Wireless network design software models radio frequency behaviour in a physical space so engineers can plan coverage and capacity before installing hardware. It combines a spatial model of the site, a propagation engine that predicts signal behaviour, and validation tools that compare the prediction against real measurements after deployment. Modern platforms cover Wi-Fi, cellular, DAS, fixed wireless and IoT from a single project model.
What it is. Software that predicts how wireless signal will behave in a specific building or outdoor area, then produces the design artefacts needed to buy, install and validate the network: hardware lists, coverage maps, cabling plans and engineering reports.
Who it is for. Wireless engineers, RF designers, system integrators, managed service providers, and the enterprise infrastructure teams responsible for connectivity in industrial and public environments.
Why it matters. Wireless design errors are expensive to discover late. A coverage gap found during commissioning means a return visit, re-cabling and sometimes re-procurement. Designing against a validated model moves that discovery to before the purchase order.
There are six stages. Every platform implements some subset, and the difference between tools is how many stages stay inside one model.
Import floor plans, BIM or IFC files, point clouds or geospatial terrain data. Set scale and real-world coordinates. Define walls, doors, windows and obstructions along with their material properties, because material determines attenuation.
Establish coverage thresholds, capacity targets, client device assumptions and demand distribution. A warehouse aisle and a stadium concourse have different requirements from the same square metre.
Select hardware, place radios, assign bands and channels, configure antennas and sectors, and plan cabling back to the IDFs.
Run propagation modelling to produce coverage and quality heatmaps. Read the right KPI for the question, whether that is RSSI, RSRP, SINR, RSRQ or throughput, and compare design alternatives against each other.
Collect walk test or drive test measurements after deployment and compare observed signal against the model. This is the step most often skipped, and the one that makes the model trustworthy next time.
Produce review-ready documentation, then monitor the deployed network against the design intent.
The dimensions below are the ones that separate platforms in practice. Confirm any vendor's current capabilities against their own documentation before you decide.
A modern platform should cover Wi-Fi, cellular including private 4G and 5G and CBRS, DAS, fixed wireless point-to-point and point-to-multipoint, and LoRa, across indoor, outdoor and multi-floor environments.
The limitation worth stating plainly: predictive modelling is a model. Accuracy depends on the fidelity of the site geometry and the material properties assigned to it. A floor plan traced at low fidelity, or walls assigned the wrong material, produces a confident-looking heatmap that is wrong. This is why field validation is a stage and not an optional extra, and why any accuracy claim that does not state its geometry assumptions should be treated sceptically.
NTT's Private Networks practice designs wireless infrastructure for enterprises across automotive, aviation, oil and gas, and industrial manufacturing.
Before eino, outdoor design required three separate tools: one for pre-sales, one for post-sales detailed engineering, and one for indoor. Nothing connected, so every won deal meant rebuilding the design from scratch. Detailed design also required purchasing per-project geodata covering clutter, terrain and building footprints, at $5,000 to $10,000 per project with a one to two week procurement cycle.
Consolidating onto eino removed both problems. Global terrain and clutter data is included, so the procurement cycle disappeared, and the same project carries from bid through final engineering.
As of July 2026: 100% of NTT's outdoor wireless designs run through eino, each project starts a minimum of one week earlier, and $5,000 to $10,000 is avoided per project.
That is the biggest point why everybody switched. It is not just the financial aspect. It is the time. I already have a head start of a week minimum.
Rahul Bangera, NTT
Ceragon launched its Private Networks business unit with eino as its design platform from day one, completing 191 wireless design projects and securing $10M in new contracts in under a year.
Design is predictive, modelling what coverage will be before hardware exists. A site survey is measurement, recording what coverage actually is. Design produces the plan and the survey validates or corrects it. Mature workflows use both, with survey data feeding back to improve the model.
Some can. Historically these were separate products with separate models, which is why converged sites often end up with two designs that never reconcile. Platforms built around a single site model handle multiple radio technologies against shared geometry.
Accuracy is bounded by input fidelity. Ray-traced propagation against accurate geometry and correct material properties is a reliable planning tool. The same engine against a poorly traced floor plan is not.
Outdoor propagation modelling needs terrain and clutter data. Some tools require you to license it per project, which adds cost and lead time. Others include it.
At minimum: coverage and quality heatmaps per band and KPI, an access point or radio schedule with configuration, a bill of materials, cabling and IDF assignments, and the design criteria the coverage was evaluated against.
Collect measurements, using an indoor walk test with waypoint positioning or an outdoor drive test with GPS, then overlay the measured data on the predicted heatmap to see where they agree and where they do not.
