Opportunistic radio spectrum access: Collaborative spectrum sensing using custom RFICs and digital signal processing (DFG)
Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) technologies are based on opportunistic exploitation of radio resources and are considered as a solution to the spectrum scarcity problem, which is an inevitable pitfall of the traditional fixed radio resource allocation scheme. The opportunistic access practically means that certain portions of the radio spectrum, licensed to a primary user but in a given location temporarily unused or underutilized, could offer precious spectrum resources for emerging wireless systems such as CRs. Beside regulatory aspects related to the transition from conventional fixed radio allocation schemes to DSA, many technical challenges need to be resolved in order to accelerate its deployment. A capability to reliably identify available radio resources, referred to as spectrum sensing is among the most challenging ones. The latter is the main scope of this research, which aims to identify preeminent spectrum sensing strategies with the help of an experimental sensing network employing distributed sensing platforms with customized frontend Integrated Circuits (ICs) and baseband Digital Signal Processing (DSP). This objective will be approached in three phases:
1) In the first phase, a highly reconfigurable spectrum sensing platform will be developed. This phase covers design and implementation of two principal subsystems of the platform: a customized frontend RFIC operating from 100 MHz-6 GHz and a flexible baseband DSP unit with a bank of sensing algorithms.
2) Deployment of multiple spectrum sensing units is envisioned for the second phase of the project: several nodes with different hardware and software configurations will be used in a distributed sensing network in realistic environments and at the same time, spectrum usage data from individual nodes will be continuously stored in a regional long term spectrum usage database that will serve for testing and validation of sensing strategies in various communication scenarios.
3) In the third phase, effort will be put on processing of the data obtained from the developed distributed sensing network. Based on observations, algorithmic aspects related to decision making will be investigated and a set of specific decision strategies will be developed, taking into account a rigorous noise analysis, decision threshold optimization or game theory aspects (uncoordinated networks) as well as hard decision strategies (centralized networks).
Unlike other research efforts that investigate CR only from communications engineering or networking point of view, we propose complete investigations relying on results from an experimental distributed sensing network that takes into account limitations, benefits and mutual interactions of both, a wideband RF frontend and baseband DSP placed in real-world propagation environments. As a result, the developed sensing and decision strategies are expected to be realistic and applicable to real network scenarios.