Channel Correlation Assisted Fast Spectrum Sensing

To dynamically and efficiently utilize the vacant spectrum resources, cognitive radio is proposed as a potential solution, where spectrum sensing is one of the indispensable techniques. As one of the remaining issues in spectrum sensing, how to achieve the fast and energy efficient spectrum sensing in face of a wide band spectrum with an acceptable sensing accuracy is still a big challenge. Therefore, to reduce the spectrum sensing cost, a fast spectrum sensing scheme is proposed in this paper. Firstly, the channels of the same service are classified into highly correlated groups by a modified version of the greedy algorithm for set covering problem. In each group, only one representative channel (RC) is detected and the current busy-idle states of other channels, namely, estimated channels (EC), can be inferred according to their historical states and the current state of RC by the proposed joint Markov and channel correlation algorithm. Based on the real-time measurement results on GSM service and TV service in Beijing, the proposed scheme is proved and verified to be efficient on the premise of low estimated error.