Studies from University of Science and Technology China Have Provided New Data o n Machine Learning [Machine Learning-inspired Hybrid Precodin g With Low-resolution Phase Shifters for Intelligent Reflecting Surface (Irs) Ma ssive Mimo Systems With ...]

中国科技大学的研究为机器学习提供了新的数据[机器学习启发的低分辨率移相器混合预编码G用于智能反射表面(Irs)Ma SIMO系统.]

Robotics & Machine Learning Daily News2024，Issue(Jun.6) ：101-102.

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Studies from University of Science and Technology China Have Provided New Data o n Machine Learning [Machine Learning-inspired Hybrid Precodin g With Low-resolution Phase Shifters for Intelligent Reflecting Surface (Irs) Ma ssive Mimo Systems With ...]

中国科技大学的研究为机器学习提供了新的数据[机器学习启发的低分辨率移相器混合预编码G用于智能反射表面(Irs)Ma SIMO系统.]

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摘要

机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx记者从中华民国安徽发回的新闻报道，研究表明：“混合预编码(HP)中移相器(PS)所需的比特数对和速率、频谱效率(SE)和能量效率(EE)有显著影响。实际的大容量多输入多输出T(MIMO)系统的空间和成本限制了基站(BS)的天线数量，限制理论分析承诺的吞吐量增益。本研究的资金来源包括中央大学基础研究基金、国家自然科学基金(NSFC)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Anhui, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “The number of bits required in phase shifters (PS) in hybrid precoding (HP) has a significa nt impact on sum-rate, spectral efficiency (SE), and energy efficiency (EE). The space and cost constraints of a realistic massive multiple-input multiple-outpu t (MIMO) system limit the number of antennas at the base station (BS), limiting the throughput gain promised by theoretical analysis.” Funders for this research include Fundamental Research Funds for the Central Uni versities, National Natural Science Foundation of China (NSFC).

Key words

Anhui/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/University of Science and Tec hnology China

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出版年

2024

Robotics & Machine Learning Daily News

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