Effortless trellis coded firefly optimized LMMSE based channel estimation for LTE-Advanced downlink.
Saved in:
| 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.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| 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] |
|---|---|
| ISSN: | 10641246 |
| DOI: | 10.3233/JIFS-17840 |
