Energy Efficient Sequential Sensing for Wideband Multi-channel Cognitive Network

Abstract—Recently, cognitive network is receiving more atten-tion due to its capability of enabling dynamic spectrum usage. When the dynamic spectrum is wide-band, a sequential sensing scheme, which divides the whole spectrum into multiple sub-channels and senses them successively, is always adopted. Con-ventionally, parameters such as sampling rate and the bandwidth of each sub-channel are empirically configured. However, when energy consumption is considered, we should pay closer attention to the new tradeoff balance involved in parameters optimization. It shows that sampling rate of A/D & D/A convertor (ADC & DAC) greatly affects the energy consumption of a cognitive handset, which impacts on detection probability as well. To figure out the optimal parameters of sequential sensing, we establish Energy Optimization and Detection Optimization problems based on the relationship among energy consumption, sampling rate and detection probability. By exploring the convex property of energy consumption function and monotonic decreasing property of detection probability function in terms of sampling rate, we obtain the optimal sampling rate of a practical cognitive handset utilizing AD9051 chip set (ADC). Numerical results are given to investigate the impact of sampling rate on energy consumption and detection probability. It shows that the optimal sampling rate will bring up to 50 % energy saving and 3 times detection probability improvement