【作者】 王冰；

【导师】 刁鸣；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2008， 硕士

【摘要】 超宽带通信技术,是一种使用超宽的带宽、通过微弱的脉冲信号进行通信的无线技术。目前,由于其设备结构简单、极高的数据传输速率,以及功耗少、抗多径干扰能力强等优点已成为通信领域的一个重要发展方向。而多用户检测技术作为超宽带通信系统的关键技术之一,具有很重要的研究意义。多用户检测也可以看作是一个具有NP(Nondeterminstic Polynomial)复杂度的组合优化问题,因此可以将有效解决这类问题的智能优化算法应用于此。本文的主要研究内容是超宽带通信系统中的多用户检测技术。多用户检测技术具有极好的抗多址干扰和良好的抗远近效应的作用,还能够提高系统性能、增加系统容量。本文首先在理论上,从性能和计算复杂度等方面对跳时超宽带系统中的几种多用户检测算法进行了比较研究,并通过计算机仿真对比了它们的误码率。在文章的第四章,对群智能算法(主要是粒子群算法),进行了理论研究和仿真分析,针对传统的离散粒子群优化算法后期容易陷入局部收敛这一缺点,提出了一种新的离散粒子群算法,并将其应用到背包问题中证明其可行性。本文最后将群智能算法应用到超宽带多用户检测中,将其与其它算法进行比较,并通过计算机仿真对比了它们的误码率。更多还原

【Abstract】 Ultra-wideband(UWB)communication technology is a kind of wireless technology which uses ultra band and slender pulse to communicate.For the advantage of simple device,higher data rate and low probability of detection and fine multipath resolution capability ,the research on Ultra-wideband communication technology has become a significant developmental direction in communication field in recent years.As one of the key technologies in UWB communication system, Multiple User Detection(MUD) has important value in research.For the technology of MUD is known as a NP-hard problem in the combinational optimization,we can use meta-heuristic method which can resolve this kind of problems effectually to solve it.The central content of this thesis is the MUD technology in the UWB systems.The MUD technology is excellently immune to Multiple Access Interference (MAI) and good at near-far resistance, even enhances the performance and capacity of the systems.Theoretically from the performance and complexity,this thesis does some comparing research during several MUD algorithms in TH-IR systems, and compares their bit error rate (BER) by computer simulation.In the forth chapter,this thesis researches the Swarm Intelligence Algorithm(SIA)(particular in PSO) in theoritics study and simulative analyse. For traditional Discrete Particle Swarm Optimization (DPSO) has a disadvantage of local optimization, a Novel Discrete Particle Swarm Optimization (NDPSO) is presented,it has been proved effectual in solving the Knapsack Problem.In the end,the thesis uses SIA to solve the problem of MUD,and compares it with other MUD algorithms by computer simulation.更多还原