Compressed-Sensing based Beam Detection in 5G NR Initial Access
Junmo Sung, Brian L Evans
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To support millimeter wave (mmWave) frequency bands in cellular communications, both the base station and the mobile platform utilize large antenna arrays to steer narrow beams towards each other to compensate the path loss and improve communication performance.
The time-frequency resource allocated for initial access, however, is limited, which gives rise to need for efficient approaches for beam detection.
For hybrid analog-digital beamforming (HB) architectures, which are used to reduce power consumption,we propose a compressed sensing (CS) based approach for 5G initial access beam detection that is for a HB architecture and that is compliant with the 3GPP standard.
The CS-based approach is compared with the exhaustive search in terms of beam detection accuracy and by simulation is shown to outperform.
Up to 256 antennas are considered, and the importance of a careful codebook design is reaffirmed.
The time-frequency resource allocated for initial access, however, is limited, which gives rise to need for efficient approaches for beam detection.
For hybrid analog-digital beamforming (HB) architectures, which are used to reduce power consumption,we propose a compressed sensing (CS) based approach for 5G initial access beam detection that is for a HB architecture and that is compliant with the 3GPP standard.
The CS-based approach is compared with the exhaustive search in terms of beam detection accuracy and by simulation is shown to outperform.
Up to 256 antennas are considered, and the importance of a careful codebook design is reaffirmed.