Spectrum sensing is an essential enabling functionality for cognitive radio
networks to detect spectrum holes and opportunistically use the under-utilized
frequency bands without causing harmful interference to legacy networks. This
paper introduces a novel wideband spectrum sensing technique, called multiband
joint detection, which jointly detects the signal energy levels over multiple
frequency bands rather than consider one band at a time. The proposed strategy
is efficient in improving the dynamic spectrum utilization and reducing
interference to the primary users. The spectrum sensing problem is formulated
as a class of optimization problems in interference limited cognitive radio
networks. By exploiting the hidden convexity in the seemingly non-convex
problem formulations, optimal solutions for multiband joint detection are
obtained under practical conditions. Simulation results show that the proposed
spectrum sensing schemes can considerably improve the system performance. This
paper establishes important principles for the design of wideband spectrum
sensing algorithms in cognitive radio networks