Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback
Multi-user wireless systems with multiple antennas can drastically increase the capac- ity while maintaining the quality of service requirements. The best performance of these systems is obtained at the presence of instantaneous channel knowledge. Since uplink-downlink channel reciprocity does not h...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OTU.1807-256322013-04-20T05:21:41ZQuantization Techniques in Linearly Precoded Multiuser MIMO System with Limited FeedbackIslam, MuhammadMIMO Broadcast ChannelLinear PrecodingChannel QuantizationBit Allocation0544Multi-user wireless systems with multiple antennas can drastically increase the capac- ity while maintaining the quality of service requirements. The best performance of these systems is obtained at the presence of instantaneous channel knowledge. Since uplink-downlink channel reciprocity does not hold in frequency division duplex and broadband time division duplex systems, efficient channel quantization becomes important. This thesis focuses on different quantization techniques in a linearly precoded multi-user wireless system. Our work provides three major contributions. First, we come up with an end-to-end transceiver design, incorporating precoder, receive combining and feedback policy, that works well at low feedback overhead. Second, we provide optimal bit allocation across the gain and shape of a complex vector to reduce the quantization error and investigate its effect in the multiuser wireless system. Third, we design an adaptive differential quantizer that reduces feedback overhead by utilizing temporal correlation of the channels in a time varying scenario.Adve, Raviraj2010-112011-01-01T15:23:33ZNO_RESTRICTION2011-01-01T15:23:33Z2011-01-01T15:23:33ZThesishttp://hdl.handle.net/1807/25632en_ca |
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en_ca |
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MIMO Broadcast Channel Linear Precoding Channel Quantization Bit Allocation 0544 |
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MIMO Broadcast Channel Linear Precoding Channel Quantization Bit Allocation 0544 Islam, Muhammad Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
description |
Multi-user wireless systems with multiple antennas can drastically increase the capac-
ity while maintaining the quality of service requirements. The best performance of these
systems is obtained at the presence of instantaneous channel knowledge. Since uplink-downlink channel reciprocity does not hold in frequency division duplex and broadband time division duplex systems, efficient channel quantization becomes important. This thesis focuses on different quantization techniques in a linearly precoded multi-user wireless system.
Our work provides three major contributions. First, we come up with an end-to-end transceiver design, incorporating precoder, receive combining and feedback policy, that
works well at low feedback overhead. Second, we provide optimal bit allocation across the
gain and shape of a complex vector to reduce the quantization error and investigate its
effect in the multiuser wireless system. Third, we design an adaptive differential quantizer that reduces feedback overhead by utilizing temporal correlation of the channels in a time varying scenario. |
author2 |
Adve, Raviraj |
author_facet |
Adve, Raviraj Islam, Muhammad |
author |
Islam, Muhammad |
author_sort |
Islam, Muhammad |
title |
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
title_short |
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
title_full |
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
title_fullStr |
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
title_full_unstemmed |
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback |
title_sort |
quantization techniques in linearly precoded multiuser mimo system with limited feedback |
publishDate |
2010 |
url |
http://hdl.handle.net/1807/25632 |
work_keys_str_mv |
AT islammuhammad quantizationtechniquesinlinearlyprecodedmultiusermimosystemwithlimitedfeedback |
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1716583462903742464 |