异构密集网络下基于POMDP负载感知的负载均衡算法研究

Load Balance Algorithm Based on POMDP Load-aware in Heterogeneous Dense Cellular Networks

针对异构密集网络场景中业务不确定性而引起的网络负载不均衡,该文提出一种基于部分可测马尔科夫决策过程(POMDP)负载感知的负载均衡方法。该方法首先通过对系统用户在感知周期内数据包传输数量进行观察,预测出下一周期系统可能出现的负载状态。其次根据负载感知结果动态调整小区范围扩展偏置值(DCRE),以达到优化系统整体负载均衡性的目的。最后采用启发式算法近似求解,能够快速得到次优解。仿真结果表明,该方案能在异构密集网络下提高系统负载均衡性,同时提升了系统吞吐量与系统资源利用率。

In order to solve the load imbalance problem caused by uncertainty of traffic in heterogeneous dense cellular networks, this paper proposes a load balance algorithm through small cell range expansion. The proposed algorithm is based on Partially Observable Markov Decision Process （POMDP）. By observing the packets of system user during the perceptual cycle, the next cycle system possible load state can be dopted. Then, the Dynamic Cell Range Expansion （DCRE） offset value is dynamically adjusted to take action in advance, reaching the purpose of optimizing the system load balance. To solve the problem efficiently, a heuristic algorithm is used to approximate and quickly get the suboptimal solution. Simulation results show that the proposed method can achieve load balance optimization in dense hetrogeneous network, and improve the system user throughput and resource utilization rate.