Nagaraja, Srinidhi and Dabeer, Onkar and Chockalingam, A (2013) Large-MIMO Receiver based on Linear Regression of MMSE Residual. In: 2013 IEEE 78TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL) .
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Abstract
Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.
| Item Type: | Journal Article |
|---|---|
| Publication: | 2013 IEEE 78TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL) |
| Series.: | IEEE Vehicular Technology Conference Proceedings |
| Publisher: | IEEE |
| Additional Information: | Copyright of this article is belongs to IEEE |
| Keywords: | Large-MIMO receiver; linear regression; MMSE residual; receiver-based training |
| Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
| Date Deposited: | 17 Mar 2014 11:20 |
| Last Modified: | 19 Mar 2014 05:40 |
| URI: | http://eprints.iisc.ac.in/id/eprint/48575 |
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