Data-Aided Channel-Gain Calibration Algorithm for Recovering Channel Amplitude Reciprocity in SFLC-OFDM Systems

This paper proposes a practical gain calibration algorithm that estimates and compensates for channel amplitude asymmetry in a space-frequency line code (SFLC) orthogonal frequency division multiplexing (OFDM) system. During uplink (UL) communications from the base station (BS) to user equipment (UE...

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Veröffentlicht in:IEEE access Jg. 13; S. 44231 - 44242
Hauptverfasser: Lee, Songmin, Joung, Jingon, Choi, Jihoon, Kim, Juyeop
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 2025
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ISSN:2169-3536, 2169-3536
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Zusammenfassung:This paper proposes a practical gain calibration algorithm that estimates and compensates for channel amplitude asymmetry in a space-frequency line code (SFLC) orthogonal frequency division multiplexing (OFDM) system. During uplink (UL) communications from the base station (BS) to user equipment (UE), the SFLC BS can acquire channel state information (CSI) for downlink (DL) communications from the BS to the UE by utilizing UL-DL channel reciprocity. However, the channel amplitudes between UL and DL are generally observed to be asymmetric in practical channels. This asymmetry results in an unexpected phase rotation of the decoded SFLC symbols at the UE, as the CSI used for SFLC encoding at the BS does not align with the actual DL channels. To address this issue, we have designed a data-aided channel-gain calibration algorithm (CCA). Based on the mathematical derivation of the phase rotation of received SFLC data symbols at the UE, we developed the CCA to adjust the received gain and restore channel amplitude symmetry. To practically validate the designed CCA, we implemented an off-the-shelf SFLC-OFDM communication system on a software modem testbed using Universal Software Radio Peripherals (USRPs). Experiments conducted with real-time SFLC-OFDM signals demonstrate that the proposed CCA significantly enhances SFLC decoding performance.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2025.3549046