Interference Cancellation Based Detection for V-BLAST With Diversity Maximizing Channel Partition
Multiple-input multiple-output (MIMO) systems achieve very high bandwidth efficiencies through spatial multiplexing. However, the complexity of optimal detection in such systems motivates the need for more practical alternatives. Recently, a suboptimal lower complexity detection scheme called ¿gener...
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| Published in: | IEEE journal of selected topics in signal processing Vol. 3; no. 6; pp. 1000 - 1015 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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New York
IEEE
01.12.2009
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1932-4553, 1941-0484 |
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| Abstract | Multiple-input multiple-output (MIMO) systems achieve very high bandwidth efficiencies through spatial multiplexing. However, the complexity of optimal detection in such systems motivates the need for more practical alternatives. Recently, a suboptimal lower complexity detection scheme called ¿generalized parallel interference cancellation¿ (GPIC), with close to optimal performance, was introduced. The reported performance of GPIC, however, was assessed by computer simulations only. In this paper, we show that with its original design, GPIC does not always provide close to optimal performance. Based on a diversity analysis of GPIC like techniques, we propose two new improved algorithms, referred to as Sel-MMSE and Sel-MMSE-OSIC, and derive sufficient conditions for achieving optimal performance asymptotically. We also provide a complexity analysis of these two schemes, and show that for large constellation sizes it is lower than the original GPIC. While still more complex than the fixed complexity sphere decoder by a factor in the range of 2-3 (for most configurations), our algorithms are also applicable to undetermined MIMO systems. Simulations results confirm that the new schemes provide maximal diversity gains. Furthermore, Sel-MMSE-OSIC provides a significant gain over Sel-MMSE, making its performance nearly indistinguishable from optimal for all signal-to-noise ratio (SNR) levels. |
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| AbstractList | Multiple-input multiple-output (MIMO) systems achieve very high bandwidth efficiencies through spatial multiplexing. However, the complexity of optimal detection in such systems motivates the need for more practical alternatives. Recently, a suboptimal lower complexity detection scheme called "Generalized Parallel Interference Cancellation" (GPIC), with close to optimal performance, was introduced. The reported performance of GPIC, however, was assessed by computer simulations only. In this paper, we show that with its original design, GPIC does not always provide close to optimal performance. Based on a diversity analysis of GPIC like techniques, we propose two new improved algorithms, referred to as Sel-MMSE and Sel-MMSE-OSIC, and derive sufficient conditions for achieving optimal performance asymptotically. We also provide a complexity analysis of these two schemes, and show that for large constellation sizes it is lower than the original GPIC. While still more complex than the fixed complexity sphere decoder by a factor in the range of 2-3 (for most configurations), our algorithms are also applicable to undetermined MIMO systems. Simulations results confirm that the new schemes provide maximal diversity gains. Furthermore, Sel-MMSE-OSIC provides a significant gain over Sel-MMSE, making its performance nearly indistinguishable from optimal for all signal-to-noise ratio (SNR) levels. Multiple-input multiple-output (MIMO) systems achieve very high bandwidth efficiencies through spatial multiplexing. However, the complexity of optimal detection in such systems motivates the need for more practical alternatives. Recently, a suboptimal lower complexity detection scheme called ¿generalized parallel interference cancellation¿ (GPIC), with close to optimal performance, was introduced. The reported performance of GPIC, however, was assessed by computer simulations only. In this paper, we show that with its original design, GPIC does not always provide close to optimal performance. Based on a diversity analysis of GPIC like techniques, we propose two new improved algorithms, referred to as Sel-MMSE and Sel-MMSE-OSIC, and derive sufficient conditions for achieving optimal performance asymptotically. We also provide a complexity analysis of these two schemes, and show that for large constellation sizes it is lower than the original GPIC. While still more complex than the fixed complexity sphere decoder by a factor in the range of 2-3 (for most configurations), our algorithms are also applicable to undetermined MIMO systems. Simulations results confirm that the new schemes provide maximal diversity gains. Furthermore, Sel-MMSE-OSIC provides a significant gain over Sel-MMSE, making its performance nearly indistinguishable from optimal for all signal-to-noise ratio (SNR) levels. |
| Author | Radji, D. Leib, H. |
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| SubjectTerms | Algorithm design and analysis Algorithms Asymptotic properties Bandwidth Cancellation Channels Codes Complexity Computer simulation Decoding Diversity methods Gain Interference Interference cancellation Interference cancellation detection MIMO minimum mean-squared error (MMSE) detection multiple-input multiple-output (MIMO) detection Optimization Performance analysis Performance gain selection diversity Sufficient conditions |
| Title | Interference Cancellation Based Detection for V-BLAST With Diversity Maximizing Channel Partition |
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