无线网络中的链路自适应算法

针对无线链路固定传输模式吞吐量低，而基于单参数的链路自适应可能误判的问题，提出了一种可有效提高无线网络吞吐量的基于多信道参数信息融合的链路自适应算法。算法根据信道参数的特点，分别采用神经网络在线预测和模糊逻辑推理算法实现载干比(CIR)、包错误率(PER)和信噪比(SNR)对信道质量的局部评估，经过融合中心的合成运算和决策规则，获取信道质量的全局判决，以此进行最适应信道状态的物理层传输模式选择。仿真结果表明，当信道状态恶化时，平均吞吐量比固定传输模式和基于单参数的链路自适应算法提高了42.9%和28.4%。

Link Adaptation Algorithm for Wireless Local Area Network

An effective link adaptation algorithm based on multi-information fusion is presented for wireless local area network(WLAN),in which the neural network(NN) predictive control algorithm on line and fuzzy logic reasoning and inferring algorithm are adopted to make part judgement about the channel quality based on the channel parameter of signal noise ratio(SNR) and carrier to interface ratio(CIR) and packet error ratio(PER).The best physical layer mode is selected with the decision which is obtained through the synthetic operation and decision rule of the information fusion center.The simulation results show that the proposed algorithm can increase throughput,especially,the network throughput enhances 42.9% and 28.4% compared with the other when the channel quality is bad.