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Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink.

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Title: Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink.
Authors: Sorna Keerthi, R.1 sornakeerthi@rediffmail.com, Meena Alias Jeyanthi, K.2
Source: Journal of Intelligent & Fuzzy Systems. 2018, Vol. 34 Issue 6, p4331-4344. 14p.
Subjects: Trellis-coded modulation, Least squares, Channel estimation, Global optimization, Mathematical optimization
Abstract: LTE-A downlink transfers data and control information from base station to mobile. To reduce the mean square error between original and estimated channel, pilot/training based channel estimation like Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE) are ubiquitous for most wireless standards. To optimize the channel, many intelligent optimized techniques were developed. GA has no guarantee in finding global optima and high convergence time. ANN suits only linear solutions and more training period. PSO fits high dimensional space but needs more iterations. ABC has limited search space by initial solution. CS requires large resources and high computational time. To overcome these effects, an effortless Trellis Coded Firefly Optimized LMMSE based algorithm is proposed to estimate the channel. TCM has high spectral efficiency, more data rate and reduced error. FA has low complexity, easy implementation, automatic subdivision of groups to find local/global optima and ability to deal with multimodality. At SNR = 10 dB, LSE has high MSE of 10–2, LMMSE has 15.85% reduced MSE than LSE. The previous optimized methods have MSE ranging from 10–3 to 10–2 but the proposed method with 64-QAM has MSE range of 10–5 to 10–4, which is 100 times reduced. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. 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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  Data: Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink.
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  Data: <searchLink fieldCode="DE" term="%22Trellis-coded+modulation%22">Trellis-coded modulation</searchLink><br /><searchLink fieldCode="DE" term="%22Least+squares%22">Least squares</searchLink><br /><searchLink fieldCode="DE" term="%22Channel+estimation%22">Channel estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Global+optimization%22">Global optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink>
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  Label: Abstract
  Group: Ab
  Data: LTE-A downlink transfers data and control information from base station to mobile. To reduce the mean square error between original and estimated channel, pilot/training based channel estimation like Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE) are ubiquitous for most wireless standards. To optimize the channel, many intelligent optimized techniques were developed. GA has no guarantee in finding global optima and high convergence time. ANN suits only linear solutions and more training period. PSO fits high dimensional space but needs more iterations. ABC has limited search space by initial solution. CS requires large resources and high computational time. To overcome these effects, an effortless Trellis Coded Firefly Optimized LMMSE based algorithm is proposed to estimate the channel. TCM has high spectral efficiency, more data rate and reduced error. FA has low complexity, easy implementation, automatic subdivision of groups to find local/global optima and ability to deal with multimodality. At SNR = 10 dB, LSE has high MSE of 10–2, LMMSE has 15.85% reduced MSE than LSE. The previous optimized methods have MSE ranging from 10–3 to 10–2 but the proposed method with 64-QAM has MSE range of 10–5 to 10–4, which is 100 times reduced. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. 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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      – Type: doi
        Value: 10.3233/JIFS-17840
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 4331
    Subjects:
      – SubjectFull: Trellis-coded modulation
        Type: general
      – SubjectFull: Least squares
        Type: general
      – SubjectFull: Channel estimation
        Type: general
      – SubjectFull: Global optimization
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
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      – TitleFull: Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink.
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            NameFull: Sorna Keerthi, R.
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            NameFull: Meena Alias Jeyanthi, K.
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            – D: 01
              M: 06
              Text: 2018
              Type: published
              Y: 2018
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              Value: 34
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            – TitleFull: Journal of Intelligent & Fuzzy Systems
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