Fast Beam Training for Higher-Rank LoS-MIMO Using True-Time-Delay Arrays
This paper proposes a fast beam training algorithm utilizing true-time-delay (TTD) arrays suitably for high-rank line-of-sight (LoS) multiple input multiple output (MIMO) systems. In millimter wave bands, analog beamforming is generally utilized to compensate the effect of severe pathloss, and a beam training (BT) is typically operated to select beams which can obtain higher received signal power. However, it is difficult to secure the higher rank transmission in LoS-MIMO link with multiple sub-array panels, due to spatial correlation depending on a distance among Tx and Rx when selecting beam direction along LoS path commonly in all the panels. To alleviate this issue, we have proposed beamforming scheme, that select beams directing reflective paths at some panels, whereas the remaining panels select the direction of the direct path. However, it takes longer training time since BT is required to be operated in all the panels to select independent directions. Our proposed solution in this paper involves leveraging TTD arrays that can form a raibow beam, a set of multiple beams for each frequency, in one OFDM symbol, leading to reduction of the training time. Furthermore, we conduct effective angle-of-departure (AoD) and angle-of-arrival (AoA) estimation using TTD arrays to enhance the robustness of channel capacity for distance-dependent LoS-MIMO systems. The effectiveness of the proposed method is demonstrated through computer simulations. They show that the overhead of the proposed BT algorithm is smaller than that of BT algorithm using phased array (PA) while maintaining channel capacity.
Authors
- Takahiro Hayashi (ORCID: https://orcid.org/0000-0002-8800-1635)
- Issei Kanno
- Masahiro Takigawa
- Ryochi Kataoka
Institutions
- KDDI Research (Japan) (JP)
Publication Details
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1109/ccnc54725.2025.10976135
- Citations
- 2
- Primary Topic
- Antenna Design and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 9.99