针对IEEE 802.11e EDCA(enhanced distributed channel access)支持业务区分服务的特点,提出了一个基于AIFS(arbitration inter-frame space)区分的信道吞吐率分析模型,该模型将不同接入等级的业务统一到一个信道模型中进行分析.通过数值计算结果与仿真实验结果的对比,验证了该模型的准确性,尤其是在分析信道吞吐率方面更优于Xiao 的Markov 链模型.根据提出的分析模型,研究了近似优化条件,使得各类优先级业务的发送概率平衡虚拟发 送时间段中空闲时间与冲突持续时间对系统性能的影响,实现靠近最优的信道吞吐率,从而使计算复杂度大为减小. 利用数值分析的方法验证了近似优化条件实现靠近最优信道吞吐率的可行性.最后,提出的DPS(dynamicparameter-tuning scheme)算法根据负载情况自适应地调整不同级别业务的相应参数,使得系统时时满足优化条件,在各种场景下都能实现最大信道吞吐率,同时又满足EDCA 支持QoS 区分的要求.仿真结果验证了DPS 算法不仅能够根据竞争节点的数目变化对信道吞吐率进行优化,而且其性能也明显优于标准的IEEE 802.11e EDCA 机制.;This paper proposes an AIFS-based multi-class model to study the saturation channel throughput on the basis of the operation mechanism of IEEE 802.11e EDCA (enhanced distributed channel access) supporting servicedifferentiation. The proposed model is calculated numerically and validated against simulation results, a good matchbetween the analytical model and simulation is observed. In particular, this paper compares the proposed modelwith Xiao’s Markov chain model under the same configures. Based on the proposed model, this paper researches thequasi-optimal condition to avoid the computational complexity but still maintain the channel throughput close to itsoptimal value. Finally, the paper proposes an adaptive p-persistent MAC scheme, named DPS (dynamicparameter-tuning scheme), to assign appropriate different transmission probabilities (or contention window size) of different classes. Through DPS, it is feasible to provide service differentiation and achieve targeted throughput ratioamong different classes, at the same time to maximize the total channel throughput. Simulation and numericalresults show that DPS can effectively achieve the performance goal under a variety of network conditions, and achieve higher channel throughput than standard IEEE 802.11e EDCA in all different environments.