標題: Traffic-Aware Beam Selection and Resource Allocation for 5G NR
作者: Liu, Yu-Hsuan
Lin, Kate Ching-Ju
資訊工程學系
Department of Computer Science
公開日期: 1-Jan-2020
摘要: 3GPP has been defining 5G New Radio (NR), a new radio access technology, to enhance flexibility, scalability, and efficiency of 5G networks. An increasing data rate can be achieved by leveraging antenna arrays to adaptively form multiple directional beams and serve geo-distributed user equipments (UEs) concurrently. However, the imperfect beam pattern of an antenna array may create side lobes, leading to inter-user interference. While most recent research focuses on beam selection that mitigates inter-user interference and maximizes the sum rate, we, however, notice that the selected beams may not be fully utilized. The root cause is that only a fixed set of beams can be configured at a time to serve a wide frequency band but some resource blocks (i.e., subcarriers) may not be able to be allocated to any UEs due to limited traffic demands. To address such inefficiency, this paper presents traffic-aware joint beam configuration and resource allocation, which explicitly considers UEs' traffic demands and configures beams that can be optimally utilized in all the RBs (i.e., the operational frequency band). Our simulation results show that our traffic-aware allocation configures beams with better utilization and achieve an effective throughput much higher than conventional maximal capacity configuration.
URI: http://hdl.handle.net/11536/155536
ISBN: 978-1-7281-3106-1
ISSN: 1525-3511
期刊: 2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)
起始頁: 0
結束頁: 0
Appears in Collections:Conferences Paper