# Joint Communication and Sensing: How 6G Will Use Cellular Signals as Radar

For decades, communications and radar have lived in separate worlds. Different waveforms, different hardware, different teams. 6G changes that. Joint Communication and Sensing (JCS), also called Integrated Sensing and Communication (ISAC), is one of the few 6G capabilities that has moved from academic papers into 3GPP study items with real momentum.

If you're working on 5G-Advanced today, you should already be tracking this. The transition isn't theoretical anymore.

What JCS Actually Is

The core idea: a base station transmits an OFDM waveform. That waveform is designed to carry data to UEs. But the same transmission also reflects off objects in the environment — vehicles, people, drones, walls. The base station (or a cooperating receiver) captures those reflections and, by correlating transmit and receive signals, extracts range, velocity, angle, and micro-Doppler information.

In other words, your gNB becomes a bistatic radar that happens to also serve users.

This is not a new idea in research. The novelty is that mmWave and sub-THz waveforms used in 5G NR and proposed for 6G have radar-like properties baked in: wide bandwidth (good for range resolution), narrow beams (good for angular resolution), and high carrier frequencies (good for Doppler sensitivity).

Why OFDM Works as a Radar Waveform

Classical pulsed radar uses simple chirps or pulses optimized purely for sensing. OFDM was designed for data, but it has favorable properties for sensing:

  • Range resolution is determined by total bandwidth. A 400 MHz NR carrier gives you ~37 cm range bins. A 2 GHz sub-THz channel gets you under 8 cm.
  • Velocity resolution comes from coherent processing interval — basically how many OFDM symbols you process together. A few milliseconds of integration on FR2 gets you sub-m/s Doppler resolution.
  • Angle resolution scales with antenna aperture. Massive MIMO arrays at 28 GHz already deliver beamwidths under 5 degrees.

The processing chain is: take the received signal, equalize against the known transmitted symbols (you sent the data, so you know what was transmitted), apply a 2D FFT across subcarriers and symbols, and you get a range-Doppler map. Beamforming weights give you angle.

The trade-off is sensitivity. A pulsed radar concentrates energy. OFDM spreads it. So JCS systems work well for short-to-medium range targets but won't replace dedicated long-range surveillance radar.

3GPP Activity in Release 19 and Beyond

3GPP closed the SA1 study on ISAC use cases (TR 22.837) in Release 19 and the RAN study item on ISAC channel modeling (TR 38.901 extensions) is the current battleground. The work splits into:

  • Mono-static sensing: TX and RX co-located at the gNB.
  • Bi-static sensing: TX at gNB, RX at another gNB or UE (or vice versa).
  • UE-assisted sensing: UE participates in transmission or reception of sensing signals.

Release 20 is expected to specify the first ISAC capability — likely starting with bi-static gNB-to-gNB sensing using existing reference signals. Don't expect a clean ISAC physical layer in Rel-20. Expect reuse of CSI-RS and SRS with extended configurations.

Use Cases That Will Actually Ship

Ignore the marketing decks. The use cases that pencil out for operators in the next five years are narrow:

  1. Drone and UAV detection. Regulators across Europe and APAC are pushing for cellular-based drone surveillance. JCS lets operators sell airspace monitoring as a service without deploying a separate radar network.
  2. V2X presence detection. Detecting pedestrians and cyclists at intersections from roadside gNBs, then alerting connected vehicles. Tighter latency than vision-based systems.
  3. Indoor occupancy sensing. Enterprise 5G networks detecting people in rooms for HVAC, security, and emergency response. No cameras, no privacy backlash.
  4. Intruder detection at perimeter sites. Substations, data centers, telecom facilities themselves. The base station already there does double duty.

Smart city traffic monitoring is the obvious one but operator economics on it are unclear.

Trade-offs Engineers Need to Understand

JCS isn't free. Real constraints:

  • Resource allocation. Sensing needs reference signals and processing time. Every sensing slot is a slot not serving data.
  • Receiver architecture. Mono-static sensing requires full-duplex or strong TX/RX isolation. Practically, most early deployments will be bi-static.
  • Privacy and regulation. Detecting people, even without identifying them, will trigger regulatory scrutiny in the EU. GDPR-class issues are real.
  • Channel model gaps. Sensing performance depends on accurate scatterer models. Existing 38.901 models were built for communication, not radar cross-section prediction.
  • Calibration drift. Bi-static systems need tight time and phase sync between nodes. PTP-grade timing — better than what most RAN sites have today.

What This Means for 5G Engineers Now

If you're optimizing 5G NR today, JCS shows up in your work in three ways:

  1. Site planning. Future ISAC deployments want sites at heights and orientations that aren't always optimal for coverage. Start asking the question on new builds.
  2. Timing and sync. PTP class C / enhanced timing isn't a luxury anymore. ISAC needs it.
  3. Reference signal density. Expect higher CSI-RS and SRS overhead in 5G-Advanced specifically to enable sensing precursors.

The specs are still moving. Vendor implementations diverge. Channel models are incomplete. But the direction is set: by 2030, the gNB you're commissioning will sense as well as it communicates.

Takeaway: JCS turns OFDM transmissions into radar — the technology works, 3GPP is actively standardizing it, and the engineers who understand it now will own the deployments in 2028.