Reference : Joint Compression and Feedback of CSI in Correlated multiuser MISO Channels
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/27684
Joint Compression and Feedback of CSI in Correlated multiuser MISO Channels
English
Alodeh, Maha mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Jul-2016
The 17th IEEE International workshop on Signal Processing advances in Wireless Communications
Yes
No
International
The 17th IEEE International workshop on Signal Processing advances in Wireless Communications
July 2016
IEEE
Edinbrugh
UK
[en] The potential gains of multiple antennas in wireless systems can be limited by the channel state information imperfections. In this context, this paper tackles the feedback in multiuser correlated multiple input single output (MU-MISO). We propose a framework to feedback the minimum number of bits without performance degradation. This framework is based on decorrelating the channel state information by compression and then quantize the compressed (CSI) and feedback it to the base station (BS). We characterize the rate loss resulted from the proposed framework. An upper bound on the rate loss is derived in terms of the amount of feedback and the statistics of the channel. Based on this characterization, we propose am adaptive bit allocation algorithm that takes into the account the channel statistics to reduce the rate loss induced by the quantization. Moreover, in order to maintain a constant rate loss with respect to the perfect CSIT case, it is shown that the number of feedback bits should scale linearly with the SNR (in dB) and to the rank of the user transmit correlation matrix. We validate the proposed framework by Monte-carlo simulations.
Researchers ; Professionals
http://hdl.handle.net/10993/27684

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