Intelligent and Efficient Finite Alphabet Signal Processing Technologies for Future Wireless Communications

面向未来无线通信的智能高效有限字母信号处理技术

• 批准号: RGPIN-2018-06819
• 负责人: Zhang, JianKang
• 金额: $ 2.84万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714492
• 关键词: Intelligent; Efficient; Finite; Alphabet; Signal

To date, it has been envisioned that non-orthogonal multi-access (NOMA) and massive MIMO (MaMIMO) are two major potential technologies for future wireless communications, because they meet three major requirements for future wireless communications, i.e., huge data rates, massive connectivity and low latency. The current research on NOMA focuses mainly on the channel capacity for either Gaussian inputs or finite-alphabet (FA) inputs. However, the methods for the FA signals are specifically numerical. Hence, a limited insight into the relationship between the optimal sum constellation and each individual user constellation can be drawn from the obtained solutions. On the other hand, the current research on MaMIMO has indicated that one of major factors to significantly affect its performance is pilot contamination, never vanishing, even when the number of BS antennas becomes infinity. Hence, non-coherent space-time code designs were proposed for MaMIMO. However, all the current non-coherent massive space-time code (MASTC) designs suffer a severe error floor phenomenon, never disappearing, even when SNR goes to infinity. In addition, it is also not difficult for a passive eavesdropper be equipped with a massive array, thereby; potentially and physically deteriorate uplink security. To address all the aforementioned significant issues, the applicant's long-term research objective is to develop advanced finite alphabet signal-processing technologies (FAST) to intelligently and efficiently manage FA interference for a general complicated wireless network topology with the uplink or the downlink having multiple base stations from the standpoint of signal estimation and detection theory. Within the next five years, the applicant targets mainly on the following three objectives: (a) to develop new FAST for FA NOMA for uplink SISO and downlink MISO systems, (b) to develop new FAST for FA uplink MaMIMO systems, and (c) to develop new FAST for physically securing FA NOMA-MaMIMO systems. In order to achieve these three objectives, the following four technical approaches are specifically proposed, i.e., (i) additively unique decomposition theory of FA signals for the design of four kinds of optimal sum constellations, (ii) multiplicatively unique decomposition theory of FA MIMO signals for the design of three kinds of optimal MASTC, (iii) super-rectangular cover theory for FA uplink MaMIMO systems for the design of an optimal MASTC when the large-scale channel is known only at the receiver, and (iv) block-equal QRS decomposition theory of MIMO channels for the design of an optimal FA precoder with ML-based block successive cancellation detection. Therefore, this proposed research program develops completely novel FAST for intelligently and efficiently managing FA interference for multi-user communications so that all the major benefits offered by NOMA-MaMIMO can be realized.

迄今为止，人们已经设想非正交多址（NOMA）和大规模MIMO（MaMIMO）是未来无线通信的两大潜在技术，因为它们满足了未来无线通信的三大需求，即大数据速率、海量连接和低延迟。目前 NOMA 的研究主要集中在高斯输入或有限字母（FA）输入的信道容量上。然而，FA 信号的方法是特定的数值方法。因此，可以从所获得的解决方案中得出对最佳总和星座与每个单独用户星座之间关系的有限了解。另一方面，目前对MaMIMO的研究表明，显着影响其性能的主要因素之一是导频污染，即使基站天线数量无穷大，导频污染也不会消失。因此，针对MaMIMO提出了非相干空时码设计。然而，当前所有的非相干大规模空时码（MASTC）设计都存在严重的错误层现象，即使信噪比趋于无穷大，这种现象也不会消失。另外，对于被动窃听者来说，配备大规模的阵列也不是什么难事，从而；潜在地和物理上恶化上行链路安全性。 为了解决所有上述重要问题，申请人的长期研究目标是开发先进的有限字母信号处理技术(FAST)，以智能且高效地管理上行链路或下行链路具有多个的通用复杂无线网络拓扑的FA干扰。从信号估计和检测理论的角度来看基站。在未来五年内，申请人主要致力于以下三个目标：（a）为上行链路SISO和下行链路MISO系统开发用于FA NOMA的新FAST，（b）为FA上行链路MaMIMO系统开发新FAST，以及（c） ）开发新的 FAST，用于物理保护 FA NOMA-MaMIMO 系统。为了实现这三个目标，具体提出了以下四种技术途径，即（i）用于设计四种最优和星座的FA信号的加性唯一分解理论，（ii）FA MIMO的乘性唯一分解理论用于设计三种最佳 MASTC 的信号，(iii) FA 上行链路 MaMIMO 系统的超矩形覆盖理论，用于当大规模信道仅在接收机处已知时设计最佳 MASTC，以及(iv) MIMO 信道的块等 QRS 分解理论，用于设计具有基于 ML 的块连续消除检测的最佳 FA 预编码器。 因此，本研究计划开发了全新的 FAST，用于智能、高效地管理多用户通信的 FA 干扰，从而实现 NOMA-MaMIMO 提供的所有主要优势。