ITR: Sequential Signal Processing Methods for Third Generation CDMA Signals

信号处理是一个已经在当前GSM和is -95系统中发挥重要作用的领域。这一角色只会在预计的第三代无线通信中增加，事实上，实施这些系统的成功将在很大程度上取决于信号处理方法解决随之而来的新技术问题的能力。第三代系统的底层技术将基于宽带CDMA （WCDMA）调制方案。该技术的核心将是序列信号处理算法，该算法能够非常快速地捕获传输通道的快速变化特征，并最佳地利用已知的系统信息。尽管最新的CDMA信号处理方法取得了重大进展，但很明显，对比当前系统低得多的误码率的要求将显著增加对WCDMA信号顺序算法的信号处理能力的要求。由于需要处理高数据速率和高移动性用户而产生的复杂性，还会带来额外的挑战。由于通信信道将快速时变，信号将经历快速衰减，信道估计和跟踪，信道均衡，干扰抑制和rakerreceiver自适应的新算法必须具有极快的收敛速率。拟议研究的目标是开发算法，以满足这项新技术的挑战。所提出的WCDMA信号处理的基本方法将基于粒子滤波器，该方法因其在处理非线性和非高斯模型方面的潜力而受到广泛关注。这种滤波器设计的基本原理是用一组粒子（样本）来表示状态变量（系统的未知数）的后验分布。每个粒子都被赋予一个重要权重，这样粒子集合和它们的权重就代表了一个近似于期望的后验分布的随机度量。粒子也可以表示密度函数的平均值，通常是高斯函数，在这种情况下，粒子有附加变量，高斯函数的协方差。当新的信息可用时，这些粒子通过状态空间递归传播，并且使用贝叶斯理论的原理修改它们的权重。有几种应用粒子滤波器的方法，包括采样-重要性-重采样、混合卡尔曼滤波、蒙特卡洛和大都会-黑斯廷斯重要性重采样。这些方法在性能上各有优缺点，并且对实时实现提出了不同的要求。在该提案中，将研究新方案，自然地结合现有方案的最佳特性，并根据WCDMA信号的处理进行调整。新方案不仅能够复制或超越已知方法的最佳性能，而且它们也将具有足够的通用性，为开发新的任务特定方案提供基础。将调查四个重要主题。第一个是对状态粒子传播的基本方案的研究。这个问题至关重要，有两个重要原因：(a)它涉及算法的性能；(b)它包含了实现，虽然并行化，但在某些情况下计算要求太高，因此不太实用。第二个主题是特定任务，涉及多用户检测和信道估计，以及利用信道的物理特性和基站/移动不对称来开发改进算法。第三部分是检验所提出方法的灵活性以及各种算法和任务之间的相互作用，以提高它们的性能和鲁棒性。最后，第四个主题将涉及计算需求的调查，以及允许实时使用的结构。

Petar M. DjuricProject SummarySignal processing is an area that already plays a significant role in the current GSM and IS-95 systems.This role will only increase in the projected third generation wireless communications, and in fact, thesuccess in implementing these systems will strongly depend on the ability of the signal processing methodsto resolve the new technical problems that will emerge with it. The underlying technology of the thirdgeneration systems will be based on the wideband CDMA (WCDMA) modulation scheme. In the coreof this technology will be sequential signal processing algorithms with abilities to capture fast-changingcharacteristics of transmission channels very quickly and to exploit known system information optimally.The significant advances of latest CDMA signal processing methods notwithstanding, it is clear that therequirements for much lower bit error rates than in current systems will markedly increase the demands onsignal processing capabilities of sequential algorithms for WCDMA signals. Additional challenge arises dueto complexities that are a result from the need to handle high data rates and users with high mobility. Sincethe communication channels will be rapidly time varying, the signals will undergo quick attenuations and thenew algorithms on channel estimation and tracking, channel equalization, interference rejection, and RAKEreceiver adaptations must have extremely fast convergence rates. The objective of the proposed research isto develop algorithms that will meet the challenges of this new technology.The basic methodology for the proposed processing of WCDMA signals will be based on particle filters, which recently have gained much attention for their potential in handling nonlinear and non-Gaussianmodels. The underlying principle used in the design of such filters is the representation of the posteriordistribution of state variables (the unknowns of the system) by a set of particles (samples). Each particleis given an importance weight so that the set of particles and their weights represent a random measurethat approximates the desired posterior distribution. The particles may also represent means of densityfunctions, usually Gaussians, in which case the particles have additional variables, the covariances of theGaussians. As new information becomes available, these particles propagate recursively through the statespace and their weights are modified using the principles of Bayesian theory. There are several ways ofapplying particle filters including sampling-importance-resampling, mixture Kalman filtering, and MonteCarlo and Metropolis-Hastings importance resampling. These approaches have their advantages and disad-vantages in performance, and impose different demands for real-time implementation. In the proposal, newschemes will be studied that naturally combine the best features of the existing schemes, and tailor themfor processing of WCDMA signals. Not only will the new schemes be able to replicate or surpass the bestpossible performance of the known methods, but they will also be general enough to provide foundations fordevelopment of new task specific schemes.Four important topics will be investigated. The first is the examination of fundamental schemes forpropagation of state particles. This issue is critical for two important reasons: (a) it aspects the performanceof the algorithm and (b) it subsumes the implementation, which although parallelizible, is in some cases toocomputationally demanding and therefore not too practical. The second topic is task specific and is relatedto multiuser detection and channel estimation as well as exploitation of the physical characteristics of thechannel and the base station/mobile asymmetry for development of improved algorithms. The third oneis examination of the flexibility of the proposed methodology and the interaction of the various algorithmsand tasks in order to improve their performances and robustness. Finally, the fourth topic will be related toinvestigation of computational requirements, and structures that would allow for real-time use.