CIF: Small: Optimized Receiver Design Integration for Diversity and Cooperative Transmissions Beyond Belief Propagation

本文提出了一种新的接收机方法，用于在多输入多输出（MIMO）通信和各种分集传输中集成信号检测和前向纠错。超越传统的方法依赖于信念传播，这一调查的集成信号检测和decodinginvolves新的联合优化配方，将二进制字段奇偶约束imposed由低密度奇偶校验在最大似然检测框架统一优化的经典开放问题。这种新的框架是通用的，包括一些practicaltransmission模型，包括分布式天线，机会合作网络，信号重传以及它们的集成。该项目对工程、教育和社会都有广泛的影响。它的成功可以带来新的研究方向，新的工具和成果，以帮助推进其他科学和工程领域。专注于多载波MIMO信号接收，研究人员将开发和优化集成接收机的重要无线网络的diversitedtransmissions，合作MIMO，和混合ARQ重传系统。新的设计方法强调从不兼容领域的多个约束的集成。通过将联合检测和解码问题转化为凸优化问题，研究人员将设计出高效的高性能接收机，并且对信道状态信息中的各种形式的不确定性具有鲁棒性。这种新颖的接收机设计集成方法代表了一种基本而实用的设计范例，它可以充分利用各种先验信令和编码约束，针对信道失真和其他非理想情况进行联合检测和解码，以实现高性能、高效率和高可靠性。研究结果可以实际有助于改善未来的无线服务，并扩大其应用在许多实际领域的质量，效率和分布式的关注是至关重要的。

This work develops a novel receiver methodology to integrate signal detection and forwarderror correction in multiple-input-multiple-output (MIMO) communications and various diversitytransmissions. Moving beyond traditional approaches relying on belief-propagation, thisinvestigation into the rather classic open problem of integrated signal detection and decodinginvolves novel joint optimization formulations that incorporate binary field parity constraintsimposed by the low-density parity check within maximum likelihood detection frameworks forunified optimization. This novel framework is general and encompasses a number of practicaltransmission models, including distributed antennas, opportunistic cooperative networking,and signal retransmission as well as their integrations. This project has broad impacts onengineering, education, and society. Its success can lead to new research directions, newtools, and results to help advance other science and engineering fields.Focusing on multicarrier MIMO signal reception, the investigators will develop and optimizeintegrated receivers for important wireless network diversities including distributedtransmissions, cooperative MIMO, and hybrid-ARQ retransmission systems. The new designmethodology emphasizes integration of multiple constraints from incompatible fields. Byreformulating and relaxing joint detection and decoding problems into convex optimization, theinvestigators will design high performance receivers that are efficient and are robust to variousforms of uncertainties in channel state information. Such a novel approach to receiver designintegration represents a fundamental and practical design paradigm that can fully utilizevarious a priori signaling and code constraints for joint detection and decoding against channeldistortions and other non-idealities to achieve high performance, efficiency, and reliability. Theresearch findings can contribute practically to improvement of future wireless services andbroaden their applications in many practical fields where quality, efficiency, and distributivityconcerns are paramount.