Coordinated Spectral Efficiency Prediction for Real-World 5G CoMP Systems

Fuente: arXiv
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Autori principali: Chen, Zhixing, Fan, Zhaoyu, Li, Yang, Kang, Yibin, Yan, Qi, Shi, Qingjiang
Natura: Preprint
Pubblicazione: 2024
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author Chen, Zhixing
Fan, Zhaoyu
Li, Yang
Kang, Yibin
Yan, Qi
Shi, Qingjiang
author_facet Chen, Zhixing
Fan, Zhaoyu
Li, Yang
Kang, Yibin
Yan, Qi
Shi, Qingjiang
contents Coordinated multipoint (CoMP) systems incur substantial resource consumption due to the management of backhaul links and the coordination among various base stations (BSs). Accurate prediction of coordinated spectral efficiency (CSE) can guide the optimization of network parameters, resulting in enhanced resource utilization efficiency. However, characterizing the CSE is intractable due to the inherent complexity of the CoMP channel model and the diversity of the 5G dynamic network environment, which poses a great challenge for CSE prediction in real-world 5G CoMP systems. To address this challenge, in this letter, we propose a data-driven model-assisted approach. Initially, we leverage domain knowledge to preprocess the collected raw data, thereby creating a well-informed dataset. Within this dataset, we explicitly define the target variable and the input feature space relevant to channel statistics for CSE prediction. Subsequently, a residual-based network model is built to capture the high-dimensional non-linear mapping function from the channel statistics to the CSE. The effectiveness of the proposed approach is validated by experimental results on real-world data.
format Preprint
id arxiv_https___arxiv_org_abs_2408_07320
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Coordinated Spectral Efficiency Prediction for Real-World 5G CoMP Systems
Chen, Zhixing
Fan, Zhaoyu
Li, Yang
Kang, Yibin
Yan, Qi
Shi, Qingjiang
Signal Processing
Coordinated multipoint (CoMP) systems incur substantial resource consumption due to the management of backhaul links and the coordination among various base stations (BSs). Accurate prediction of coordinated spectral efficiency (CSE) can guide the optimization of network parameters, resulting in enhanced resource utilization efficiency. However, characterizing the CSE is intractable due to the inherent complexity of the CoMP channel model and the diversity of the 5G dynamic network environment, which poses a great challenge for CSE prediction in real-world 5G CoMP systems. To address this challenge, in this letter, we propose a data-driven model-assisted approach. Initially, we leverage domain knowledge to preprocess the collected raw data, thereby creating a well-informed dataset. Within this dataset, we explicitly define the target variable and the input feature space relevant to channel statistics for CSE prediction. Subsequently, a residual-based network model is built to capture the high-dimensional non-linear mapping function from the channel statistics to the CSE. The effectiveness of the proposed approach is validated by experimental results on real-world data.
title Coordinated Spectral Efficiency Prediction for Real-World 5G CoMP Systems
topic Signal Processing
url https://arxiv.org/abs/2408.07320