Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems
Interference alignment (IA) is a promising technique that allows high-capacity gains in interference channels, but which requires the knowledge of the channel state information (CSI) for all the system links. We design low-complexity and low-bit rate feedback strategies where a quantized version of...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/619454 |
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| author | Sara Teodoro Adão Silva Rui Dinis Atílio Gameiro |
| author_facet | Sara Teodoro Adão Silva Rui Dinis Atílio Gameiro |
| author_sort | Sara Teodoro |
| collection | DOAJ |
| description | Interference alignment (IA) is a promising technique that allows high-capacity gains in interference channels, but which requires the knowledge of the channel state information (CSI) for all the system links. We design low-complexity and low-bit rate feedback strategies where a quantized version of some CSI parameters is fed back from the user terminal (UT) to the base station (BS), which shares it with the other BSs through a limited-capacity backhaul network. This information is then used by BSs to perform the overall IA design. With the proposed strategies, we only need to send part of the CSI information, and this can even be sent only once for a set of data blocks transmitted over time-varying channels. These strategies are applied to iterative MMSE-based IA techniques for the downlink of broadband wireless OFDM systems with limited feedback. A new robust iterative IA technique, where channel quantization errors are taken into account in IA design, is also proposed and evaluated. With our proposed strategies, we need a small number of quantization bits to transmit and share the CSI, when comparing with the techniques used in previous works, while allowing performance close to the one obtained with perfect channel knowledge. |
| format | Article |
| id | doaj-art-9c181cafc672469a879614703fd41fa5 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-9c181cafc672469a879614703fd41fa52025-02-03T06:12:14ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/619454619454Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based SystemsSara Teodoro0Adão Silva1Rui Dinis2Atílio Gameiro3DETI, Instituto de Telecomunicações, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, PortugalDETI, Instituto de Telecomunicações, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, PortugalInstituto de Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, PortugalDETI, Instituto de Telecomunicações, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, PortugalInterference alignment (IA) is a promising technique that allows high-capacity gains in interference channels, but which requires the knowledge of the channel state information (CSI) for all the system links. We design low-complexity and low-bit rate feedback strategies where a quantized version of some CSI parameters is fed back from the user terminal (UT) to the base station (BS), which shares it with the other BSs through a limited-capacity backhaul network. This information is then used by BSs to perform the overall IA design. With the proposed strategies, we only need to send part of the CSI information, and this can even be sent only once for a set of data blocks transmitted over time-varying channels. These strategies are applied to iterative MMSE-based IA techniques for the downlink of broadband wireless OFDM systems with limited feedback. A new robust iterative IA technique, where channel quantization errors are taken into account in IA design, is also proposed and evaluated. With our proposed strategies, we need a small number of quantization bits to transmit and share the CSI, when comparing with the techniques used in previous works, while allowing performance close to the one obtained with perfect channel knowledge.http://dx.doi.org/10.1155/2014/619454 |
| spellingShingle | Sara Teodoro Adão Silva Rui Dinis Atílio Gameiro Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems The Scientific World Journal |
| title | Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems |
| title_full | Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems |
| title_fullStr | Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems |
| title_full_unstemmed | Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems |
| title_short | Low-Bit Rate Feedback Strategies for Iterative IA-Precoded MIMO-OFDM-Based Systems |
| title_sort | low bit rate feedback strategies for iterative ia precoded mimo ofdm based systems |
| url | http://dx.doi.org/10.1155/2014/619454 |
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