With targets of cost reduction per bit and high energy efficiency,5G and beyond call for innovation in the mmWave transmitter architecture and the power amplifier(PA)circuit.To illustrate these points,this paper first...With targets of cost reduction per bit and high energy efficiency,5G and beyond call for innovation in the mmWave transmitter architecture and the power amplifier(PA)circuit.To illustrate these points,this paper firstly explains the benefits and design implications of the hybrid beamforming structure in terms of the mmWave spectrum characteristics,energy efficiency,data rate,communication capacity,coverage and implementation technology choices.Then after reviewing the techniques to improve the power amplifier(PA)output power and efficiency,the design considerations and test results of 60 GHz and 90 GHz mmWave PAs in bulk complementary metal oxide semiconductor(CMOS)process are shown.展开更多
基金supported by the National Natural Science Foundations of China (Nos. 61306030, 61674037)the National Key R&D Program of China (Nos.2016YFC0800400, 2018YFE0205900)the National Science and Technology Major Project (No. 2018ZX03001008)
文摘With targets of cost reduction per bit and high energy efficiency,5G and beyond call for innovation in the mmWave transmitter architecture and the power amplifier(PA)circuit.To illustrate these points,this paper firstly explains the benefits and design implications of the hybrid beamforming structure in terms of the mmWave spectrum characteristics,energy efficiency,data rate,communication capacity,coverage and implementation technology choices.Then after reviewing the techniques to improve the power amplifier(PA)output power and efficiency,the design considerations and test results of 60 GHz and 90 GHz mmWave PAs in bulk complementary metal oxide semiconductor(CMOS)process are shown.
文摘为改善智能反射表面(Intelligent reflective surface,IRS)辅助的毫米波多输入多输出(Multiple⁃input multiple⁃output,MIMO)级联信道的估计精度和收敛速度,基于平行因子(Parallel factor,PARAFAC)分解模型,把常规的双线性交替最小二乘(Bilinear alternating least squares,BALS)算法改进为带松弛因子的ω⁃BALS算法和正则化的T⁃BALS,加快了收敛速度和算法稳定性。当基站、IRS元件或用户侧的阵列天线数目较大时,提出改进的奇异值(Singular value decomposition,svd)⁃BALS算法。该算法通过奇异值分解压缩张量,再利用低维度的核心张量来重构模式n矩阵。仿真结果表明,该算法的归一化均方误差性能有所提高,并且加快了收敛速度。
