Guardbands are designed to insulate transmissions on adjacent frequencies from mutual interference. As more devices in a given area are packed into orthogonal wireless channels, choosing the right guardband size to minimize cross-channel interference becomes critical to network performance. Using both WiFi and GNU radio experiments, we show that the traditional "one-size-fits-all" approach to guardband assignment is ineffective, and can produce throughput degradation up to 80%. We find that ideal guardband values vary across different network configurations, and across different links in the same network. We argue that guardband values should be set based on network conditions and adapt to changes over time.

We propose Ganache, an intelligent guardband configuration system that dynamically sets and adapts guardbands based on local topology and propagation conditions. Ganache includes three key mechanisms: an empirical model of guardband sizes based on power heterogeneity of adjacent links, network-wide frequency and guardband assignment, and local guardband adaptation triggered by real-time detection of cross-band interference. We deploy a Ganache prototype on a local 8-node GNU radio testbed. Detailed experiments on different topologies show that to minimize interference, traditional fixed-size configurations allocate more than 40% of available spectrum to guardbands, while Ganache does the same using only 10% of the spectrum, leading to a 150% gain in throughput.