Near-Optimal Antenna Topology and Detection Strategy for Multiple-Input Multiple-Output (MIMO) Communication Systems

多输入多输出（MIMO）通信系统的近最优天线拓扑和检测策略本研究的目的是开发评估非理想可实现多输入多输出（MIMO）容量的方法，并优化实际MIMO系统的天线和检测器。MIMO无线系统提供了额外的容量，以支持更多的用户、额外的服务和面向新市场的新应用。虽然理论上，MIMO系统承诺通过使用具有独立通信路径的许多不同天线来无限提高吞吐量，但随着MIMO的成熟，其声称的无限改进已被现实世界的测量所缓和。本项目采用的方法是：(1)调整现有的容量计算以纳入天线设计数据，并使用遗传算法和/或线性化反演技术来开发最佳的现实MIMO天线，(2)使用马尔可夫链蒙特卡罗（MCMC）方法来改进现有的检测算法并使其适应现实信道，以及(3)验证天线和检测系统的预测性能。本研究的更广泛影响是使个人通信系统技术继续传播到娱乐，远程医疗，远程安全监控等更宽频带（更高容量）的应用中。这个项目的另一个重要影响将体现在美国国家科学基金会赞助的犹他大学基于实践的集成项目（HIP）课程开发工作中，以及目前由其中一位pi编写的软件无线电教科书中。该系统的简化版本将作为一个多课程设计项目，可以结合天线、通信、信号处理、微波工程等。

Near-optimal Antenna Topology and Detection Strategy for Multiple-Input Multiple-Output (MIMO) Communication SystemsThe objective of this research is to develop methods to assess non-ideal realizable Multiple Input Multiple Output (MIMO) capacity and optimize antennas and detectors for realistic MIMO systems. MIMO wireless systems provide additional capacity, to enable more users, additional services, and new applications for new markets. While in theory, MIMO systems promise virtually limitless increases in throughput by using many different antennas with independent communication paths, as MIMO matures its claims of boundless improvements have been tempered by real-world measurements. The approaches utilized in this project are (1) To adapt existing capacity calculations to incorporate antenna design data, and to use genetic algorithms and / or linearized inversion techniques to develop the best possible realistic MIMO antennas, (2) To use Markov chain Monte-Carlo (MCMC) methods to improve on existing detection algorithms and adapt them to realistic channels, and (3) To verify the predicted performance of the antennas and detection system. The broader impacts of this research are to enable the continued propagation of personal communication system technologies into broader band (higher capacity) applications for entertainment, remote health care, remote security monitoring, etc. Another significant impact of this project will be felt in the NSF-sponsored Hands-on Integrated Project-Based (HIP) curriculum development effort at the University of Utah, and in a Software Radio textbook currently being written by one of the PIs. An abbreviated version of the system will serve as a multi-course design project that can combine antennas, communication, signal processing, microwave engineering, and more.