标题: DS-CDMA/PRMA与DS-CDMA/FRMA第三代无线通讯系统之乏晰/类神经壅塞控制
Fuzzy/Neural Congestion Control for Third Generation DS-CDMA Cellular Systems
作者: 陈伯伟
Bo-way Chen
张仲儒
Chung-ju Chang
电信工程研究所
关键字: 分码多重撷取;封包预留多重撷取;时框预留多重撷取;通道撷取函数;乏晰通道撷取函数;乏晰撷取机率控制器;类神经撷取机率控制器;CDMA;PRMA;FRMA;channel access function;fuzzy channel access function;fuzzy access probability controller;neural-net access probability controller
公开日期: 1998
摘要: 在第三代无线通讯系统中,能否提供较大的频宽、较高的传输速率及传送多媒体资料已成为主要的设计考量。其中分码多工撷取 (CDMA) 的系统由于具有高度频宽使用效率、抵抗多路线干扰以及低功率传输的能力等,已成为未来无线通讯系统的一个选择。而对于直接序列-分码多工撷取 (DS-CDMA) 来说,系统的容量是受到多重撷取干扰限制的,如何去控制干扰量就是一个重要的课题。
在本篇论文中,我们首先在直接序列-分码多工撷取/封包保留多工撷取 (DS-CDMA/PRMA) 环境下使用乏晰逻辑 (fuzzy logic) 设计壅塞控制器。此控制器基于传统通道撷取函数 (channel access function) 的知识,给予使用者更适当的撷取机率 (access probability),使得传送失败率 (corruption ratio) 降低,因而有较好的表现。再来我们在直接序列-分码多工撷取/时框保留多工撷取 (DS-CDMA/FRMA) 环境中设计一个回授壅塞控制器。这个控制器包含了平行回路类神经网路 (pipeline recurrent neural network) 干扰预测器、乏晰效能指标器 (fuzzy performance indicator) 以及撷取机率控制器 (APC)。有了这个干扰预测器的帮助,对于系统干扰量的控制将会更有效。针对其中的撷取机率控制器我们提出了两种机制来设计,一为乏晰撷取机率控制器 (FAPC),另一为类神经网路撷取机率控制器 (NAPC)。藉由预测的干扰值及系统效能指标器的回授,乏晰撷取机率控制器与类神经网路撷取机率控制器可以恰当地调整撷取机率来控制竞争使用者的人数以使干扰量低于某个标准。由模拟的结果中,我们可以看到我们所设计的智慧型壅塞控制器在传送失败率、语音封包漏失率及系统使用效率上,都有较好的表现。
In this thesis, we study congestion control in DS-CDMA cellular systems. We propose a fuzzy technique for congestion control in DS-CDMA with PRMA (packet reservation multiple access) as its MAC (medium access control) protocol. We design a fuzzy congestion controller, named fuzzy channel access function (FCAF), based on knowledge from the channel access function (CAF) used in conventional DS-CDMA/PRMA cellular systems. We also design a fuzzy/neural congestion control for DS-CDMA/FRMA (frame reservation multiple access), where FRMA evolves from PRMA. FRMA separates the contention traffic from the reservation traffic so that the reservation traffic will not be disturbed by the contention traffic,
unlike PRMA. The fuzzy/neural congestion controller is constituted by a pipeline recurrent neural network (PRNN) interference predictor, a fuzzy performance indicator, and an access probability controller (APC). This APC can be either fuzzy access probability controller (FAPC) or neural-net access probability controller (NAPC). By taking more system
performance parameters into consideration, the access probabilities given by FAPC and NAPC can be more accurate. Simulation results show that the DS-CDMA/PRMA system with FCAF performs better than that with conventional CAF in overall performance. Furthermore, the DS-CDMA/FRMA system with fuzzy/neural congestion controller overrides the
DS-CDMA/PRMA system with CAF in the voice packet dropping ratio, the corruption ratio, the utilization, and data packet delay. This approach also outperforms the DS-CDMA/PRMA system with FCAF in the voice packet dropping ratio under medium traffic load, the corruption ratio and the utilization for all traffic loads. Moreover, NAPC outperforms FAPC. If
the requirement of the voice packet dropping ratio is set to be $10^{-2}$, the DS-CDMA/FRMA system with NAPC has an improvement of $10.76\%$ in capacity, the DS-CDMA/FRMA system with FAPC has $7.59\%$ improvement, and the DS-CDMA/PRMA system with FCAF has $5.06\%$ improvement, with comparison to the DS-CDMA/PRMA system with CAF.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT870435011
http://hdl.handle.net/11536/64469
显示于类别:Thesis