中文摘要：

针对无线网络的传输问题，提出了一种适用于无线网络的智能传输调度方案，在马尔可夫决策过程（MDP）的基础上构建了系统模型，通过形学习算法的引入，中继节点对缓存器储存状态及信道质量进行学习，从而在信息数据包的传输过程中智能地选择数据包传输对象及数据包传输方式来达到在节省能量损耗的前提下尽量减少数据包丢失的目的。通过状态聚合方法解决因状态空间过大而导致的维灾问题，同时采用了行动集缩减来以减少某些状态对应的行动数，利用这些简化方法可以发现逐次逼近法的存储空间压缩率为41％，矽学习算法的存储空间压缩率为43％。最后，系统仿真结果表明，提出的传输调度方案可以在节省能耗的基础上尽量地传输数据，减少了数据包的丢失，同时采取的状态聚合法及行动集缩减在有效地简化计算的同时并没有影响算法的性能。

英文摘要：

To solve the problem of transmission in wireless networks, a transmission and scheduling scheme based on W- learning algorithm in wireless networks was proposed in this paper. Building the system model based on Markov Decision Progress （MDP）, with the help of W-learning algorithm, the goal of using this scheme was to transmit intelligently, namely, the package loss under the premise of energy saving by choosing which one to transmit and the transmit mode legitimately was reduced. The curse of dimensionality was overcome by state aggregate method, and the number of actions was reduced by action set reduction scheme. The storage space compression ratio of successive approximation was 41%; the storage space compression ratio of W-learning algorithm was 43%. Finally, the simulation results were given to evaluate the performances of the scheme, which showed that the proposed scheme can transport data as much as possible on the basis of energy saving, the state aggregation method and the action set reduction scheme can simplify the calculation with little influence on the performance of algorithms.