关键词: 无线Mesh网络, 功率控制, 信道分配, Q学习, 差分进化

Abstract:

To solve the problem that the load which is carried by gateway node and that the network links in wireless Mesh network is imbalanced, a resource allocation model was constructed to optimize network weighted throughput by selecting the best gateway node and designing the weight on each link. A joint power control and channel assignment algorithm (QDJPCA) was proposed based on Q learning and differential evolution under the resource allocation model. In this algorithm, the channel assignment is achieved by obtaining the feedback results of power control, using the multiple mutations and adaptive crossover rate based differential evolution algorithm. In each iteration, to achieve power control, the Q learning algorithm based on state clustering and state correction is utilized on the channel assignment result. NS-3 simulation shows that the QDJPCA can not only effectively solve the proposed resource allocation model, but also improve the overall network performance through preferentially ensuring the gateway load balancing and throughput performance of heavy load link.

Key words: wireless Mesh network, power control, channel assignment, Q learning, differential evolution