FDD Massive MIMO Uplink and Downlink Channel Reciprocity Properties: Full or Partial Reciprocity?
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Abstract (arXiv)
One challenge for FDD massive MIMO communication system is how to obtain the downlink channel state information (CSI) at the base station. Except for traditional codebook feedback through uplink pilot transmission, some channel reciprocity properties can be utilized through uplink channel estimation and channel parameter estimation algorithms. In this paper, the uplink and downlink channel reciprocity properties are analyzed. It is theoretically proved that not all multipath parameters for FDD downlink and uplink channels are equivalent. Therefore, the so called full reciprocity property does not hold while the partial reciprocity property holds. Moreover, the channel measurement campaign is conducted to verify our theoretical analysis. Finally, in order to support the partial reciprocity property, the revision for the standardization 5G channel model is proposed as well. With the contribution of this paper, the FDD massive MIMO system transmission scheme design could be led to the right direction.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Dec 2019.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 3; 2025: 0; 2026: 2.
7 papers.
- 2024Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensingcited by 4
- 2022Deep Generative Models for Downlink Channel Estimation in FDD Massive MIMO Systemscited by 1
- 2023Deep Learning Empowered Type-II Codebook: New Paradigm for Enhancing CSI Feedbackcited by 1
- 2024Downlink Channel Covariance Matrix Estimation via Representation Learning with Graph Regularizationcited by 1
- 2024Physics-Inspired Deep Learning Anti-Aliasing Framework in Efficient Channel State Feedbackcited by 0
- 2026Self-Evolving In-Context Learning for Direct Pilot-to-Beamformer Design in MU-MISO Systemscited by 0
- 2026Mean Spatial Frequency Decoupling for Learning-Based Uplink-to-Downlink Covariance Conversion in FDD Massive MIMOcited by 0
- 2026Mean Spatial Frequency Decoupling for Learning-Based Uplink-to-Downlink Covariance Conversion in FDD Massive MIMO30 Sep 2026
- 2026Self-Evolving In-Context Learning for Direct Pilot-to-Beamformer Design in MU-MISO Systems13 Jul 2026
- 2024Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing16 Sep 2024
- 2024Downlink Channel Covariance Matrix Estimation via Representation Learning with Graph Regularization26 Jul 2024
- 2024Physics-Inspired Deep Learning Anti-Aliasing Framework in Efficient Channel State Feedback12 Mar 2024
- 2023Deep Learning Empowered Type-II Codebook: New Paradigm for Enhancing CSI Feedback14 May 2023
- 2022Deep Generative Models for Downlink Channel Estimation in FDD Massive MIMO Systems9 Mar 2022