ITR: Adaptive Signaling and MIMO Precoding for Rapidly Time-Varying Fading Channels

ITR：针对快速时变衰落信道的自适应信令和 MIMO 预编码

• 批准号: 0312294
• 负责人: Alexandra Duel-Hallen
• 金额: --
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-15 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0312294&HistoricalAwards=false
• 关键词: ITR; Adaptive; Signaling; MIMO; Precoding

This project investigates feasibility of transmitter optimization for rapidly time varying fading channels encountered in wideband mobile radio communication systems. Adaptive transmitter optimization methods have the potential to significantly improve performance in wireless channels by adjusting the transmitted signal-to-fading conditions. However, rapid channel variation makes application of these closed-loop techniques difficult in wireless systems. Previous investigations demonstrate that it is not sufficient to utilize the outdated Channel State Information (CSI) in adaptive transmission algorithms when vehicle speeds are significant. Prediction of the channel coefficients several tens-to-hundreds of symbols ahead is essential to realize these methods in practice. A novel adaptive, long-range fading channel prediction algorithm (LRP) was previously developed by the PI and her collaborators for narrowband wireless channels. In this research, the long range fading prediction capability is extended to frequency selective fading channels with antenna arrays. These methods are utilized in adaptive modulation and coding techniques for multicarrier and multiple antenna systems and in novel precoding methods and joint transmitter/receiver optimization techniques for Multiple Input Multiple Output (MIMO) wideband mobile radio systems. This research contributes to the development and realization of adaptive transmission and precoding methods that are essential in reliable high rate wireless communication. Moreover, collaboration with industry benefits graduate students involved in the project. Broader participation of underrepresented groups is enhanced since the PI and the graduate students are females. The infrastructure for research and education is enriched by incorporating the methods investigated in this research in senior and class projects and by integrating with wireless communications activities at NC State. The first component of this project focuses on utilization of prediction methods in interference cancellation for the MIMO channels that arise in multicarrier, multiple antennae and the downlink of multiuser Direct Sequence Code Division Multiple Access (DS/CDMA) channels. While the sources of interference depend on the application, these systems can be described with a single underlying MIMO model. Novel Tomlison-Harashima precoding methods are developed for this model. These methods are expected to improve significantly on previously proposed linear precoding techniques. Moreover, they distribute computational resources between the transmitter and the receiver as dictated by the application. For the downlink of the DS/CDMA channel, novel low complexity linear techniques that have the potential to significantly simplify precoding at the base station and detection at the mobile station are investigated. The proposed interference cancellation techniques are combined with adaptive modulation and coding. Since these precoding and adaptive transmission methods depend on accurate CSI in the transmitter, reliable LRP and the underlying prediction error statistics are essential in the design and the performance analysis of the proposed methods. In the second component, joint prediction for multiple subcarriers in multicarrier systems and antenna array elements in multiple antenna channels is investigated. Novel linear and nonlinear approaches to long-range prediction are explored. A statistical model of the prediction error is developed and utilized in the design of reliable adaptive modulation and coding methods. Flexible prediction methods that trade spectral efficiency for complexity and feedback requirements are explored.

本课题针对宽带移动通信系统中遇到的快时变衰落信道，研究发射机优化的可行性。自适应发射机优化方法通过调整发射信号衰落比条件，有可能显著提高无线信道的性能。然而，快速的信道变化使得这些闭环技术在无线系统中的应用变得困难。以往的研究表明，当车速很大时，利用过时的信道状态信息(CSI)在自适应传输算法中是不够的。对于在实践中实现这些方法来说，对前面几十到数百个码元的信道系数的预测是必不可少的。PI及其合作者针对窄带无线信道提出了一种新的自适应长程衰落信道预测算法(LRP)。在本研究中，将长距离衰落预测能力扩展到具有天线阵的频率选择性衰落信道。这些方法被用于多载波和多天线系统的自适应调制和编码技术以及用于多输入多输出(MIMO)宽带移动无线电系统的新型预编码方法和联合发射机/接收机优化技术。这项研究有助于开发和实现可靠的高速无线通信中必不可少的自适应传输和预编码方法。此外，与行业的合作使参与该项目的研究生受益。由于PI和研究生都是女性，代表不足群体的更广泛参与得到了加强。通过将研究中调查的方法纳入高年级和班级项目，并与北卡罗来纳州立大学的无线通信活动相结合，丰富了研究和教育的基础设施。本项目的第一部分主要针对多载波、多天线和多用户直接序列码分多址(DS/CDMA)信道下行链路中的MIMO信道，重点研究了预测方法在干扰消除中的应用。虽然干扰源取决于应用，但这些系统可以用单一的底层MIMO模型来描述。针对该模型提出了新的Tomlison-Harashima预编码方法。这些方法有望显著改进先前提出的线性预编码技术。此外，它们根据应用程序的指示在发送器和接收器之间分配计算资源。对于DS/CDMA信道的下行链路，研究了可能显著简化基站处的预编码和移动站处的检测的新型低复杂度线性技术。所提出的干扰消除技术与自适应调制和编码相结合。由于这些预编码和自适应传输方法依赖于发射机中准确的CSI，可靠的LRP和潜在的预测误差统计在所提出的方法的设计和性能分析中是必不可少的。第二部分研究了多载波系统中的多个子载波和多个天线信道中的天线阵元的联合预测问题。探索了新的线性和非线性长期预测方法。建立了预测误差的统计模型，并将其用于设计可靠的自适应调制和编码方法。探索了以频谱效率换取复杂性和反馈要求的灵活预测方法。