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Efficient Compressive Sensing Detectors for Generalized Spatial Modulation Systems.

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Title: Efficient Compressive Sensing Detectors for Generalized Spatial Modulation Systems.
Authors: Xiao, Lixia1, Yang, Ping1, Xiao, Yue2, Fan, Shiwen1, Di Renzo, Marco3, Xiang, Wei3, Li, Shaoqian1
Source: IEEE Transactions on Vehicular Technology. Feb2017, Vol. 66 Issue 2, p1284-1298. 15p.
Subjects: Algorithms -- Social aspects, Spatial ability, Detectors, Computational complexity, Probability theory
Abstract: Generalized spatial modulation (GSM) is a novel multiple-input–multiple-output (MIMO) technique, which relies on a sparse use of radio-frequency (RF) front ends at the transmitter. In this paper, low-complexity and compressive-sensing (CS)-based detectors for GSM systems are proposed. First, an extension of the normalized CS detector (E-NCS) based on the orthogonal matching pursuit (OMP) algorithm is proposed, which is shown to be suitable for large-scale GSM implementations, due to its low complexity. Furthermore, to mitigate the error floor effect of the E-NCS detector, two efficient CS (ECS) detectors based on the OMP algorithm are designed with the aid of a preset threshold. Specifically, different searching algorithms are designed, whose objective is to balance computational complexity and system performance. An upper bound for the average bit error probability (ABEP) of the first ECS detector is derived and used to optimize the preset threshold. Simulation results show that the proposed ECS detectors are capable of achieving a considerable reduction in computational complexity, compared with other near-optimal algorithms, with a negligible performance loss. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Transactions on Vehicular Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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PubType: Academic Journal
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  Data: Efficient Compressive Sensing Detectors for Generalized Spatial Modulation Systems.
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  Data: <searchLink fieldCode="AR" term="%22Xiao%2C+Lixia%22">Xiao, Lixia</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yang%2C+Ping%22">Yang, Ping</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xiao%2C+Yue%22">Xiao, Yue</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Fan%2C+Shiwen%22">Fan, Shiwen</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Di+Renzo%2C+Marco%22">Di Renzo, Marco</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Xiang%2C+Wei%22">Xiang, Wei</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Li%2C+Shaoqian%22">Li, Shaoqian</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Vehicular+Technology%22">IEEE Transactions on Vehicular Technology</searchLink>. Feb2017, Vol. 66 Issue 2, p1284-1298. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Algorithms+--+Social+aspects%22">Algorithms -- Social aspects</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+ability%22">Spatial ability</searchLink><br /><searchLink fieldCode="DE" term="%22Detectors%22">Detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+complexity%22">Computational complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+theory%22">Probability theory</searchLink>
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  Data: Generalized spatial modulation (GSM) is a novel multiple-input–multiple-output (MIMO) technique, which relies on a sparse use of radio-frequency (RF) front ends at the transmitter. In this paper, low-complexity and compressive-sensing (CS)-based detectors for GSM systems are proposed. First, an extension of the normalized CS detector (E-NCS) based on the orthogonal matching pursuit (OMP) algorithm is proposed, which is shown to be suitable for large-scale GSM implementations, due to its low complexity. Furthermore, to mitigate the error floor effect of the E-NCS detector, two efficient CS (ECS) detectors based on the OMP algorithm are designed with the aid of a preset threshold. Specifically, different searching algorithms are designed, whose objective is to balance computational complexity and system performance. An upper bound for the average bit error probability (ABEP) of the first ECS detector is derived and used to optimize the preset threshold. Simulation results show that the proposed ECS detectors are capable of achieving a considerable reduction in computational complexity, compared with other near-optimal algorithms, with a negligible performance loss. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of IEEE Transactions on Vehicular Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TVT.2016.2558205
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        Text: English
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      – SubjectFull: Algorithms -- Social aspects
        Type: general
      – SubjectFull: Spatial ability
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      – SubjectFull: Detectors
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      – SubjectFull: Computational complexity
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      – SubjectFull: Probability theory
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              Text: Feb2017
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