High Performance Receiver Designs in Non-Orthogonal Multiple Access Networks for New Generations of Wireless Services

这项研究项目解决了未来几代无线通信网络中的一些关键和新兴挑战，以服务于广泛的物联网(IoT)应用的需求。与现有的蜂窝网络不同，物联网应用程序预计将在严格的带宽限制下连接大量智能物联网设备。物联网无线设备的这种大规模规模和需求，以及许多其他正在兴起的无线应用，如车载到一切(V2X)，都强烈推动了网络容量的高效利用。为大幅扩展网络容量，非正交多址(NOMA)技术是一种将发射端的叠加编码和接收端的连续干扰抵消(SIC)概念相结合的前沿技术。NOMA因其较高的频谱利用率而备受关注。然而，NOMA吞吐量的增加是以必须克服无线网络节点之间的大量同信道干扰(CCI)为代价的。尽管广泛而理想化的接收机假设是完美的干扰消除，但NOMA接收机的实际成功取决于在存在实质性CCI的情况下对信号的成功检测和译码。本研究项目旨在开发高效实用的联合检测和解码接收器，以提供未来5G和物联网无线服务中成功部署NOMA所需的网络性能。具体地说，该项目通过利用用户前向纠错码的知识来开发联合检测和纠错接收器的优化设计，以显著提高在信道不确定情况下对抗CCI的接收器性能。研究成果对提高高速无线网络的服务质量和效率，扩大其在高质量、高效率、高服务分散化领域的应用具有重要意义。该项目的成功可能导致新的系统设计、新的工具和结果，可能会影响其他科学和工程领域。本项目的技术重点是开发一种新的接收机设计方法，将多输入多输出(MIMO)无线通信和分集网络中的信号检测和前向纠错统一起来，以应对恶劣的无线信道条件。与传统方法不同，对这一相当经典但开放的问题的新研究集中在新的优化公式上，该公式可以将前向纠错(FEC)码施加的伽罗瓦域码字约束合并到用于统一接收器优化的最大似然检测原则中。这种新的框架是通用的，涵盖了许多无线模型，包括分布式MIMO、机会协作网络、重传多样性以及它们的集成。这一创新方向强调通过有效的约束松弛和新颖的目标函数公式来关键地整合来自不相容领域的多个约束。将联合检测和译码问题的优化问题转化为凸优化问题，提出的接收机设计集成方法代表了一种基本和实用的设计范例，可以充分利用各种实用的信令和代码约束，针对信道和其他非理想情况进行联合检测和译码，以实现高性能、高效率和高可靠性。为了应对无线网络中信道估计误差和快速信道衰落的实际挑战，项目组将根据不同的实际限制和网络配置，在复杂性和性能权衡方面，为强共信道干扰下的编码MIMO传输开发快速、有效、可靠和健壮的算法。研究结果预计将对包括高速蜂窝、物联网和V2X服务在内的广泛无线应用产生重大而广泛的影响。

This research project addresses some critical and emerging challenges in future generations of wireless communication networks to serve the need of the widespread Internet of Things (IoT) applications. Unlike existing cellular networks, IoT applications are expected to connect a massive number of smart IoT devices under severe bandwidth constraint. This massive scale and need of IoT wireless devices, along with many other rising wireless applications such as vehicular to everything (V2X) strongly motivates highly effective utilization of network capacity. To substantially expand network capacity, non-orthogonal multiple access (NOMA) is a cutting-edge technology that integrates the concepts of superposition coding at transmitter and successive interference cancelation (SIC) at receiver, respectively. NOMA has attracted much attention for its high spectral efficiency. However, the NOMA throughput gain comes at the price of having to overcome substantial co-channel interferences (CCI) among wireless network nodes. Despite the widespread and idealized receiver assumption of perfect interference cancellation, practical success of NOMA receivers depends critically on the successful detection and decoding of signals in the presence of substantial CCI. This research project aims to develop highly effective and practical joint detection and decoding receivers to deliver the much needed network performance for successful deployment of NOMA in future 5G and IoT wireless services. Specifically, the project develops optimized design of joint detection and error correction receivers by leveraging the knowledge of user forward error correction codes to substantially improve receiver performance against CCI under channel uncertainties. The research findings can contribute importantly to the service improvement of high speed wireless networks and to broadening their applications in many practical fields where quality, efficiency, and service decentralization are paramount. The success of the project can lead to new system designs, new tools, and results that can impact other science and engineering fields. The technical focus of this project is to develop a new receiver design methodology that unifies signal detection and forward error correction in multiple-input-multiple-output (MIMO) wireless communications and diversity networks against poor wireless channel conditions. Unlike traditional approaches, this new investigation into the rather classic but open problem centers on novel optimization formulations that can incorporate Galois field codeword constraints imposed by the forward error correction (FEC) codes within the maximum likelihood detection principle for unified receiver optimization. This novel framework is general and encompasses many wireless models, including distributed MIMO, opportunistic cooperative networking, and retransmission diversities as well as their integrations. This innovative direction emphasizes critical integration of multiple constraints from incompatible fields through effective constraint relaxation and novel objective function formulation. Reformulating the optimization of joint detection and decoding problems into convex optimization, the proposed approach to receiver design integration represents a fundamental and practical design paradigm that can fully leverage various practical signaling and code constraints for joint detection and decoding against channel and other non-idealities to achieve high performance, efficiency, and reliability. To confront practical challenges of channel estimation errors and fast channel fading in wireless networks, the project team shall develop fast, effective, reliable, and robust algorithms for coded MIMO transmissions under strong co-channel interferences subject to different practical limitations and network configurations, with respect to complexity and performance tradeoffs. The research findings are expected to have significant broader impact on a wide range of wireless applications including high speed cellular, IoT, and V2X services.