ERI:Interference-Aware Constellation Design

ERI：干扰感知星座设计

• 批准号: 2301778
• 负责人: Mojtaba Vaezi
• 金额: $ 19.62万
• 依托单位: Villanova University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301778&HistoricalAwards=false
• 关键词: ERI; Interference; Aware; Constellation; Design

Wireless networks have seen an exponential increase in the number of users requiring access, making it impractical to allocate a dedicated spectrum to each user. To address this issue, non-orthogonal transmission has been proposed as a potential solution. By sharing spectrum among multiple users, more devices can access the spectrum or more bandwidth can be committed to each transceiver, achieving higher data transmission rates. However, non-orthogonal transmission suffers from interference among users, and effective transmission and decoding methods are needed for its successful deployment. The primary goal of this research is to develop such methods and advance the field, which has significant value for next-generation wireless networks and applications like the Internet of Things (IoT). In addition, the project will provide education opportunities, including involving undergraduate students in research on deep learning for communications and designing graduate-level course material. The findings of this research will be shared with both academic and industrial communities. This project aims to address inter-user interference by proposing a novel end-to-end learning-based digital modulation design. Digital modulation techniques are used to achieve a balance between high bit rates and low bit-error rates for information transmission. A particular focus of this research is on designing new superimposed constellations for non-orthogonal multiple access (NOMA) that take into account both noise and interference during the design phase. Unlike traditional constellations such as quadrature amplitude modulation, the proposed transform results in non-uniform constellations that can adapt to different interference levels and work effectively in their presence. This approach provides new insights and tools for multi-user constellation design, which has the potential to improve spectral efficiency, reduce bit-error rate, and decrease latency in communication for next-generation wireless networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

无线网络需要接入的用户数量呈指数级增长，这使得为每个用户分配专用频谱变得不切实际。为了解决这个问题，非正交传输被提出作为一种潜在的解决方案。通过在多个用户之间共享频谱，更多设备可以访问该频谱，或者可以为每个收发器分配更多带宽，从而实现更高的数据传输速率。然而，非正交传输会受到用户之间的干扰，其成功部署需要有效的传输和解码方法。 这项研究的主要目标是开发此类方法并推进该领域的发展，这对于下一代无线网络和物联网 (IoT) 等应用具有重要价值。此外，该项目还将提供教育机会，包括让本科生参与通信深度学习研究和设计研究生课程材料。这项研究的结果将与学术界和工业界分享。该项目旨在通过提出一种新颖的基于端到端学习的数字调制设计来解决用户间干扰。数字调制技术用于实现信息传输的高比特率和低误码率之间的平衡。这项研究的一个特别重点是为非正交多址（NOMA）设计新的叠加星座，在设计阶段同时考虑噪声和干扰。与正交幅度调制等传统星座不同，所提出的变换产生非均匀星座，可以适应不同的干扰水平并在存在干扰的情况下有效工作。这种方法为多用户星座设计提供了新的见解和工具，有可能提高频谱效率、降低误码率并减少下一代无线网络的通信延迟。该奖项反映了 NSF 的法定使命，并已通过使用基金会的智力优点和更广泛的影响审查标准进行评估，认为值得支持。