Enabling MIMO Communication for Complex Channels

本研究的目的是开发复杂信道中多输入多输出（MIMO）通信的关键分析框架。现有的MIMO容量计算软件将通过包括车辆的复杂信道模型、有损生物信道和高噪声信道来增强。我们还将集成探测器模型与电磁和通信MIMO模型，并通过测量验证模型。知识优势：今天的MIMO模型不包括非高斯、超反射、去极化和高损耗信道的准确表示，这些信道见于许多个人通信信道、身体穿戴或植入的医疗通信信道、飞机、汽车、公共汽车、火车、船舶等内部传感器网络的典型车载通信的高反射和高损耗（“超罗利”）信道，以及大多数无线自组织网络环境。或人体散射通道，用于医学成像。该研究计划将为MIMO提供更先进的信道模型。这将为每个应用程序提供专门的MIMO设计，为部署的系统提供更大的初始成功概率。更广泛的影响：这项研究解决了未来无线设备未满足的通信需求。除了潜在的重大社会、医学和经济方面的进步外，这项研究还将直接融入犹他大学的课程。

The objective of this research is to develop the critical analytical framework for Multiple Input Multiple Output (MIMO) communication in complex channels. Existing MIMO capacity calculation software will be enhanced by including complex channel models for vehicles, lossy biological channels, and highly noisy channels. We will also integrate detector models with the electromagnetic and communication MIMO models, and verify the models via measurement. Intellectual Merit:Today's MIMO models do not include an accurate representation of non-Gaussian, ultra-reflective, depolarizing, and highly lossy channels seen in many personal communication channels, body-worn or implanted medical communication channels, highly reflective and lossy ('Hyper-Raleigh') channels typical of intra-vehicular communication for sensor networks inside aircraft, cars, buses, trains, ships, etc., most wireless ad-hoc network environments, or the human body scattering channel for medical imaging. This research program will provide more advanced channel models for MIMO. This will enable specialized MIMO design for each application, providing a far greater probability of initial success for the deployed systems. Broader Impacts:This research addresses unmet communication demand for future wireless devices. In addition to the significant societal, medical, and financial aspects of that potential advancement, the research will be directly integrated into coursework at the University of Utah.