Full-duplex Wireless

Theoretical foundations, practical protocol design, and experimental evaluation.


We develop foundational principles for wireless network design by leveraging full-duplex transmissions in both access and wireless backhaul. Full-duplex is most promising at shorter ranges and hence is fortuitously aligned with the predicted dominant access range in future networks. Furthermore, larger full-duplex ranges are feasible in infrastructure-to-infrastructure links and are well suited for backhaul links. While full-duplex is well-aligned with the key elements of hierarchical networks, our current design principles are largely developed for half-duplex transmissions which are the basis for all current networks. 

The research is heavily leveraging Rice WARP platform and Rice Argos platform. Our objectives fall in three broad inter-related thrust areas. In each case, we will develop solutions that ensure low complexity and low communications overhead.

  1. Signal-Scale Foundations for Full-duplex Networks: Full-duplex transmissions induce self-interference, which is a near-field reception compared to all other receptions that happen in far-field. Our goal here is to develop data-driven signal models for self-interference and use the resulting models to develop signal-scale (PHY) foundations for hierarchical MIMO full-duplex networks.
  2. Theoretical Foundations for Full-duplex Network Scale Resource Allocation: Our second research goal is to develop scheduling and routing foundations for hierarchical full-duplex networks, by leveraging full-duplex self-interference cancellation. In addition to the physical layer gains obtained through multiple antennas, the promise of full-duplex lies in the potential for developing simpler algorithms because the half-duplex link activation constraint is eliminated.
  3. Protocols and Prototypes for Network Scale Full-duplex Resource Management: Our goal here is to develop practical protocols and construct operational network prototypes to translate the theoretical foundations into principles for deployment, using a combination of analysis and at-scale experimental evaluations.