Abstract:The narrow millimetre wave beam in future 5G networks is easily interrupted by the movement of mobile handsets including both location change and self-rotation. In this paper, a three-dimensional (3-D) beam tracking method is proposed to achieve beam alignment between the access node (AN) and the user node (UN). A gradient descent algorithm is employed for self-rotation tracking based on measurements obtained by the three smart phone sensors (gyroscope, accelerometer and magnetometer) embedded in the micro-electro-mechanical system (MEMS). An extended Kalman filtering (EKF) based location tracking algorithm is also incorporated into the design by combining the data from direction of arrival (DoA) and time of arrival (ToA) estimation results of the user node (UN), since accurate UN location information is also crucial in the beam tracking process. Moreover, an operation protocol is developed to coordinate the tracking process and tested in different scenarios.
Positional modulation (PM) has been introduced recently where a given modulation pattern can only be received at certain desired positions. To achieve it, the multi-path effect is exploited for positional modulation with the aid of metasurface acting as a low-cost flexible reflecting surface. In this paper, sparse antenna array based positional modulation design is proposed for the first time; to reduce the implementation complexity of the metasurface, the number of active units is also minimised for a given PM design requirement. Design examples are provided to show the effectiveness of the proposed design.
Due to the narrow beam in millimetre wave communication for future 5G networks, small device movements in the form of either self-rotation or displacement can result in serious power loss. In this paper, a three-dimensional (3-D) beam tracking method employing extended Kalman filtering (EKF) is proposed based on antenna arrays and the three smart phone sensors, which are gyroscope, accelerometer and magnetometer, embedded in the micro-electro-mechanical system (MEMS) inside the smart phone. The EKF-based location tracking is also incorporated into the design by combing the data from direction of arrival (DoA) and time of arrival (ToA) estimation results of the user node (UN), since accurate UN location information is also very important in the process of beam tracking to achieve beam alignment between the access node (AN) and the UN.
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