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EN
With the advent of massive MIMO and mmWave, Antenna selection is the new frontier in hybrid beamforming employed in 5G base stations. Tele-operators are reworking on the components while upgrading to 5G where the antenna is a last-mile device. The burden on the physical layer not only demands smart and adaptive antennas but also an intelligent antenna selection mechanism to reduce power consumption and improve system capacity while degrading the hardware cost and complexity. This work focuses on reducing the power consumption and finding the optimal number of RF chains for a given millimeter wave massive MIMO system. At first, we investigate the power scaling method for both perfect Channel State Information (CSI) and imperfect CSI where the power is reduced by1/Nᵣ and 1/√Nᵣ respectively. We further propose to reduce the power consumption by emphasizing on the subdued resolution of Analog-to-Digital Converters (ADCs) with quantization awareness. The proposed algorithm selects the optimal number of antenna elements based on the resolution of ADCs without compromising on the quality of reception. The performance of the proposed algorithm shows significant improvement when compared with conventional and random antenna selection methods.
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EN
The paper is devoted to a numerical analysis of an influence of a pumping beam diameter on output power of optically pumped vertical-external-cavity surface-emitting lasers. Simulations have been carried out for a structure with a GaInNAs/GaAs active region operating at 1.32 μm. Various assembly configurations have been considered. Results obtained show that laser power scaling is strongly affected by thermal properties of the device.
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