Equal Gain Transmission with Antenna Selection in MIMO Communications

The beamforming vectors of an equal gain transmission (EGT) contains phase information only and thereby enjoys several implementational advantages when compared to the optimal scheme, i.e. maximum ratio transmission (MRT). The implementational advantages make EGT a promising solution for simple transceiver design while offering a performance comparable to that of MRT. This solution motivates us to explore how close the performance can be between EGT and MRT. The maximum SNR loss between EGT and MRT is known to be 1.05 dB in MISO channels. However, little is known about the SNR loss in MIMO channels, since no closed-form solution is available for the best EGT in MIMO channels. In this work, a suboptimal closed-form EGT design for MIMO channels is proposed and its performance is analyzed. Interestingly, the maximum SNR loss between the proposed EGT and the MRT (both employing MRC in receiver) in MIMO channels is shown to be approximately 1.05 dB as well. Moreover, instead of applying conventional all transmit antennas, this study proposes to adopt antenna selection, to further improve the performance of EGT. Two antenna selection algorithms are proposed and the corresponding performance is analyzed. When the proposed antenna selection algorithms are applied to EGT, the SNR loss between EGT and MRT can be reduced to as low as 0.45-0.65 dB, with the numbers of transmit antennas ranging from 4 to 8. One of the proposals with fixed number of transmit antennas not only outperforms conventional EGT but also requires fewer number of RF (radio frequency) components; also, it employs constant power in each transmit antenna like EGT does. As a result, hardware complexity can be reduced by this proposal. Furthermore, design strategies to apply the proposed EGT and antenna selection algorithms in systems with limited feedback are also suggested.

[1]  I. Miller Probability, Random Variables, and Stochastic Processes , 1966 .

[2]  D. G. Brennan Linear Diversity Combining Techniques , 1959, Proceedings of the IRE.

[3]  A.F. Molisch,et al.  MIMO systems with antenna selection , 2004, IEEE Microwave Magazine.

[4]  Robert W. Heath,et al.  Antenna selection for spatial multiplexing systems with linear receivers , 2001, IEEE Communications Letters.

[5]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[6]  Jørgen Bach Andersen,et al.  Array gain and capacity for known random channels with multiple element arrays at both ends , 2000, IEEE Journal on Selected Areas in Communications.

[7]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[8]  Laurence B. Milstein,et al.  Average SNR of a generalized diversity selection combining scheme , 1999, IEEE Communications Letters.

[9]  M. V. Wilkes,et al.  The Art of Computer Programming, Volume 3, Sorting and Searching , 1974 .

[10]  H. N. Nagaraja,et al.  Order Statistics, Third Edition , 2005, Wiley Series in Probability and Statistics.

[11]  Arogyaswami Paulraj,et al.  Selecting an optimal set of transmit antennas for a low rank matrix channel , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[12]  Moe Z. Win,et al.  Analysis of hybrid selection/maximal-ratio combining in Rayleigh fading , 1999, IEEE Trans. Commun..

[13]  Vijay K. Bhargava,et al.  Equal-gain diversity receiver performance in wireless channels , 2000, IEEE Trans. Commun..

[14]  Robert W. Heath,et al.  Equal gain transmission in multiple-input multiple-output wireless systems , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[15]  T. W. Anderson An Introduction to Multivariate Statistical Analysis, 2nd Edition. , 1985 .

[16]  Arogyaswami Paulraj,et al.  Receive antenna selection for MIMO spatial multiplexing: theory and algorithms , 2003, IEEE Trans. Signal Process..

[17]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[18]  Shang-Ho Tsai,et al.  Transmit Equal Gain Precoding in Rayleigh Fading Channels , 2009, IEEE Transactions on Signal Processing.

[19]  Donald E. Knuth,et al.  The Art of Computer Programming: Volume 3: Sorting and Searching , 1998 .

[20]  Jian Li,et al.  MIMO Transmit Beamforming Under Uniform Elemental Power Constraint , 2007, IEEE Transactions on Signal Processing.

[21]  Bhaskar D. Rao,et al.  Quantization Methods for Equal Gain Transmission With Finite Rate Feedback , 2007, IEEE Transactions on Signal Processing.

[22]  Norman C. Beaulieu,et al.  An infinite series for the computation of the complementary probability distribution function of a sum of independent random variables and its application to the sum of Rayleigh random variables , 1990, IEEE Trans. Commun..