Zhurnal Radioelektroniki - Journal of Radio Electronics. ISSN 1689-1719. 2020. No. 2

Full text in Russian (pdf)
Russian page


DOI  10.30898/1684-1719.2020.2.1

UDC 621.391.1


Efficiency of threshold method for optimizing bit error Rate and throughput in MIMO system WITH feedback


A. V. Elokhin, I. S. Sorokin, A. G. Flaksman

Nizhny Novgorod Lobachevsky State University, 603950, Nizhny Novgorod, prosp. Gagarina, 23

The paper is received on December 24, 2019, after correction - on January 30, 2020

Abstract. The main problem in the field of mobile (cellular) communication systems is an increase in the data transmission rate and decrease in the bit error rate. The use of MIMO-systems (Multiple-Input Multiple-Output) with transmitting and receiving antenna arrays and various methods of spatial signal processing is a more promising way to solve this problem. The bit error rate depends on the mean square error between the input and output signals, which, in turn, is determined by the signal to noise ratio. If the channel state information (channel matrix) is used on the transmitting side of MIMO system, then the system can be represented as a set of independent parallel eigen subchannels. The number of subchannels is equal to the rank of the channel matrix, and their gains are determined by the singular numbers of the channel matrix. In a multipath Rayleigh channel (the so-called “urban” channel type), these subchannels can provide significantly different bit error rate. Two methods of transmitting information in a MIMO-system are of interest. The first one is based on the use of all subchannels and the optimal distribution of transmitter power between them. The second (“threshold”) method is based on transmitting data only on “strong” subchannels with the highest SNR and optimal power distribution among the remaining subchannels. In present work we performed a comparative analysis of the bit error rate and the throughput provided by these methods. Signal fading in a multipath channel is assumed to be Rayleigh uncorrelated in different antennas (“urban” channel type).

Key words: MIMO-system, feedback, eigen subchannel, bit error rate, throughput, Rayleigh signal fading.


1.     Björnson E., Hoydis J., Sanguinetti L. Massive MIMO Networks: Spectral, Energy and Hardware Efficiency. Foundations and Trends in Signal Processing. 2017. Vol. 11, No. 3-4. P. 154–655. DOI: 10.1561/2000000093.

2.     Palomar D., Jiang Y. MIMO transceiver design via majorization theory. Foundations and Trends in Communications and Information Theory. 2006. Vol. 3. No. 4–5. P. 331–551.

3.     Paylraj A., Nabar R. and Gore D. Introduction to space-time wireless communications. Cambridge University Press, 2003.  278 p.

4.     Jankiraman M. Space-time codes and MIMO systems. Artech House, Inc., 2004.  328 p.

5.     Gershman A.B., Sidoropoulos N.D., editors. Space-Time Processing for MIMO Communications. Wiley&Sons, 2005. 370 p.

6.     Ermolaev V.T., Flaksman A.G. Teoreticheskiye osnovy obrabotki signalov v besprovodnykh sistemakh svyazi. [Theoretical Foundations of Signal Processing in Wireless Communication Systems]. Nizhny Novgorod, Nizhni Novgorod University Press. 2011. 368 p. (In Russian)

7.     Palomar D.P., Cioffi J.M., Lagunas M.A. Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. IEEE Trans. Signal Process. 2003. Vol. 51. No. 9, P. 2381–2401.

8.     Palomar D.P., Lagunas M.A., Cioffi J.M. Optimum Linear Joint Transmit-Receive Processing for MIMO Channels with QoS Constraints. IEEE Trans. Signal Process. 2004. Vol. 52. No. 5, P. 1179–1197.

9.     Scaglione A., Stoica P., Barbarossa S., Giannakis G.B., Sampath H. Optimal designs for space-time linear precoders and decoders. IEEE Trans. Signal Process. 2002. Vol. 50. P. 1051–1064.

10.   ErmolayevV.T., Mavrychev E.A., Flaksman A.G. Reduction of Bit Error Probability during Parallel Transmission of Information in a MIMO System. Radiophysics and Quantum Electronics. 2003. Vol.46. No.3. P.224–232.

11.   Voevodin V.V. Lineynaya algebra. [Linear Algebra]. Moscow. Nauka Publ. 1980. 400 p. (In Russian)

12.   Gantmacher F.R. Teoriya matrits. [Matrix Theory]. Moscow. Nauka Publ. 1988. 552 p. (In Russian)

13.   Ermolayev V.T., Flaksman A.G., Averin I.M. Bit Error Rate in Eigenchannels of SVD-based MIMO System. Signal Process. 2013. Vol. 93. No. 12. P. 33193326.

14.   Ermolaev V.T., Flaksman A.G. Lysyakov D.N. Throughput increase in a MIMO system with eigen subchannels. Nizhni Novgorod, Vestnik NNGU im. N.I. Lobachevskogo – Bulletin of Lobachevsky State University of Nizhni Novgorod. 2010. Vol.3. No.1. P.79–86. (In Russian)

15.   Telatar I.E. Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications. 1999. Vol. 10. No. 6. P. 585–595.

16.   Tulino A.M., Verdú S. Random Matrix Theory and Wireless Communications. now Publishers Inc, USA. 2004.  182 p.  Full text available at: http://dx.doi.org/10.1561/0100000001


For citation:

Elokhin A.V., Sorokin I.S., A.G. Flaksman A.G. Efficiency of threshold method for optimizing bit error Rate and throughput in MIMO system WITH feedback. Zhurnal Radioelektroniki – Journal of Radio Electronics. 2020. No. 2. Available at http://jre.cplire.ru/jre/feb20/1/text.pdf
DOI  10.30898/1684-1719.2020.2.1