带缓存的云接入网络中最小化传输时延设计

Minimization of Transmission Delay Design for Cache-based Cloud-RAN

为了更好适应下一代通信网络以内容为中心的特性,在云接入网络(Cloud Radio Access Network,Cloud-RAN)中考虑射频拉远头(Remote Radio Heads,RRHs)具备缓存功能也变得必要。本文考虑在Cloud-RAN中设计优化算法,并通过有效设计缓存方案减少系统传输时延。基于混合式自动重传请求(hybrid automatic repeat request, HARQ)的重传机制,前程链路与下行链路频谱信道的正交性,系统采用马尔可夫链理论建立了最小化系统传输时延的优化问题。考虑只能通过递归方式得到优化目标函数表达式,头脑风暴优化(brain storm optimization, BSO)算法被引入解决非凸问题,仿真结果表明,该优化算法可以更有效地减少系统传输时延,满足未来通信需求。

To better adapt the content-centric feature of next-generation communication networks,it’s necessary to consider caching function for RRHs in Cloud-RAN.This paper intends to design the optimization algorithms and reduce the system transmission delay by designing suitable caching schemes.Based on the hybrid automatic repeat request(HARQ)retransmission mechanism,the orthogonality between the fronthaul link and the download link spectrum channel,the system employs the Markov chain theory to establish the minimization optimization problem of system transmission delay.Considering the optimization objective function expression could only be obtained recursively,the Brain Storm Optimization(BSO)algorithm is introduced to solve the non-convex problem and obtain the optimal caching scheme.The experimental results show that the algorithms proposed in this paper can effectively reduce the transmission delay of the system,which meets the requirements of communication system in the future.