Fast Ambiguous DOA Elimination Method of DOA Measurement for Hybrid Massive MIMO Receiver
Not on the map. Why?
Abstract (arXiv)
DOA estimation for massive multiple-input multiple-output (MIMO) system can provide ultra-high-resolution angle estimation. However, due to the high computational complexity and cost of all digital MIMO systems, a hybrid analog digital (HAD) structure MIMO was proposed. In this paper, a fast ambiguous phase elimination method is proposed to solve the problem of direction-finding ambiguity caused by the HAD MIMO. Only two-data-blocks are used to realize DOA estimation. Simulation results show that the proposed method can greatly reduce the estimation delay with a slight performance loss.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 May 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 2.
4 papers.
- 2024Co-learning-aided Multi-modal-deep-learning Framework of Passive DOA Estimators for a Heterogeneous Hybrid Massive MIMO Receivercited by 2
- 2024Multi-modal Iterative and Deep Fusion Frameworks for Enhanced Passive DOA Sensing via a Green Massive H2AD MIMO Receivercited by 2
- 2025Multi-Branch DNN and CRLB-Ratio-Weight Fusion for Enhanced DOA Sensing via a Massive H2AD MIMO Receivercited by 0
- 2025DNN-based Methods of Jointly Sensing Number and Directions of Targets via a Green Massive H2AD MIMO Receivercited by 0
- 2025DNN-based Methods of Jointly Sensing Number and Directions of Targets via a Green Massive H2AD MIMO Receiver15 Jul 2025
- 2025Multi-Branch DNN and CRLB-Ratio-Weight Fusion for Enhanced DOA Sensing via a Massive H2AD MIMO Receiver29 Jun 2025
- 2024Multi-modal Iterative and Deep Fusion Frameworks for Enhanced Passive DOA Sensing via a Green Massive H2AD MIMO Receiver11 Nov 2024
- 2024Co-learning-aided Multi-modal-deep-learning Framework of Passive DOA Estimators for a Heterogeneous Hybrid Massive MIMO Receiver27 Apr 2024