Code-aided joint channel and frequency offset estimation for DS-CDMA
This paper deals with joint data detection, synchronization and channel parameter estimation for direct-sequence code-division multiple-access systems over frequency-selective channels. In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacc...
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| Veröffentlicht in: | IEEE journal on selected areas in communications 2006-01, Vol.24 (1), p.181-189 |
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| container_title | IEEE journal on selected areas in communications |
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| creator | Guenach, M. Simoens, F. Wymeersch, H. Moeneclaey, M. |
| description | This paper deals with joint data detection, synchronization and channel parameter estimation for direct-sequence code-division multiple-access systems over frequency-selective channels. In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts. |
| doi_str_mv | 10.1109/JSAC.2005.858898 |
| format | Article |
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In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. 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In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Channels</subject><subject>Code-division multiple access (CDMA)</subject><subject>Computational complexity</subject><subject>Computer simulation</subject><subject>expectation maximization (EM) algorithm</subject><subject>Fading</subject><subject>Frequency estimation</subject><subject>Frequency synchronization</subject><subject>Iterative algorithms</subject><subject>iterative processing</subject><subject>Maximization</subject><subject>Maximum likelihood detection</subject><subject>Maximum likelihood estimation</subject><subject>maximum-likelihood (ML) estimation</subject><subject>Multiaccess communication</subject><subject>Offsets</subject><subject>Parameter estimation</subject><subject>Spectra</subject><subject>Synchronism</subject><subject>Synchronization</subject><issn>0733-8716</issn><issn>1558-0008</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kD1PwzAQQC0EEqWwI7FYDDCl2HHsXMYq5VNFDIXZSuyzSJXGJU6H_ntcBQmJgeXupHt3unuEXHI245wVdy-reTlLGZMzkAAFHJEJlxISxhgckwnLhUgg5-qUnIWwZoxnGaQTsii9xaRqLFq69k03UPNZdR22tOosdT1-7bAze-qdCzhQDEOzqYbGd9T5ni5WSbl4nZ-TE1e1AS9-8pR8PNy_l0_J8u3xuZwvEyOkGJI0L2qHmOVobWpqVstaMLR54WLMalHkqJSw4DjWJjV5LBGMzTC2jKmUmJLbce-29_GuMOhNEwy2bdWh3wUNheJFwQVE8uZfMp4CALmM4PUfcO13fRe_0KCkSmXKswixETK9D6FHp7d91NDvNWf6YF8f7OuDfT3ajyNX40iDiL-4VFkKmfgGs0WAJw</recordid><startdate>200601</startdate><enddate>200601</enddate><creator>Guenach, M.</creator><creator>Simoens, F.</creator><creator>Wymeersch, H.</creator><creator>Moeneclaey, M.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSAC.2005.858898</doi><tpages>9</tpages></addata></record> |
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| subjects | Algorithms Approximation Channels Code-division multiple access (CDMA) Computational complexity Computer simulation expectation maximization (EM) algorithm Fading Frequency estimation Frequency synchronization Iterative algorithms iterative processing Maximization Maximum likelihood detection Maximum likelihood estimation maximum-likelihood (ML) estimation Multiaccess communication Offsets Parameter estimation Spectra Synchronism Synchronization |
| title | Code-aided joint channel and frequency offset estimation for DS-CDMA |
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