NSF Award
2301778
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.<br/> <br/>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.<br/><br/>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.
