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首页> 外文期刊>Progress in Artificial Intelligence >Cell ID and Angle of Departure Estimation for Millimeter-wave Cellular Systems in Line-of-Sight Dominant Conditions Using Zadoff-Chu Sequence Based Beam Weight
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Cell ID and Angle of Departure Estimation for Millimeter-wave Cellular Systems in Line-of-Sight Dominant Conditions Using Zadoff-Chu Sequence Based Beam Weight

机译：基于Zadoff-Chu序列的光束重量，毫米波蜂窝系统中毫米波蜂窝系统的小区ID和偏离估计角度

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摘要

Millimeter-wave (mmWave) bands is considered for fifth-generation (5G) cellular systems because abundant spectrum is available for mobile broadband communications. In mmWave communication systems, accurate beamforming is important to compensate for high attenuation in the mmWave frequency band and to extend the transmission range. However, with the existing beamformers in mmWave cellular systems, the mobile station (MS) cannot identify the source (base station; BS) of the received beam because there are many neighboring BSs transmitting their training signals, requiring a large overhead. This paper proposes a new beam weight generation method for transmitting (Tx) beamformers at the BS in mmWave cellular systems during a beam training period. Beam weights are generated for Tx beamformers at neighboring BSs, so that a mobile station (MS) can estimate the source (cell ID; CID) and angle of departure (AoD) for each BS in multi-cell environments. A CID and AoD estimation method for mmWave cellular systems in a line-of-sight (LOS) dominant condition is presented using the beam weights generated by Zadoff-Chu sequence. A simulation is conducted in a LOS dominant condition to show that the performances of CID detection and AoD estimation are similar for both the proposed and conventional methods. In the conventional methods, the DFT-based beamforming weight is used for Tx beamformer at the BS and orthogonal matching pursuit (OMP) algorithm is used for AoD estimation at the MS. The proposed method significantly reduces the processing time (1.6-6.25%) required for beam training compared to the conventional method.
机译：对于第五代（5G）蜂窝系统考虑毫米波（MMWAVE）带，因为可以用于移动宽带通信的丰富频谱。在MMWAVE通信系统中，精确的波束成形是重要的，可以补偿MM波频带中的高衰减并延长传输范围。然而，利用MMWAVE蜂窝系统中的现有波束形成器，移动台（MS）不能识别所接收光束的源（基站; BS），因为存在许多相邻的BSS发送其训练信号，需要大开销。本文提出了一种新的光束重量生成方法，用于在光束训练期间MM波蜂窝系统中的BS处发送（TX）波束形成器。在相邻BSS处针对Tx波束形成器生成光束重量，使得移动台（MS）可以估计多小区环境中的每个BS的源（小区ID; CID）和偏离角度（AOD）。使用由Zadoff-Chu序列产生的光束权重呈现了视线中的MMWave蜂窝系统的CID和AOD估计方法。在LOS主导条件下进行模拟以表明CID检测和AOD估计的性能对于所提出的和传统方法类似。在传统方法中，基于DFT的波束成形重量用于BS的Tx波束形成器，并且正交匹配追踪（OMP）算法用于MS处的AOD估计。与传统方法相比，所提出的方法显着降低了光束训练所需的处理时间（1.6-6.25％）。

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