1 Ocak 2022 Konferans bildirisi Açık Erişim

Nayir, Hasan; Karakoca, Erhan; Gorcin, Ali; Qaraqe, Khalid

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        "name": "Nayir, Hasan"
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      {
        "name": "Karakoca, Erhan"
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      {
        "name": "Gorcin, Ali"
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      {
        "affiliation": "Texas A&M Univ Qatar, Dept Elect & Comp Engn, Doha, Qatar", 
        "name": "Qaraqe, Khalid"
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    "description": "Frequency scarcity implies the utilization of higher frequencies for wireless communications; however, spreading loss becomes a dominating issue as the frequency increases to the level of and beyond millimeter waves. To this end, massive multiple-input multiple-output structures introduce mitigation alternatives. However, to make these solutions possible, the channel estimation approach strives to be modified: since Rayleigh distance is very short for conventional systems, the only far-field channel is examined in that context. On the other hand, the implementation of massive antenna arrays in high frequencies increases Rayleigh distance; thus, both near-field and far-field analyses become necessary. Instead of a dual estimation process, it would be effective and efficient to develop hybrid-field channel estimation techniques. Therefore, in this study, a new channel estimation method which is based on convolutional autoencoder (CAE) and orthogonal matching pursuit (OMP) approach, is proposed for hybrid channel estimation. The results indicate that the proposed OMP-CAE method has much better error performance when compared to the conventional OMP algorithm, especially at low signal-to-noise ratio regimes.", 
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    "meeting": {
      "title": "2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL)"
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    "publication_date": "2022-01-01", 
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    "title": "Hybrid-Field Channel Estimation for Massive MIMO Systems based on OMP Cascaded Convolutional Autoencoder"
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