CRN中基于公平性的数据采集算法研究

Research on Data Gathering Algorithm Based on Fairness in Cognitive Radio Network

研究了认知无线电网络的分布式数据采集问题。首先讨论了SU的合适载波侦听范围(PCR)。以此PCR为基础,一个SU可以成功地发送数据且不对PU和其他SU造成干扰。然后,提出了一种兼顾公平性的异步分布式数据采集(ADDC)算法。ADDC算法以分布式策略把快照数据收集到基站,且没有任何时间同步要求。与集中式和同步式算法相比,ADDC算法的可拓展性和实用性更强。全面的仿真实验结果表明,ADDC算法的数据采集效率更高,数据采集时延更低。

The distributed data collection problem for CRN was studied, which has not been addressed before. First, the proper carrier-sensing range（PCR） for SU was studied. By working with this PCR, a SU can successfully conduct data transmission without disturbing the activities of PU and other SU. Subsequently, based on the PCR, an asynchronous distributed data collection （ADDC） algorithm with fairness consideration for CRN was proposed. ADDC collects data of a snapshot to the base station in a distributed manner without any time synchronization requirement. The algorithm is scalable and more practical compared with centralized and synchronized algorithms. The comprehensive theoretical analysis shows that ADDC is order-optimal in terms of delay and capacity, as long as SU has a positive probability to access the spectrum. Finally, extensive simulation results indicate that ADDC can effectively finish a data collection task and significantly reduce data collection delay.