A soft-output adaptive equalizer for land mobile communications based on a modified least-square solution.
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| Title: | A soft-output adaptive equalizer for land mobile communications based on a modified least-square solution. |
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| Authors: | Obata, Kazunori1, Tominaga, Hideyoshi1 |
| Source: | Electronics & Communications in Japan, Part 1: Communications. Jun2000, Vol. 83 Issue 6, p55-67. 13p. |
| Subject Terms: | *MOBILE communication systems, *TELECOMMUNICATION systems, *WIRELESS communications, LEAST squares, ERROR-correcting codes, CODING theory |
| Abstract: | Various methods have been proposed for the design of an adaptive equalizer including soft-decision decoding. Most such methods, however, are not practical since the computational complexity increases rapidly with the increase of the symbol time delay or the number of bits per symbol. This article discusses a new soft-output adaptive equalizer in which soft output is obtained within the specified computational complexity. A soft-output adaptive equalizer is proposed in which the sequence obtained by the least-square solution is corrected based on the estimation error. In order to verify the effectiveness of the proposed method, the performance is evaluated by computer simulation. It is seen that the performance of the proposed system depends on the ratio (L/m) of the maximum symbol time delay L and the number m of data in a block. Performance close to that of maximum-likelihood estimation is obtained when L/m is large. In particular, when the error-correcting code with the minimum Hamming distance d is used in the two-ray model, a performance close to the theoretical performance of a combination of the maximum-likelihood sequence estimation and maximum-likelihood decoding is obtained. © 2000 Scripta Technica, Electron Comm Jpn Pt 1, 83(6): 55–67, 2000 [ABSTRACT FROM AUTHOR] |
| Copyright of Electronics & Communications in Japan, Part 1: Communications is the property of Wiley-Blackwell 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: | Business Source Index |
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