Multi-UCA Assisted OAM for Full-Duplex IAB Networks
6G is expected to support a massive number of connected Internet of Things (IoT) devices that are producing data on an unprecedented scale. Full-duplex-enabled integrated access and backhaul (FD-IAB) emerges as one of the pivotal solutions for ensuring efficient and reliable 6G IoT networks. Orbital angular momentum (OAM) is well-suited for innovative multiple access schemes and backhaul networking due to its capability for mode multiplexing. This paper introduces a new FD-IAB network framework utilizing OAM multiplexing, which incorporates multiple uniform circular arrays (MUCA) antennas. Two types of MUCA are suggested, specifically multi-ring-based MUCA (MR-MUCA) and single-ring with subarray based MUCA (SS-MUCA), and their respective performances are analyzed. However, the OAM-based FD system is significantly challenged by various interferences. Primarily, the FD system introduces self-interference (SI), and secondly, OAM multiplexing suffers from inter-mode interference (IMI) due to misalignment between the transceiver antennas. To mitigate SI, antenna configuration method for MUCA is proposed consisting of several subsets, which involves adjusting the space of antenna elements. To reduce IMI, a beam steering matrix (BSM) is utilized to compensate for the misaligned angle at the receiver. Simulation results validate the performance of two types of MUCA and the subset configuration method regarding the impact of SI and IMI in terms of the sum rate and outage probability.
Authors
- Hye Yeong Lee (ORCID: https://orcid.org/0000-0003-2924-4191)
- Man Hee Lee (ORCID: https://orcid.org/0000-0003-1901-0279)
- Soo Young Shin (ORCID: https://orcid.org/0000-0002-2526-2395)
Institutions
- Kumoh National Institute of Technology (KR)
Publication Details
- Journal
- IEEE Transactions on Vehicular Technology
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/tvt.2025.3543505
- Citations
- 4
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 6.54