Energy Consumption vs. Bit Rate Analysis Toward Massive MIMO Systems

In this paper, we provide a comprehensive study and comparison of the impact of both multiple-input multiple-output (MIMO) and massive MIMO techniques, at the base station (BS), on the energy consumption versus bit rate performance of a multi-antenna wireless handset. Both spatial diversity and spatial multiplexing (SM) are examined and compared for both known and unknown channel state information (CSI) at the transmitter. For the diversity case, our results show that for a BS with four or more receive antennas, there is little to be gained in terms of energy efficiency at the wireless handset by having more than one transmit antenna. For the SMcase with conventional MIMO, the bit rate increases linearly with Nt at the cost of additional energy consumption at the handset due to the absence of diversity gain. For massive MIMO, however, the excess receive antennas provide a diversity gain in a SM scheme thus allowing a high bit rate without sacrificing energy efficiency at the handset and even with no needs of CSI knowledge.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  Emil Björnson,et al.  Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits , 2013, IEEE Transactions on Information Theory.

[3]  Hamid Jafarkhani,et al.  Space-Time Coding - Theory and Practice , 2010 .

[4]  Erik G. Larsson,et al.  Massive MIMO for next generation wireless systems , 2013, IEEE Communications Magazine.

[5]  Christian Oberli,et al.  Impact of the Channel State Information on the Energy-Efficiency of MIMO Communications , 2015, IEEE Transactions on Wireless Communications.

[6]  Min Chen,et al.  Energy-Efficiency Optimization for MIMO-OFDM Mobile Multimedia Communication Systems With QoS Constraints , 2014, IEEE Transactions on Vehicular Technology.

[7]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[8]  Erik G. Larsson,et al.  Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems , 2011, IEEE Transactions on Communications.

[9]  F. Hlawatsch,et al.  Detection techniques for MIMO spatial multiplexing systems , 2005 .

[10]  Nan Liu,et al.  Energy Efficiency Optimization for MIMO Distributed Antenna Systems , 2015, IEEE Transactions on Vehicular Technology.

[11]  Harald Haas,et al.  Index Modulation Techniques for Next-Generation Wireless Networks , 2017, IEEE Access.

[12]  Ernst Bonek,et al.  Capacity of different MIMO systems based on indoor measurements at 5.2 GHz , 2003 .

[13]  Lingjia Liu,et al.  Modeling and Analysis of Energy Consumption for RF Transceivers in Wireless Cellular Systems , 2014, GLOBECOM 2014.

[14]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[15]  Daniel Pérez Palomar,et al.  High-SNR Analytical Performance of Spatial Multiplexing MIMO Systems With CSI , 2007, IEEE Transactions on Signal Processing.

[16]  Sergio Verdú,et al.  Computational complexity of optimum multiuser detection , 1989, Algorithmica.

[17]  Thomas L. Marzetta,et al.  Massive MIMO: An Introduction , 2015, Bell Labs Technical Journal.

[18]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[19]  Jerry R. Hampton,et al.  Introduction to MIMO Communications , 2013 .

[20]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[21]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[22]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.