Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems
Grant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and es...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/1672421 |
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| author | Yang Yang Guanghua Song Hui Liu |
| author_facet | Yang Yang Guanghua Song Hui Liu |
| author_sort | Yang Yang |
| collection | DOAJ |
| description | Grant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and estimation of channels in grant-free RA. The approach incorporates two distinct preamble structures: the single orthogonal preamble (SOP) and the concatenated orthogonal preamble (COP). The proposed algorithms make full use of the inherent quasiorthogonal characteristic of massive MIMO, thereby enabling the accurate estimation of user channels while effectively avoiding collisions in the preambles. As a result, these algorithms generate highly precise estimations of user channels. To substantiate the effectiveness of the proposed algorithms, this paper provides an extensive theoretical analysis and presents a comprehensive set of experimental results. These findings offer robust evidence for the efficacy of the algorithms in substantially bolstering the performance of grant-free RA. Additionally, we have conducted further research and analysis, which has led to additional insights and refinements in our proposed approach. Moreover, the experimental results validate the statistical significance and reliability of the performance enhancements achieved by these algorithms. Moreover, the proposed approach exhibits robustness in scenarios with different levels of user density and varying channel conditions. Through a thorough analysis of these scenarios, we showcase the versatility and applicability of our algorithms in real-world environments. |
| format | Article |
| id | doaj-art-78f13e369aee4136b549081428ee9dc6 |
| institution | Kabale University |
| issn | 2090-0155 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-78f13e369aee4136b549081428ee9dc62025-02-03T06:47:29ZengWileyJournal of Electrical and Computer Engineering2090-01552023-01-01202310.1155/2023/1672421Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO SystemsYang Yang0Guanghua Song1Hui Liu2School of Information and Safety EngineeringSchool of Information and Safety EngineeringResearch Center of Hubei Logistics DevelopmentGrant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and estimation of channels in grant-free RA. The approach incorporates two distinct preamble structures: the single orthogonal preamble (SOP) and the concatenated orthogonal preamble (COP). The proposed algorithms make full use of the inherent quasiorthogonal characteristic of massive MIMO, thereby enabling the accurate estimation of user channels while effectively avoiding collisions in the preambles. As a result, these algorithms generate highly precise estimations of user channels. To substantiate the effectiveness of the proposed algorithms, this paper provides an extensive theoretical analysis and presents a comprehensive set of experimental results. These findings offer robust evidence for the efficacy of the algorithms in substantially bolstering the performance of grant-free RA. Additionally, we have conducted further research and analysis, which has led to additional insights and refinements in our proposed approach. Moreover, the experimental results validate the statistical significance and reliability of the performance enhancements achieved by these algorithms. Moreover, the proposed approach exhibits robustness in scenarios with different levels of user density and varying channel conditions. Through a thorough analysis of these scenarios, we showcase the versatility and applicability of our algorithms in real-world environments.http://dx.doi.org/10.1155/2023/1672421 |
| spellingShingle | Yang Yang Guanghua Song Hui Liu Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems Journal of Electrical and Computer Engineering |
| title | Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems |
| title_full | Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems |
| title_fullStr | Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems |
| title_full_unstemmed | Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems |
| title_short | Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems |
| title_sort | joint user detection and channel estimation in grant free random access for massive mimo systems |
| url | http://dx.doi.org/10.1155/2023/1672421 |
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