Pilot decontamination through pilot sequence hopping in massive MIMO systems

This work concerns wireless cellular networks applying massive multiple-input multiple-output (MIMO) technology. In such a system, the base station in a given cell is equipped with a very large number (hundreds or even thousands) of antennas and serves multiple users. Estimation of the channel from the base station to each user is performed at the base station using an uplink pilot sequence. Such a channel estimation procedure suffers from pilot contamination. Orthogonal pilot sequences are used in a given cell but, due to the shortage of orthogonal sequences, the same pilot sequences must be reused in neighboring cells, causing pilot contamination. The solution presented in this paper suppresses pilot contamination, without the need for coordination among cells. Pilot sequence hopping is performed at each transmission slot, which provides a randomization of the pilot contamination. Using a modified Kaiman filter, it is shown that such randomized contamination can be significantly suppressed. Comparisons with conventional estimation methods show that the mean squared error can be lowered as much as an order of magnitude at low mobility.

[1]  Erik G. Larsson,et al.  Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays , 2012, IEEE Signal Process. Mag..

[2]  Ralf R. Müller,et al.  Blind Pilot Decontamination , 2013, IEEE Journal of Selected Topics in Signal Processing.

[3]  David Gesbert,et al.  A Coordinated Approach to Channel Estimation in Large-Scale Multiple-Antenna Systems , 2012, IEEE Journal on Selected Areas in Communications.

[4]  David James Love,et al.  Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training With Memory , 2013, IEEE Journal of Selected Topics in Signal Processing.

[5]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[6]  Tim Brown,et al.  Practical guide to the MIMO radio channel with MATLAB examples , 2012 .

[7]  T.L. Marzetta,et al.  How Much Training is Required for Multiuser Mimo? , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[8]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[9]  Thomas L. Marzetta,et al.  Pilot contamination precoding in multi-cell large scale antenna systems , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[10]  Sang-Wook Lee,et al.  Channel estimation for OFDM with fast fading channels by modified Kalman filter , 2004, IEEE Trans. Consumer Electron..

[11]  Thomas L. Marzetta,et al.  Pilot Contamination and Precoding in Multi-Cell TDD Systems , 2009, IEEE Transactions on Wireless Communications.

[12]  Erik G. Larsson,et al.  EVD-based channel estimation in multicell multiuser MIMO systems with very large antenna arrays , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[13]  Kien T. Truong,et al.  Effects of channel aging in massive MIMO systems , 2013, Journal of Communications and Networks.

[14]  S.M. Kay,et al.  Spectrum analysis—A modern perspective , 1981, Proceedings of the IEEE.

[15]  Iain B. Collings,et al.  Analysis of adaptive least squares filtering in massive MIMO , 2014, 2014 Australian Communications Theory Workshop (AusCTW).

[16]  Michael D. Zoltowski,et al.  Optimal pilot beam pattern design for massive MIMO systems , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

[17]  Ralf R. Müller,et al.  Analysis of Pilot Decontamination Based on Power Control , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[18]  Ralf R. Müller,et al.  Analysis of blind pilot decontamination , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.