Private 5G Has a Location Problem, and It's About Spectrum

On a factory floor, a port, a hospital, or a large construction site, private 5G is supposed to do more than carry data. It is supposed to make the operation visible: where every asset, vehicle, and worker is, continuously and accurately. Location-based services are roughly 80% of the business case for why enterprises roll out private 5G in the first place.

Private 5G networks can't deliver that location without ZaiNar, and the main reason is spectrum.

Conventional 5G positioning was built for spectrum you don't have

Conventional 5G positioning runs on dedicated signals: PRS on the downlink and PSRS on the uplink. Those signals need at least 100 MHz of bandwidth. Private networks don't have it: globally, private 5G is legally allotted between 10 and 40 MHz, depending on where you are in the world. And putting a phone on everything you want to track is too expensive, so enterprises connect equipment through reduced-capability (RedCap) 5G devices that run on 20 MHz or less, a tier no conventional positioning approach works on even in public networks.

The result is that there is no positioning on private 5G at all. The best the network can do is tell you that a device is on it. For scale: public cellular positioning today lands around 100 to 200 meters, and even the top vendors' 6G simulations promise only 30 to 50 meters in perfect line of sight, on the full 100 MHz a private network doesn't have, on networks that are still years away.

The high-accuracy workaround is a dead end

The proposed cellular methods that do reach 1 to 5 meter accuracy need that same 100 MHz of public spectrum plus the device in range of three separate base stations within a 50 meter radius. That is not how anyone deploys a network. Those methods also lean on signal strength and angle of arrival, which don't scale and falter as the environment changes, so even that accuracy doesn't hold: shelves fill up with inventory in a warehouse and the numbers drift. At that density and that fragility, it is cheaper and more accurate to put ultra-wideband anchors on the walls instead.

The positioning signal was already there

ZaiNar computes position from SRS, the Sounding Reference Signal devices already transmit on the uplink for normal network operation. It is a connectivity signal, not a positioning one, which means it is always there, reliable, and scalable. The computation happens network-side, in standards-compliant software on the infrastructure. No dedicated positioning signal, no anchors, no new hardware or software on the tracked device.

ZaiNar just needs to detect the signal. It does not care how strong the signal is or what angle it comes from, which is why it delivers centimeter-level accuracy, and can operate on less than 10 MHz of spectrum, the spectrum every private network actually has available. That makes ZaiNar the only viable 5G positioning approach within private-network and RedCap constraints. And this is not a simulation result. ZaiNar runs in production today, including at sites tens of meters underground surrounded by solid metal, holding centimeter-level accuracy.

The device does nothing new

Conventional cellular positioning makes the device work for its own location, spending battery to transmit positioning signals or to measure and report them. A ZaiNar-positioned device transmits the same SRS it was already transmitting to stay connected. No added battery drain, no new silicon, no app. The computation is cheap on the network side too: ZaiNar computes a location with 100x less compute per location update than conventional cellular positioning methods, which is what makes continuous positioning across every device on the network economical to run.

Once per second only works standing still

PRS or PSRS 5G positioning is capped at one location update per second, so it cannot support moving objects: drones, cars, robots. That is fine for inventory that sits still. A vehicle driving at 10 meters per second gets one location update every 10 meters. The SRS that ZaiNar reads is sent at least 100 times per second and up to 500, so ZaiNar supports moving objects, even very fast ones.

4x the range of cell service

Because ZaiNar only needs to detect the signal, positioning holds to at least 4x the range of cell service, out to multiple kilometers, with no accuracy loss at longer range. No one has to add base-station density to get positioning coverage, on private networks or public ones. That makes ZaiNar not just the only option inside these constraints, but the only scalable one.

Built in, not bolted on

Add it up. Every other cellular positioning approach needs spectrum private networks don't have, dedicated signals devices pay for in battery and compute, base-station density nobody builds, and only delivers a maximum of one location update per second. ZaiNar delivers centimeter-level positioning from the signals already on the network, can operate on networks that have less than 10 MHz, at 100 to 500 updates per second, at kilometers of range, with nothing added to the device.

And it is not built for one robot maker's hardware or one vendor's tags. Every device on the network gets the same treatment, no matter who makes it or whether it is a robot, a forklift, or a cell phone: one view of everything, with no software or hardware changes on any of them.

That is why ZaiNar pays off for the network. Once accurate, continuous location is built into private 5G rather than bolted on, it becomes an operating input rather than a dashboard nobody checks: utilization reports that show which rented machines sat idle for weeks, geofences that move with the equipment, workflows that trigger when the right asset, worker, or vehicle reaches the proper zone. Private 5G sales cycles shorten and the ROI of the network goes up 500%. That is the foundation layer for Physical AI across the enterprise site, running on the private network the enterprise already built. The missing piece was never another beacon system. It was positioning that fits the spectrum.