RF Chain Reduction for MIMO Systems: A Hardware Prototype
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Abstract (arXiv)
Radio frequency (RF) chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we study the design and hardware implementation of hybrid architectures via minimizing channel estimation error. We first derive the optimal solution for complex-gain combiners and propose an alternating optimization algorithm for phase-shifter combiners. We then present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows evaluating the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 May 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 1.
4 papers.
- 2021LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receiverscited by 11
- 2022Deep Task-Based Analog-to-Digital Conversioncited by 7
- 2021Self-Organizing mmWave MIMO Cell-Free Networks With Hybrid Beamforming: A Hierarchical DRL-Based Designcited by 3
- 2024Rapid and Power-Aware Learned Optimization for Modular Receive Beamformingcited by 0
- 2024Rapid and Power-Aware Learned Optimization for Modular Receive Beamforming1 Aug 2024
- 2022Deep Task-Based Analog-to-Digital Conversion29 Jan 2022
- 2021Self-Organizing mmWave MIMO Cell-Free Networks With Hybrid Beamforming: A Hierarchical DRL-Based Design17 Mar 2021
- 2021LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receivers5 Feb 2021