5G-NR跨层速率自适应,用于VoIP和终端的前台/后台应用

Jyotirmoy Karjee, Shubhneet Khatter, Diprotiv Sarkar, Hema Lakshman C. Tammineedi, Ashok Kumar Reddy Chavva
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引用次数: 6

摘要

推荐比特率(RBR)由gndeb通过MAC控制元素(CE)实体分配给用户设备(UE),以提供5G新无线电(NR)中的比特率信息。在终端,比特率信息被传递到上层;即,传输或应用,用于上行链路或下行链路中的特定逻辑通道。然而,基于特定目标的应用速率,UE不知道如何有效地利用和分配下层和上层的RBR/吞吐量,分别考虑特定的逻辑通道。为了解决这些问题,我们提出了一种跨层速率自适应(CLRA)机制。CLRA由两部分组成。在第一部分中,CLRA利用从gndeb接收到的RBR来计算底层的吞吐量。在第二部分中,CLRA根据目标的特定应用速率将从下层接收到的吞吐量在上层进行分配。CLRA提供了一种智能的机制,在前台/后台应用程序和VoIP应用程序之间分配吞吐量,考虑基于学习的编解码器适应。我们利用三星Galaxy S8设备进行了实验和仿真,验证了CLRA机制在5G NR中的应用。
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5G-NR Cross Layer Rate Adaptation for VoIP and Foreground/Background Applications in UE
The recommended bit rate (RBR) is assigned by gNodeB to the user equipment (UE) using MAC control element (CE) entity to provide bit rate information in 5G New Radio (NR). At the UE, the bit rate information is passed on to the upper layers; i.e., transport or application, for a specific logical channel either in uplink or downlink. However, based on specific application rate of target, UE does not know how to efficiently utilize and distribute RBR/throughput in lower and upper layer, respectively considering the specific logical channel. To address these problems, we propose a cross layer rate adaptation (CLRA) mechanism for UE. CLRA consists of two parts. In the first part, CLRA utilizes RBR received from gNodeB to compute throughput at lower layer. In the second part, CLRA distributes the throughput in upper layer received from lower layer based on specific applications rate of target. CLRA provides an intelligent mechanism to distribute throughput among foreground/ background applications and voice over internet protocol (VoIP) application considering a learning based codec adaptation. We conduct experiments with Samsung Galaxy S8 device and simulations to validate CLRA mechanism for applications in 5G NR.
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