摘要
智能天线是利用数字信号处理技术，产生空间定向波束，使天线主波束对准期望用户信号到达方向，旁瓣或零陷对准干扰信号到达方向，达到充分高效利用移动用户信号并删除或抑制干扰信号的目的。智能天线技术利用了空域信息，可以更有效地抑制多址干扰，又与现有的技术(FDMA、TDMA、CDMA)完全兼容，因此可以成倍地增加移动通信系统的容量，现在已经成为第三代移动通信系统的关键技术之一。
本文首先阐述了智能天线和自适应波束形成的基本理论，并简要地介绍了几种适用于CDMA系统的典型的自适应算法，但它们存在复杂度高的缺点，实用价值不大。在此基础之上作者给出了两种新的、计算量相对较小的、适用于DS-CDMA系统的盲波束形成算法，并对算法进行了大量的仿真及性能分析。一种是基于最大信噪比准则的算法，该算法适用于CDMA系统的处理增益比较大，即解扩以后期望用户信号远大于干扰信号的情况；另一种是基于最大信干噪比准则的算法，该算法在强干扰存在的情况依然有较好的性能。在论文的最后一章，介绍了数字信号处理器(DSP)的相关知识，并用处理速度为100MIPS的TMS320C5402芯片实现了上述两种算法，对算法的实时性进行了分析和研究。本文的工作具有很强的工程应用价值，并对今后的理论研究有一定的指导意义和参考价值。
Digital signal processing technologies were used to produce spatial and directional beam in smart antennas. Then the main beam aims at the coming direction of reference user and the side lobe points to the coming direction of interference user. The Smart Antenna Systems (SAS) has become one of the key techniques of the Third Generation Mobile Communication Systems (3G) for its advantages on multiple access interference (MAI) suppression by using spatial information. It can be compatible with the present techniques (TDMA, FDMA and CDMA), and can remarkably improve the performance and the capacity of communication systems.
In this paper, firstly, the author illustrates the principles of smart antenna and adaptive beamforming, and then introduces some typical adaptive algorithms used in CDMA systems, but they have the disadvantage of high complexity, so they are not fit for practice. Based on these works, the author proposes two novel, low computational load DS-CDMA uplink blind beamforming algorithms, simulates the algorithms and analyses the performance. One of which is based on the maximum signal-to-noise ratio (MSNR) criterion, it can improve the performance of the array system only when the processing gain of the given CDMA system is high enough such that the desired signal can become dominant after dispreading. The other is based on the maximum signal-to-interference- plus-noise ratio (MSINR) criterion, and it has well performance when strong interferers occur. In the last chapter, the author introduces some knowledge of Digital Signal Processor (DSP), and in order to research the real-time performance, the author implements the above algorithms on TMS320C5402 DSP chip, and its processing speed is 100MIPS. It is of great value in engineering application and is a good guide to theory study in the future.
引文
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