Efficient Handover Mode Synchronization for NR-REDCAP on a Vector DSP

Author:

Qureshi Sheikh FaizanORCID,Damjancevic Stefan,Matus Emil,van der Wolf Pieter,Utyansky Dmitry,Fettweis Gerhard

Abstract

AbstractTo enable the low-cost design of 5 G IoT Standard reduced capability (NR-REDCAP) devices, hardware-software trade-offs must be made for various signal processing baseband kernels. Dedicated hardware for a kernel provides higher speed and power efficiency but limits the device’s programmability. With the varying range of user equipment (UE) deployment scenarios and dynamic wireless channel conditions, flexible solutions like digital signal processors (DSPs) are favorable for implementing channel estimation, channel equalization, and waveform modulation/demodulation algorithms. Due to stringent requirements on latency for algorithms like decimation, synchronization, and decoding, designers might favor dedicated hardware over DSP-based solutions. Such dedicated hardware increases the device cost as it needs to be added to the modem design solely to implement such specific algorithms. In this work, we study the most critical operation mode of synchronization for the NR-REDCAP standard,i.e., during the Handover between cells. Whereas for the enhanced mobile broadband (eMBB) 5 G NR standard, dedicated hardware might be the best implementation choice for decimation and synchronization; in contrast, for NR-REDCAP, a cost saving can be achieved by implementing and optimizing the kernels onto the vector DSP. We propose an architecture-aware methodology for implementing the most compute-intensive sub-kernels on our vector DSP. Furthermore, we perform structural optimizations to find the most effective sub-kernel variant in performance optimization. After algorithmic and structural optimizations, our results show that the synchronization procedure can be accommodated on a vector DSP with a clock frequency of 500 MHz.

Funder

N/A

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3