.pcap (MAC-NR), gnb_ngap.pcap (NGAP + 5G NAS)
  logs/            srsRAN console + srslog, per-burst sniffer logs, phone radio logcat, keepalive ping
  config/          exact Open5GS core and srsRAN gNB configs used
  meta/            final size report
  run_info.yaml    run metadata
  timeline.ndjson  ground-truth event timeline (UTC)
```

## Tier 1 — raw IQ (`tier1_iq/`)

Duty-cycled over-the-air capture of the live cell: a **2-second burst every 20 seconds** across the whole
run, so samples span the full session at a practical size. For the run above: 46 bursts, ~7.9 GB.

- `iq_<utc>_c<freq>_r<rate>.sc16` — interleaved signed 16-bit complex samples (I, Q, I, Q, …),
  little-endian. One 2-second burst = 46,080,000 complex samples = 184.32 MB. Sample rate 23.04 Msps,
  center frequency 2593.35 MHz.
- `iq_<utc>_c<freq>_r<rate>.sigmf-meta` — a [SigMF](https://github.com/sigmf/SigMF) metadata sidecar
  (`core:datatype: ci16_le`, sample rate, center frequency, hardware serial, UTC datetime, label).

Read one burst in Python:

```python
import numpy as np
x = np.fromfile("iq_….sc16", dtype=np.int16).astype(np.float32).view(np.complex64)
fs, fc = 23.04e6, 2593.35e6   # sample rate, center frequency
```

Typical uses: RF fingerprinting (carrier-frequency offset, IQ imbalance, phase noise), synchronization-signal
(SSB / PSS-SSS) analysis, spectrograms, and physical-layer inputs to a digital-twin or anomaly model.

## Tier 2 — PHY telemetry (`tier2_metrics/`, `pcap/`)

**`gnb_sched_ue.csv`** — per-UE physical-layer metrics from the base-station scheduler:

| column | meaning |
|---|---|
| `pci`, `rnti` | cell identity, UE radio identifier |
| `dl_cqi`, `dl_ri`, `dl_mcs`, `dl_brate` | downlink channel quality, rank, modulation-and-coding, bitrate |
| `dl_ok`, `dl_nok`, `dl_bler_pct` | downlink HARQ ACK / NACK and block error rate |
| `ul_pusch_snr`, `ul_rsrp` | uplink SNR and received power at the base station |
| `ul_ri`, `ul_mcs`, `ul_brate`, `ul_ok`, `ul_nok`, `ul_bler_pct` | uplink rank, MCS, bitrate, HARQ, BLER |
| `ul_bsr`, `ul_ta`, `ul_phr` | buffer status, timing advance, power headroom |

**`ue_nr_adb.csv`** — the phone's own NR radio measurements, polled every 2 seconds over adb:

| column | meaning |
|---|---|
| `ts`, `reg` | timestamp, registration state |
| `ss_rsrp`, `ss_rsrq`, `ss_sinr` | synchronization-signal received power, quality, SINR (the UE's downlink view) |
| `csi_rsrp`, `csi_rsrq`, `csi_sinr` | CSI-RS equivalents when reported |

`ue_adb.ndjson` is the raw per-poll source for that CSV. The `tier2_metrics/*.csv` are derived from the raw
logs and can be regenerated.

**Packet captures** (`pcap/`): `gnb_mac.pcap` is MAC-NR (per-transport-block MCS, grants, HARQ);
`gnb_ngap.pcap` is NGAP control plane and contains the **5G NAS (5GMM)** signaling, including the full
registration sequence (Registration Request, Authentication Request/Response, Identity Request/Response,
Security Mode Command). Read with Wireshark or `tshark -r gnb_ngap.pcap -Y nas-5gs`.

## Loading in `datasets`

The IQ files are binary and are referenced by their SigMF sidecars; load them with NumPy as shown above. The
CSV metrics are exposed as dataset-viewer configs:

```python
from datasets import load_dataset
gnb = load_dataset("<your-username>/Twin6G", "gnb_metrics")  # per-UE PHY metrics
ue  = load_dataset("<your-username>/Twin6G", "ue_nr")        # phone-side NR measurements
```

## Intended uses

- Physical-layer feature extraction and RF fingerprinting of 5G base stations.
- Training and validating digital-twin / anomaly models on real radio telemetry.
- Fusing physical-layer features with higher-layer (NAS / RRC) detectors, for example to reduce false
  positives in fake-base-station detection.

## Limitations and honest notes

- **Benign only.** This run is a single legitimate cell. It is **not** a fake-base-station capture; that
  requires a separate two-transmitter benign-versus-fake handover scenario.
- **IQ is duty-cycled**, 2 seconds every 20 seconds. It spans the full run but totals about 92 seconds of
  samples per 20-minute run, not continuous. This bounds storage and avoids radio contention with the live
  cell.
- A minority of IQ bursts logged a transient hardware overflow (a few dropped samples at the start of the
  burst). Files are full-size and usable; the per-burst sniffer logs in `logs/` record which bursts.
- Identifiers are test values on a private PLMN (99970). Subscriber keys are not included; the UE config in
  `config/` has credentials stripped.

## Citation

Part of the Twin6G project (digital twin for 5G/6G). If you use this dataset, please cite the project and
link this repository.