非正交多址接入系统中基于受限马尔科夫决策过程的网络切片虚拟资源分配算法

针对无线接入网络切片虚拟资源分配优化问题，该文提出基于受限马尔可夫决策过程(CMDP)的网络切片自适应虚拟资源分配算法。首先，该算法在非正交多址接入(NOMA)系统中以用户中断概率和切片队列积压为约束，切片的总速率作为回报，运用受限马尔可夫决策过程理论构建资源自适应问题的动态优化模型；其次定义后决策状态，规避最优值函数中的期望运算；进一步地，针对马尔科夫决策过程(MDP)的“维度灾难”问题，基于近似动态规划理论，定义关于分配行为的基函数，替代决策后状态空间，减少计算维度；最后设计了一种自适应虚拟资源分配算法，通过与外部环境的不断交互学习，动态调整资源分配策略，优化切片性能。仿真结果表明，该算法可以较好地提高系统的性能，满足切片的服务需求。

Network Slice Virtual Resource Allocation Algorithm Based on Constrained Markov Decision Process in Non-orthogonal Multiple Access

An adaptive virtual resource allocation algorithm is proposed based on Constrained Markov Decision Process (CMDP) for wireless access network slice virtual resource allocation. First of all, this algorithm in the Non-Orthogonal Multiple Access (NOMA) system, uses the user outage probability and the slice queues as constraints, uses the total rate of slices as a reward to build a resource adaptive problem using the CMDP theory. Secondly, the post-decision state is defined to avoid the expectation operation in the optimal value function. Furthermore, aiming at the problem of " dimensionality disaster” of MDP, based on the approximate dynamic programming theory, a basis function for the assignment behavior is designed to replace the post-decision state space and to reduce the computational dimension. Finally, an adaptive virtual resource allocation algorithm is designed to optimize the slicing performance. The simulation results show that the algorithm can improve the performance of the system and meet the service requirements of slicing.