XL-MIMO 系统中基于稀疏度自适应匹配追踪算法的混合场信道估计

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中图分类号：TN929.5；TN911.22 文献标志码：A 文章编号：1007-2683（2025）05-0106-08

Abstract：Compared to the massive multiple-input multiple-output （MassiveMIMO）of 5G，theExtra-Large Masive MultipleInput Multiple-Output（XL-MIMO）of6Gutilizesanultra-large-scaleantennaarray，resultingintheexistenceofhybrid-field chanels.Existingchannelestimationschemesforfar-fieldandnear-fieldchannelsareinacuratewhenappiedtotheestimationof hybrid-fieldchannelstateinformation.Aditionally，obtainingthesparsityofchannelsinpracticalcommunicationscenariosis challenging.Thispaperproposesahybrid-fieldchanelestimationschemebasedontheSparseAdaptive MatchingPursuit（SAMP） algorithm.Specifically，theSAMPalgorithmdoesnotrequirepriorknowledgeofthesparsityoffar-fieldandnear-fieldchannels.By exploitingthecharactersticsofresidualsthroughinnerproductoperations，itidentifiesthesupportsetofallnon-sparselements coresponding tothesensingmatrixMoreover，bystingathresholdandcomputingthediferencebetweethenewandoldresiduals， non-sparseelementscoespondingtothechannelareidentfied，enablingchaelstiationSimulationresultsdmonstrateatthe proposed hybrid-field SAMPschemecan efectively estimate hybrid-field channelseven in the absenceof prior knowledgeof F1-score （20 sparsity，and it outperforms existing channel estimation schemes in terms of performance.

Keywords：XL-MIMO;channel state information;sparse adaptive matching pursuit ;hybrid-field;channel estimatior

0 引言

超大规模海量多输入多输出（extra-largemas-sivemultiple-inputmultiple-output，XL-MIMO）是无线通信领域的一项重要技术，在6G中具有重要意义，为高速移动数据传输、物联网和智能城市等场景提供了强大的支持[1-2]。（剩余11145字）