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ERDT: Energy-efficient Reliable Decision Transmission for Intelligent Cooperative Spectrum Sensing in Industrial IoT

Correct decision probability Pe of ERDT and DT with N=10

 

Due to harsh environment, large number of sensors, limited energy, and spectrum scarcity, intelligent sensing becomes a key issue to enable many practical applications in industrial Internet of Things (IoT). In such an industrial environment with noise and interference, an efficient cooperative spectrum sensing (CSS) scheme can achieve spectrum sharing between primary users (PUs) and secondary users (SUs), and effectively solve the spectrum scarcity and reduce energy consumption to make the IoT smarter. As a vital part of CSS, decision transmission (DT) between SUs and fusion center (FC) plays a crucial role. In traditional DT, each SU will transmit its local decision to FC with orthogonal channel in each sensing, which does not consider the packet error and packet loss due to noise during transmission, and aggravates spectrum scarcity and energy consumption. An energy-efficient reliable DT (ERDT) scheme is proposed to enhance CSS in industrial IoT, which considers both packet error and packet loss. First, the CSS mathematical model based on DT is formulated. Second, with rigorous mathematical deduction, the correct decision probability and the energy consumption are analyzed for both ERDT and DT based on logic OR-rule and AND-rule under three cases, respectively: 1) bit error only; 2) packet loss only; and 3) both bit error and packet loss. Detailed simulation results show that, compared with DT, the proposed ERDT can increase correct decision probability and reduce energy consumption for CSS under three different cases. When the existence probability of PU is 50%, the energy consumption of ERDT is only half of that of DT in CSS. Furthermore, when there are 30 SUs in CSS, the existence probability of PU is 50%, both pocket loss rate and bit error rate are 0.05, and the correct decision probability of ERDT is approaching to 1 for CSS in industrial IoT.

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