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

University Of California-Davis, Davis CA

Investigators

Abstract

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.