本科层次中美合作办学计算机课程教学研究与探讨

本文以南京邮电大学与美国纽约理工学院本科层次上的合作办学为背景,分析了中美本科教学理念及方式的差异。并且以该合作项目中的计算机硬件课程＂Computer System Architecture＂为例,对中美合作办学中教学方式进行了研究与探讨。     

基于贝叶斯判决规则的异步合作频谱感知新算法

依据认知无线电中授权频谱占用情况的On-Off模型,提出了一种新型的合作频谱感知算法。该算法将次用户在不同时刻的软判决结果传输给数据融合中心,在考虑到不同认知节点具有不同信噪比的情况下,将On-Off模型求得的贝叶斯融合似然比作为感知权重对各认知用户的感知结果进行数据融合。理论分析与仿真结果表明,相比传统的同步合作感知算法,该算法具有合理性更强、可靠性更高、检测性能更优以及代价更少等优点。     

认知无线网络中频谱预测技术研究进展

随着无线网络业务的迅猛增长,稀缺的无线频谱资源成为制约无线通信技术发展的瓶颈。认知无线电技术通过对授权频谱进行二次利用的方法为缓解频谱资源匮乏与日益增长的无线业务需求之间的矛盾提供了一种十分有效的技术解决方案。频谱预测技术作为认知无线电的关键技术之一,其在降低系统能量消耗,提高系统灵敏度,降低频谱冲突及提高系统容量等方面发挥重要作用。为此,对认知无线网络中频谱预测技术的研究现状及最新进展进行较为全面和深入的研究,从频谱感知,频谱决策,频谱迁移及频谱共享等4个方面对频谱预测技术及其在认知无线网络中的应用进行了分析,并指出频谱预测技术未来的发展趋势及存在的挑战。     

Compressive Wideband Spectrum Sensing Based on Random Matrix Theory

Spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based compressive wideband spectrum sensing(ECWSS) scheme using random matrix theory(RMT) was proposed in this paper.The ECWSS directly utilized the compressive measurements based on compressive sampling(CS) theory to perform wideband spectrum sensing without requiring signal recovery,which could greatly reduce computational complexity and data acquisition burden.In the ECWSS,to alleviate the communication overhead of secondary user(SU),the sensors around SU carried out compressive sampling at the sub-Nyquist rate instead of SU.Furthermore,the exact probability density function of extreme eigenvalues was used to set the threshold.Theoretical analyses and simulation results show that compared with the existing eigenvalue-based sensing schemes,the ECWSS has much lower computational complexity and cost with no significant detection performance degradation.