Evaluation of the performance of different channel estimation smoothing algorithms in NR base stations

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Volume Title

School of Science | Master's thesis

Authors

Date

2025-05-16

Department

Major/Subject

Computer Science

Mcode

Degree programme

Master's Programme in Computer, Communication and Information Sciences

Language

en

Pages

49

Series

Abstract

Wireless cellular networks are being continuously improved to support advanced functionality, as witnessed recently by the development of New Radio standards. A base station forms a central part of a wireless cellular network, where fast and reliable data processing is only possible due to 1) the utilization of high performance Digital Signal Processing (DSP) hardware, and 2) the development and usage of highly specialized and optimized low-level DSP code. In this study, the performance evaluation of two channel estimation smoothing algorithms was conducted on a DSP hardware. The first algorithm, which is referred to as 'the reference' model, calculates convolution of raw channel estimates with a given pre-defined filter, by its mathematical definition. The second approach is based on 'the overlap add' method, and utilizes the properties of the Fast Fourier Transform (FFT) to optimize convolution calculations. Despite the theoretical promise of the overlap add method, the current implementation suggests that the reference approach outperforms such method by at least 60 percent, when FFT sizes of 64 and 128 are used. However, testing also indicates that increasing the FFT size, from 64 to 128, results in up to a threefold increase in performance. This leaves huge room for improvement with further low-level DSP code optimization, by exploring larger FFT sizes, including 256 and possibly 512.

Description

Supervisor

Wichman, Risto

Thesis advisor

Sadi, Toufik

Keywords

new radio, physical layer, physical uplink shared channel, channel estimation, channel estimation smoothing, digital signal processing

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Citation

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202506174825

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[dipl] Perustieteiden korkeakoulu / SCI