针对不同应用场景的用户利用底层网络资源不充分的问题,提出一种利用网络切片技术对切片进行准入控制和资源分配联合算法(Joint Access Control and Resource Allocation Algorithm for Slicing,JACRAAS)。在第五代移动通信技术(5th Gen...针对不同应用场景的用户利用底层网络资源不充分的问题,提出一种利用网络切片技术对切片进行准入控制和资源分配联合算法(Joint Access Control and Resource Allocation Algorithm for Slicing,JACRAAS)。在第五代移动通信技术(5th Generation Mobile Communication Technology,5G)的演进(5G-Advanced,5G-A)标准下,通过最大化网络切片提供商(Network Slicing Provider,NSP)的收益,使用双深度Q网络算法对网络切片请求进行智能高效的准入控制和资源分配,并对重要经验优先回放,拒绝不满足条件的切片请求。同时,考虑网络拓扑对节点的影响,对重要节点优先排序,并进行节点映射和链路映射。仿真结果表明,所提算法与深度Q网络算法和Q学习算法相比,NSP收益成本比分别提高了9%和15%,资源利用率分别提升了10%和14%,所提算法可以显著提高底层资源的利用率。展开更多
Estimation of model parameter for transient signal is very important in many aspects. This paper presents a new Markov ARMA model Q-slice estimation algorithm for transient signal based on bispectrum. Simulation resul...Estimation of model parameter for transient signal is very important in many aspects. This paper presents a new Markov ARMA model Q-slice estimation algorithm for transient signal based on bispectrum. Simulation results show that this new method has some special features, such as higher estimation precision, lower amount of calculation, higher fitting effect even in lower signal-to-noise ratio (SNR) situation.展开更多
文摘针对不同应用场景的用户利用底层网络资源不充分的问题,提出一种利用网络切片技术对切片进行准入控制和资源分配联合算法(Joint Access Control and Resource Allocation Algorithm for Slicing,JACRAAS)。在第五代移动通信技术(5th Generation Mobile Communication Technology,5G)的演进(5G-Advanced,5G-A)标准下,通过最大化网络切片提供商(Network Slicing Provider,NSP)的收益,使用双深度Q网络算法对网络切片请求进行智能高效的准入控制和资源分配,并对重要经验优先回放,拒绝不满足条件的切片请求。同时,考虑网络拓扑对节点的影响,对重要节点优先排序,并进行节点映射和链路映射。仿真结果表明,所提算法与深度Q网络算法和Q学习算法相比,NSP收益成本比分别提高了9%和15%,资源利用率分别提升了10%和14%,所提算法可以显著提高底层资源的利用率。
文摘Estimation of model parameter for transient signal is very important in many aspects. This paper presents a new Markov ARMA model Q-slice estimation algorithm for transient signal based on bispectrum. Simulation results show that this new method has some special features, such as higher estimation precision, lower amount of calculation, higher fitting effect even in lower signal-to-noise ratio (SNR) situation.
