Research of Sensing Points and Performance about Method of Energy Detection in HC-MAC

Method of energy detection decides the existence of primary user by collecting the signal energy, so the SNR and the sensing points affect the performance a lot. Our paper verifies the relationship between the sensing points and correct detection probability of the method of energy detection in different SNRs. The sensing mode of on-demand sensing policy (HC-MAC) is asynchronous, which only allows the node which want to transmit to sense the licensed channel, so the sensing time and data transmission time have much influence on the network performance. If under the high SNR environment, the more sensing points the node senses, the more precise the sensing result would be. It benefits data transmission. But one question is that sensing more points costs more time, the throughput would decrease. So there is a trade-off between the correct detection probability and throughput. Our goal is verifying the relationship between the sensing time and throughput, then we propose mathematical model and verify the model by simulating HC-MAC which is the abbreviation of Hardware-constrained Multi-Channel Cognitive MAC.