Cooperative wideband spectrum detection based on Maximum Likelihood Ratio for cognitive VANET

Centralized cognitive Vehicular Ad Hoc Network (VANET) is a special VANET of vehicle-to-roadside (V2R) network that each vehicle could explore local spectrum gap and a central controller coordinates the spectrum for cognitive vehicles to realize dynamic spectrum access (DSA). In this paper, Maximum Likelihood Ratio (MLR) detection is proposed as the effective scheme for wideband spectrum detection in multi-carrier modulation based centralized cognitive VANET. Hard fusion process is implemented at central controller to make final decision by means of the combination of each vehicle´s local sensing result with special rules. Meanwhile, robust cooperative sensing technique is investigated with the consideration of sensing channel SNR and reporting channel error rate. Simulation results are presented to confirm our theoretical derivations. It is revealed that, compared with energy detection (ED), cooperative wideband spectrum detection with MLR scheme has adaptive features. It is available to adaptive robust cooperative sensing with dynamic threshold variations for centralized cognitive VANET.