视频流量已成为移动互联网流量增长的主要部分，提高蜂窝网络的视频传输能力成为5G通信系统发展的重要任务。另一方面，异构蜂窝网络与缓存技术作为提高网络容量的重要手段，已成为满足未来 5G 网络需求所必须的关键技术。本项目拟开展基于缓存的异构蜂窝视频传输优化研究，构建针对视频数据和异构蜂窝网络特点的缓存与传输优化模型，设计高效的缓存与传输策略，满足用户服务质量需求。具体的研究内容包括：1）建立针对视频数据分层特点的缓存分配模型，设计高效的小基站非协作与协作缓存策略以减少用户的访问时间；2）在蜂窝网络传输干扰环境下，建立干扰冲突传输模型，研究基于干扰避免的编码广播传输策略和基于干扰容忍的传输调度策略，优化传输的信道资源和保证用户接收的公平性；3）构建基于视频数据层内编码和层间编码的异构蜂窝网络缓存与传输联合优化模型，研究联合优化策略与分布式解决方案，设计缓存与传输协议，最优化小基站服务用户的能力。

Video traffic has become a major part of the growth of mobile internet traffic, and improving the capacity of video transmission over cellular network has become an important task for the development of the 5G communication system. On the other hand, heterogeneous cellular networks and caching technology, as an important means to improve the network capacity, have become the key technologies to meet the requirements of the future 5G network. This project intends to carry out the research on optimization schemes of video transmission over cache-enabled heterogeneous cellular network, construct the caching and transmission optimization models based on the characteristics of video data and heterogeneous cellular network, and design efficient caching and transmission strategy to satisfy the quality of service requirements. Specific research contents include: 1) Establishing the caching assignment model for layered video data, and designing efficient non-cooperative and cooperative caching strategies for small base stations to reduce data access time of users; 2) Establishing the conflict transmission model when considering the transmission interference over the cellular network, and studying the interference avoidance based broadcast transmission scheduling with coding and interference tolerance based transmission scheduling strategy, to optimize the utilization of transmission channel resources and ensure the fairness of users; 3) Constructing the joint caching and transmission optimization model of heterogeneous cellular network based on the intra-layer and inter-layer encoding of layered video, studying joint optimization strategy and distributed solutions, and designing caching and transmission protocol, to optimize the service capacity of small base stations.