Doubly-Selective Channel Estimation Using Superimposed Training and Weighted First-Order Statistics
Doubly-selective channel estimation using superimposed training and complex exponential basis expansion model is considered. By taking a weighted averaging operation of the received data, a weighted first-order statistical estimator is proposed, where the time-varying channel estimation is reduced t...
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| Veröffentlicht in: | Wireless personal communications 2013-12, Vol.73 (3), p.767-778 |
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| container_end_page | 778 |
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| container_issue | 3 |
| container_start_page | 767 |
| container_title | Wireless personal communications |
| container_volume | 73 |
| creator | Dou, Gaoqi Zhang, Xianfeng He, Chunquan Gao, Jun |
| description | Doubly-selective channel estimation using superimposed training and complex exponential basis expansion model is considered. By taking a weighted averaging operation of the received data, a weighted first-order statistical estimator is proposed, where the time-varying channel estimation is reduced to the simple average-based solution of time-invariant coefficients and the dominant effect of information-induced interference on channel estimation can be suppressed. To further improve the estimation performance with a limited training power, a joint iterative channel estimation and symbol detection scheme is developed where the detected symbol is exploited to enhance estimation performance instead of being viewed as interference. Theoretical analysis and simulation results show that the proposed scheme is superior to data-dependent superimposed training scheme and competitive with the conventional time-multiplexed training in terms of symbol error rate over doubly-selective channels. |
| doi_str_mv | 10.1007/s11277-013-1215-8 |
| format | Article |
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By taking a weighted averaging operation of the received data, a weighted first-order statistical estimator is proposed, where the time-varying channel estimation is reduced to the simple average-based solution of time-invariant coefficients and the dominant effect of information-induced interference on channel estimation can be suppressed. To further improve the estimation performance with a limited training power, a joint iterative channel estimation and symbol detection scheme is developed where the detected symbol is exploited to enhance estimation performance instead of being viewed as interference. 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By taking a weighted averaging operation of the received data, a weighted first-order statistical estimator is proposed, where the time-varying channel estimation is reduced to the simple average-based solution of time-invariant coefficients and the dominant effect of information-induced interference on channel estimation can be suppressed. To further improve the estimation performance with a limited training power, a joint iterative channel estimation and symbol detection scheme is developed where the detected symbol is exploited to enhance estimation performance instead of being viewed as interference. Theoretical analysis and simulation results show that the proposed scheme is superior to data-dependent superimposed training scheme and competitive with the conventional time-multiplexed training in terms of symbol error rate over doubly-selective channels.</description><subject>Applied sciences</subject><subject>Channels</subject><subject>Communications Engineering</subject><subject>Computer Communication Networks</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Engineering</subject><subject>Exact sciences and technology</subject><subject>Networks</subject><subject>Radiocommunications</subject><subject>Signal,Image and Speech Processing</subject><subject>Software</subject><subject>Systems, networks and services of telecommunications</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Transmission and modulation (techniques and equipments)</subject><issn>0929-6212</issn><issn>1572-834X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp9kE9P4zAQxS0E0hbYD7C3XJC4ePHYSRwfUfmzSEgcCtq9WY4zKUapUzwJUr_9uiriyGk0M-_3pPcY-wXiNwihrwhAas0FKA4SKt4csQVUWvJGlf-O2UIYaXgtQf5gp0RvQmTKyAXzN-PcDju-wgH9FD6wWL66GHEobmkKGzeFMRYvFOK6WM1bTGGzHQm74jm5EPdXF7viL4b165SvdyHRxJ9Sh6lYTRnOHp7O2UnvBsKfn_OMvdzdPi__8Men-4fl9SP3qoKJoypdVRsBCLUWTndV771BXRvVmq5sTN5b1LqsfFN3rfFC9WUm0VTGyxbVGbs8-G7T-D4jTXYTyOMwuIjjTBYqUSutlRRZCgepTyNRwt5uczSXdhaE3RdqD4XaXKjdF2qbzFx82jvybuiTiz7QFygbIcEAZJ086Ci_4hqTfRvnFHPyb8z_A3IwhoY</recordid><startdate>20131201</startdate><enddate>20131201</enddate><creator>Dou, Gaoqi</creator><creator>Zhang, Xianfeng</creator><creator>He, Chunquan</creator><creator>Gao, Jun</creator><general>Springer US</general><general>Springer</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20131201</creationdate><title>Doubly-Selective Channel Estimation Using Superimposed Training and Weighted First-Order Statistics</title><author>Dou, Gaoqi ; Zhang, Xianfeng ; He, Chunquan ; Gao, Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c351t-e34a56901e1670a7d5fcc9e7693b9d4895fcbe7745c86db9c03f4351e959c2be3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Applied sciences</topic><topic>Channels</topic><topic>Communications Engineering</topic><topic>Computer Communication Networks</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. 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| ispartof | Wireless personal communications, 2013-12, Vol.73 (3), p.767-778 |
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| language | eng |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Applied sciences Channels Communications Engineering Computer Communication Networks Computer science control theory systems Computer systems and distributed systems. User interface Engineering Exact sciences and technology Networks Radiocommunications Signal,Image and Speech Processing Software Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) |
| title | Doubly-Selective Channel Estimation Using Superimposed Training and Weighted First-Order Statistics |
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