Geometry-Aided Near-Field MIMO Communications via Forward-Backward Beamformer Training
Eslami, Shima; Gouda, Bikshapathi; Tölli, Antti (2024-08-26)
IEEE
26.08.2024
S. Eslami, B. Gouda and A. Tölli, "Geometry-Aided Near-Field MIMO Communications via Forward-Backward Beamformer Training," 2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM), Corvallis, OR, USA, 2024, pp. 1-5, doi: 10.1109/SAM60225.2024.10636361
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© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202412097108
https://urn.fi/URN:NBN:fi:oulu-202412097108
Tiivistelmä
Abstract
In near-field communication systems, the estimation of the line-of-sight (LoS) component of the MIMO channel can be achieved with the minimal pilot transmission, relying exclusively on the geometric characterization of the high-rank LoS channels between the user equipment (UEs) and base station (BS). Nevertheless, even a slight error in the LoS-specific angular parameters, stemming from noisy estimates or information exchange with limited quantization levels, can significantly impact the accuracy of the channel estimate. Additionally, neglecting significant Non-Line-of-Sight (NLoS) components in the channel characterization may render LoS-only estimates ineffective. Given limited pilot resources, bidirectional over-the-air (OTA) transmit-receive beamformer training proves advantageous, eliminating the need for explicit antenna-specific channel estimation. Typically, lacking prior knowledge about the channel characteristics, the forward-backward beamformer training is initialized with a set of stream-specific random beamformers. This paper proposes a trans-mission design procedure that begins with LoS channel estimation using two downlink pilots and geometry information feedback from UEs, followed by an initial precoder design algorithm at the BS based on the LoS channel estimate to initialize beamformers for the OTA bidirectional beam training procedure. Simulation results demonstrate that such a bidirectional algorithm can achieve significantly higher rates within a few iterations compared to traditional forward-backward beam training procedures with random initialization.
In near-field communication systems, the estimation of the line-of-sight (LoS) component of the MIMO channel can be achieved with the minimal pilot transmission, relying exclusively on the geometric characterization of the high-rank LoS channels between the user equipment (UEs) and base station (BS). Nevertheless, even a slight error in the LoS-specific angular parameters, stemming from noisy estimates or information exchange with limited quantization levels, can significantly impact the accuracy of the channel estimate. Additionally, neglecting significant Non-Line-of-Sight (NLoS) components in the channel characterization may render LoS-only estimates ineffective. Given limited pilot resources, bidirectional over-the-air (OTA) transmit-receive beamformer training proves advantageous, eliminating the need for explicit antenna-specific channel estimation. Typically, lacking prior knowledge about the channel characteristics, the forward-backward beamformer training is initialized with a set of stream-specific random beamformers. This paper proposes a trans-mission design procedure that begins with LoS channel estimation using two downlink pilots and geometry information feedback from UEs, followed by an initial precoder design algorithm at the BS based on the LoS channel estimate to initialize beamformers for the OTA bidirectional beam training procedure. Simulation results demonstrate that such a bidirectional algorithm can achieve significantly higher rates within a few iterations compared to traditional forward-backward beam training procedures with random initialization.
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