基于超密集組網(wǎng)的無線傳輸容量優(yōu)化方法研究

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摘要：超密集組網(wǎng)（UDN）是5G/6G網(wǎng)絡(luò)擴(kuò)容關(guān)鍵技術(shù)，但微基站密度大幅提升導(dǎo)致跨層干擾。鑒于此本文提出了優(yōu)化方法：利用分布式探針采集參數(shù)，改進(jìn)支持向量機(jī)識別容量瓶頸，構(gòu)建深度強(qiáng)化學(xué)習(xí)自適應(yīng)模型優(yōu)化資源。實(shí)驗(yàn)表明，該方案有效提升了吞吐量和頻譜效率，相較于傳統(tǒng)方法具有明顯優(yōu)勢。

關(guān)鍵詞：超密集組網(wǎng)；無線傳輸容量；支持向量機(jī)；優(yōu)化方法

doi：10.3969/J.ISSN.1672-7274.2025.03.002

中圖分類號：TN 929.5          文獻(xiàn)標(biāo)志碼：B            文章編碼：1672-7274（2025）03-000-03

Research on Optimization Methods for Wireless Transmission Capacity

Based on Ultra-Dense Network

WU Lian

（Diqing Branch of China Mobile Communications Group Yunnan Co.， Ltd.， Diqing 674499， China）

Abstract： Ultra-Dense Network （UDN） is a key technology for capacity expansion in 5G/6G. However， the increase in the density of micro base stations leads to cross-layer interference. This paper proposes optimization methods： using distributed probes to collect parameters， improving the Support Vector Machine to identify capacity bottlenecks， and constructing a deep reinforcement learning adaptive model to optimize resources. Experiments show that this scheme effectively improves throughput and spectral efficiency and has obvious advantages compared with traditional methods.

Keywords： ultra-dense network; wireless transmission capacity; support vector machine; optimization method

0   引言

在5G網(wǎng)絡(luò)和未來6G網(wǎng)絡(luò)中，超密集組網(wǎng)（Ultra-Dense Network，UDN）被認(rèn)為是提高網(wǎng)絡(luò)容量、支持海量連接設(shè)備的關(guān)鍵技術(shù)之一[1]。（剩余4600字）