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Full Duplex DD for In-Band D2D Communication
Wireless Personal Communications ( IF 1.9 ) Pub Date : 2020-06-18 , DOI: 10.1007/s11277-020-07593-8
Omar Hayat , Razali Ngah , Siti Zaiton Mohd Hashim

Device to device (D2D) communication is a candidate technology to ascertain the 5G wireless system. To implement the D2D communication in an in-band cellular network, device discovery (DD) is a primary and critical task. A positioning reference signal has been incorporated to discover the device in the 4G-LTE system, but the DD is still a challenge due to the non-line of sight (NLOS) and scattering environment. The discovery signal distorts due to these challenges at both device and base station ends. Along with NLOS and scattering, the practical issues for the DD are the latency, precision, and energy efficiency. They need special attention to achieve, because of the random mobility of the devices. A full-duplex (FD) DD procedure is suggested in which the discovery signal is transmitted from both ends. To solve these challenges and attains effective DD procedure, the log-likelihood maximization and estimation based algorithm is applied on the FD signal from three base stations (triangulation). It incorporates the FD and triangulation-based data, NLOS characteristics, elliptical scattering model, and MUSIC spectrum information for direction of arrival. It reduces the 40% energy consumption by linear estimation and achieves maximum discovery at 220 iterations. It also reduces the average discovery (position) error 52 cm according to KPI of 5G. The proposed system is a comprehensive work managing fundamental issues developing DD in practical situations: directionality, impediment forces, environment supervision, and base station coordination.



中文翻译:

全双工DD,用于带内D2D通信

设备到设备(D2D)通信是确定5G无线系统的一项候选技术。为了在带内蜂窝网络中实现D2D通信,设备发现(DD)是一项主要且关键的任务。定位参考信号已被并入以发现4G-LTE系统中的设备,但由于非视线(NLOS)和散射环境,DD仍然是一个挑战。由于设备和基站端的这些挑战,发现信号失真。除NLOS和散射外,DD的实际问题还包括等待时间,精度和能效。由于设备的随机移动性,它们需要特别注意才能实现。建议使用全双工(FD)DD程序,其中从两端发送发现信号。为了解决这些挑战并获得有效的DD程序,将基于对数似然最大化和估计的算法应用于来自三个基站的FD信号(三角测量)。它结合了基于FD和三角测量的数据,NLOS特性,椭圆散射模型和MUSIC频谱信息以用于到达方向。它通过线性估计减少了40%的能耗,并在220次迭代中实现了最大发现。根据5G的KPI,它还可将平均发现(位置)误差降低52 cm。提议的系统是一项综合工作,管理在实际情况下发展DD的基本问题:方向性,障碍力,环境监管和基站协调。将基于对数似然最大化和估计的算法应用于来自三个基站的FD信号(三角测量)。它结合了基于FD和三角测量的数据,NLOS特性,椭圆形散射模型以及MUSIC频谱信息以用于到达方向。它通过线性估计减少了40%的能耗,并在220次迭代中实现了最大发现。根据5G的KPI,它还可将平均发现(位置)误差降低52 cm。拟议的系统是一项综合工作,管理在实际情况下发展DD的基本问题:方向性,障碍力,环境监管和基站协调。将基于对数似然最大化和估计的算法应用于来自三个基站的FD信号(三角测量)。它结合了基于FD和三角测量的数据,NLOS特性,椭圆形散射模型以及MUSIC频谱信息以用于到达方向。它通过线性估计减少了40%的能耗,并在220次迭代中实现了最大发现。根据5G的KPI,它还可将平均发现(位置)误差降低52 cm。拟议的系统是一项综合工作,管理在实际情况下发展DD的基本问题:方向性,障碍力,环境监管和基站协调。和MUSIC频谱信息以了解到达方向。它通过线性估计减少了40%的能耗,并在220次迭代中实现了最大发现。根据5G的KPI,它还可将平均发现(位置)误差降低52 cm。拟议的系统是一项综合工作,管理在实际情况下发展DD的基本问题:方向性,障碍力,环境监管和基站协调。和MUSIC频谱信息以了解到达方向。它通过线性估计减少了40%的能耗,并在220次迭代中实现了最大发现。根据5G的KPI,它还可将平均发现(位置)误差降低52 cm。拟议的系统是一项综合工作,管理在实际情况下发展DD的基本问题:方向性,障碍力,环境监管和基站协调。

更新日期:2020-06-18
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