随着无线业务的爆炸性增长，其对频谱资源的需求也越来越大。认知无线网络可以提高频谱利用率，是在频谱资源紧缺的环境下满足频谱需求的有效途径。然而，由于认知无线网络中的频谱具有变化性、多样性和差异性，传统信息分发算法在该场景中面临着可靠性下降、冗余增加、时延变长等新问题。.本项目拟针对以上问题，将环境建模、算法优化与理论分析相结合，自底向上研究和建立动态频谱环境下的认知无线网络信息分发机制。其目标是增强信息分发的可靠性、降低传输冗余、减少时延，以有效提高网络性能。具体内容包括：1、结合频谱的动态特征对频谱环境进行精确建模；2、结合动态频谱接入策略与线性网络编码设计高可靠的信息分发算法; 3、在集合覆盖和冲突图等理论模型的基础上，结合层次化虚拟主干分发和冲突避免技术，研究动态频谱环境下信息分发冗余和时延优化策略；4、研究可靠性、冗余和时延三者之间的量化关系，探索信息分发性能优化和容量的理论最优值。

With the explosive growth of the wireless business, the demand for spectrum resources is growing as well. Cognitive wireless network can improve the spectrum utilization, and it is an effective way to meet the demand for spectrum when the spectrum resources are scarce. However, traditional information dissemination algorithms lead to low reliability, high redundancy and long latency if used in cognitive wireless networks since the spectrum in cognitive wireless networks is variable, diverse and differential. .To address these problems, this proposal plans to combine the environment modeling, algorithm optimization and theoretical analysis to study and establish the information dissemination mechanism of cognitive wireless networks in dynamic spectrum environment from the bottom up. The goal is to enhance the reliability, lower the transmission redundancy and reduce the latency, thereby improving the network performance effectively. The details are as follows. First, we model the dynamic spectrum environment accurately combined with dynamic characteristics; Second, we plan to employ the technologies of dynamic spectrum access strategy and linear network coding to design high-reliable information dissemination algorithm. Third, based on the theory of set cover and the interference graph, we conduct research on the optimization of redundancy and latency for information dissemination in dynamic spectrum environment using the hierarchical virtual backbone dissemination and collision avoidance technologies; Finally, we study the quantitative relationship among the reliability, redundancy and latency. Then, we would also like to explore the theoretical optimal value on the performance optimization and capacity of the information dissemination.