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Multi-Scenario Millimeter Wave Wireless Channel Measurements and Sparsity Analysis 被引量:4
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作者 Hang Mi Bo Ai +5 位作者 Ruisi He Xin Zhou Zhangfeng Ma Mi Yang Zhangdui Zhong Ning Wang 《China Communications》 SCIE CSCD 2022年第11期16-31,共16页
Wireless channel characteristics have significant impacts on channel modeling,estimation,and communication performance.While the channel sparsity is an important characteristic of wireless channels.Utilizing the spars... Wireless channel characteristics have significant impacts on channel modeling,estimation,and communication performance.While the channel sparsity is an important characteristic of wireless channels.Utilizing the sparse nature of wireless channels can reduce the complexity of channel modeling and estimation,and improve system design and performance analysis.Compared with the traditional sub6 GHz channel,millimeter wave(mmWave)channel has been considered to be more sparse in existing researches.However,most research only assume that the mmWave channel is sparse,without providing quantitative analysis and evaluation.Therefore,this paper evaluates the sparsity of mmWave channels based on mmWave channel measurements.A vector network analyzer(VNA)-based mmWave channel sounder is developed to measure the channel at 28 GHz,and multi-scenario channel measurements are conducted.The Gini index,Rician𝐾factor and rootmean-square(RMS)delay spread are used to measure channel sparsity.Then,the key factors affecting mmWave channel sparsity are explored.It is found that antenna steering direction and scattering environment will affect the sparsity of mmWave channel.In addition,the impact of channel sparsity on channel eigenvalue and capacity is evaluated and analyzed. 展开更多
关键词 channel sparsity channel measurement mmWave channel measures of sparsity
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