【正文】 KNT? represent he event that there are K unlicensed users reporting 1bit decision and NK users not reporting to the mon receiver, respectively. The KiK pTP )](1[}{ 21 ??? ???? , KNiKN PTP ?? ??? )]([}{ 21` ???.and then the average number of sensing bits for our method can be derived as: ? ?? ? ?? ?????????????????? NK NK kNkKNkav g HTPHTPKNKPHTPHTPKNKPK 1 1 111039。 1H :primary user is present. For implementation simplicity, we restrict ourselves to energy detection in the spectrum sensing. The local spectrum sensing is to decide between the following two hypotheses: 01( ) , ,() ( ) ( ) ( ) ,n t Hxt h t s t n t H?? ? ??? (1) Where )(tx is the signal received by secondary user, )(ts is primary user’s transmitted signal, )(tn is AWGN, and )(th is the temporary amplitude gain of the channel. According to energy detection theory [7], we have the following distribution: ?????122022 ),(,~ HX HXmm ?? (2) Where ? is the energy value collected by secondary user,? is instantaneous SNR and follows exponentially distribution with the mean value _? , m is the time bandwidth product of the energy detector, 22m? represents a central chisquare distribution with 2m degrees of freedom and. )(22 ??m represents a noncentral chisquare distribution with m2 degrees of freedom and a noncentrality parameter ?2 . In conventional energy detection method, the local decision is made by paring the observation with a prefixed threshold as (a). When the collected energy ? exceeds the threshold ? , decision 0H will be made. Otherwise decision 1H will be made. In contrast, the system model which has two thresholds of our interest is shown (b). Where ― Decision 0H ‖ and ―Decision 1H ‖ represent the absence and the presence of licensed user, respectively.“ No decision‖ means that the observation is not reliable enough and the i th cognitive user will send nothing to the mon receiver. But when all the secondary users don’t send their local decisions, only the cognitive user with the highest reputation is selected to sense spectrum based on conventional energy detection method, and send its local decision to the mon receiver. Reputation is obtained based on the accuracy of cognitive user’s sensing results. The reputation value is set to zero at the beginning. Whenever its local spectrum sensing report is consistent with the final sensing decision, its reputation is incremented by one。 double threshold。 參考文獻 [1] Federal Communications Commission. Spectrum Policy Task Force, Rep. ET Docket no. 02135 [R]. Nov. 2020. [2] J. Mitola and G. Q. Maguire. Cognitive radio: Making software radios more personal[C],IEEE Personal Communication. vol. 6, pp. 13–18, Aug. 1999. [3] S. Haykin. Cognitive radio: brainempowered wireless munications [J]. IEEE J. Sel. Areas Communication. vol. 23, pp. 201–220, Feb. 2020. [4] AKYLDIZ IF. Next generation/dynamic spectrum access/cognitive radio wireless works: A Survey [J]. ELSEVIER Computer Networks, 2020(50):21272159. [5] D. Cabric, S. M. Mishra, and R. W. Brodersen. Implementation issues in spectrum sensing for cognitive radios[C]// in Proc. Of A silomar Conf. on Signals, Systems, and Computers, Pacific Grove,CA, USA, Nov. 710, 2020, pp. 772 776. [6] and E. S. Sousa. Collaborative spectrum sensing for opportunistic access in fading environments[C]// in Proc. 1st IEEES ymp. New Frontiers in Dynamic Spectrum Access Networks, Baltimore, USA, Nov. 8–11, 2020, pp. 131–136. [7] Chunhua Sun, Wei Zhang, Letaief . Cooperative spectrum sensing for cognitive radios under bandwidth constraints[C]// in Proc. IEEE WCNC, March 1115, 2020, pp. 15. [8] H. Urkowitz. Energy detection of unknown deterministic signals [C]. Proceedings of IEEE, , pp. 523531, April 1967. [9] Ruiliang Chen, JungMin Park, Kaigui Bian. Robust Distributed Spectrum Sensing in Cognitive Radio Networks[C]. in Proc. IEEEINFOCOM, April 2020, pp. 18761884. [10] F. F. Digham, M. S. Alouini, and M. K. Simon. On the energy detection of unknown signals over fading channels[C]. in Proc. IEEE ICC, Anchorage, AK, USA, May 1115, 2020, pp. 3575–3579.