Designing a Cloud-Based Infrastructure for Spectrum Sensing: A Case Study for Indoor Spaces

TLDR: It is argued that spectrum sensing on mobile clients will be both necessary and feasible if the authors wish to manage the white space spectrum optimally in indoor spaces and the feasibility is demonstrated by building a spectrum sensing infrastructure that collects measurements from sensing devices to analyze and better use spectrum resources.

Abstract: We argue that spectrum sensing on mobile clients will be both necessary and feasible if we wish to manage the white space spectrum optimally in indoor spaces. We demonstrate the necessity with a set of empirical measurements showing the need for fine grained sensing. We demonstrate the feasibility by building a spectrum sensing infrastructure that collects measurements from sensing devices to analyze and better use spectrum resources. The infrastructure consists of mobile spectrum sensors that are built using DTV receiver dongles interfaced with Android-based mobile devices and a cloud-based central server to manage such sensing devices. We also show results about resource consumption (energy, network overhead) involved in operating such sensors. The vision is ultimately creating a system where mobile devices perform part-time spectrum sensing in a coordinated fashion under the control of a central spectrum manager. We lay out the research challenges based on our initial prototyping and benchmarking experience.