In a wireless network, transmitter locations strongly impact achievable rates. Cellular deployment is a difficult non-convex problem, typically addressed using simplified models and heuristics. We propose a mathematically rigorous framework incorporating detailed site-specific maps, material properties, and realistic attenuation. We introduce an aggregated network-quality functional scoring receiver-weighted signal quality, impose deployment costs via cardinality and budget constraints, and establish submodularity under practical conditions. To solve the optimization problem, we propose the Interference-Aware Submodular Placement Algorithm (IA-SPA) with a theoretical approximation guarantee relative to the optimum. IA-SPA incorporates existing base stations and prohibited areas, making it applicable to clean-slate and incremental deployments. We evaluate our approach using ray-tracing simulations on 3D maps of San Francisco and Florence, comparing against known deployments by AT and T, T-Mobile, and Iliad. Our strategy achieves significant increases in mean data rate (about 2x) and edge rate (2-8x) using the same number of transmitters. These gains persist under simultaneous exclusionary zones, small-scale fading, material/geometric perturbations, and incremental densification of existing networks. The pipeline has linear computational dependence on candidate sites, and wall-clock measurements demonstrate practical runtime at city scale.

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