CityDeploy-Bench: Benchmarking Physics-Grounded Spatial Set Planning for Multi-Transmitter Network Deployment

Key points

• Automating city-scale wireless deployment remains challenging under complex urban propagation and network-wide interference.1
• The benchmark separates utility representation from planning dynamics, enabling controlled comparison between direct scalar rewards, relational models, and higher-order interaction structures across diverse planners.1
• This establishes multi-transmitter deployment as a coordination problem over physically interacting sets rather than a collection of independent spatial decisions.1
• We release CityDeploy-Data and the benchmark framework as a reproducible testbed for research linking decision learning with physically grounded wireless network design.1

Sources (1)

• [1]CityDeploy-Bench: Benchmarking Physics-Grounded Spatial Set Planning for Multi-Transmitter Network Deployment
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 01:25 AM

  We introduce CityDeploy-Bench, a benchmark that reframes multi-transmitter deployment as physics-grounded spatial set planning under a unified ray-tracing verifier.

  Automating city-scale wireless deployment remains challenging under complex urban propagation and network-wide interference.

Extractive summary: sentences quoted from the sources.