Approximation of Capacity in MIMO Systems
https://doi.org/10.35596/1729-7648-2022-20-2-53-61
Abstract
This paper introduces functional approximations to the MIMO capacity over flat Rayleigh fading channels, which allow for analytical solutions to network resource optimization problems. This approximation allows to solve the problem of resource allocation optimization in radio networks and in other systems used to transfer information. The precision of the suggested approximations is assessed and is shown to provide a very close match to the exact capacity expression.
About the Author
V. P. Tuzlukov
Belarussian State Aviation Academy
Belarus
Belarus
Tuzlukov Vyacheslav Petrovich - Dr. of Sci., Professor, Head of the Department of Technical Maintenance of Aviation and Radio Electronic Equipment
220096, Minsk, Uborevich st., 77
References
1. Foschini G.J. and Gans M.J. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communications.1998;6(5):311-335.
2. Kai Liu, Cheng Tao, Liu Liu, Yinsheng Liu, Yongzhi Li, Yanping Lu. Analytical approximation for capacity in massive MIMO systems. Wireless Personal Communications. 2017; 97:4551-4561.
3. Yinsheng Liu, Yongzhi Li, Cheng Tao. Noise power estimation in SC-FDMA systems. IEEE Wireless Communications Letters. 2015;4(2):217-220.
4. Pand S., Shafi, M. An approximate capacity distribution for MIMO systems. IEEE Transactions on Communications. 2004;52(6):887-890.
5. Felipe de Figneiredo A.P., Dias C.F., Eduardo de Lima R., Fraidenraich G. Capacity bounds for dense massive MIMO in a line-of-sight propagation environment. Sensors. 2020;20:520. DOI: 10.3390/s20020520.
6. Dohler M., Gkelias A., Aghvami H. A resource allocation strategy for distributed MIMO multi-hop communication systems. IEEE Communications Letters. 2004;8(2):99-101.
7. Nafkha A., Bonnefoi R. Upper and lower bounds for the ergodic capacity of MIMO Jacobi fading channels. Optics Express. 2017;25(11):12145-12151.
8. Perez J., Ibanez J., Vielva L., Santamaria I. Closed-form approximation for the outage capacity of orthogonal STBC. IEEE Communications Letters. 2005; 9(11):961-963.
9. Ng S.X., Hanzo L. On the MIMO channel capacity of multi-dimensional signal sets. IEEE Transactions on Vehicular Technology. 2006;55(2):528-536.
10. Gershman A.B., Sidoropoulos N.D. Space-Time Processing for MIMO Communications. New York, USA: Wiley & Sons Inc; 2005.
11. Vucetic B., Yuan J. Space-Time Coding. New York, USA: Wiley & Sons Inc; 2003.
12. Communications Systems: New Research / Ed.: V.P. Tuzlukov. New York: NOVA Science Publishers, Inc. 2013.
13. Yankov M.P., Forchhammer S., Larsen K.J., Christensen L.P.B., Approximating the constellation constrained capacity of the MIMO channel with discrete input. In Proceedings of the IEEE International Conference on Communications. 2015. DOI: 10.1109/ICC.2015.7248952.
14. Tuzlukov V.P. Advances in Signal Processing. Chapter 2: Signal processing by generalized receiver in wireless communications systems over fading channels. Barcelona, Spain: IFSA Publishing Corp. 2021:55-111.
15. Hongyuan Zhang, Huaiyn Dai On the capacity of distributed MIMO systems. In Proceedings of the 2004 International Conference on Information Sciences and Systems. Princeton University, USA. 2004, March 17–19.
16. Lian Yang, Khalid Qarage, Erchin Serpedin, Mohamed-Slim Alouini. Capacity analysis of spectrum sharing spatial multiplexing MIMO systems. Physical Communications. 2014;Part C:109-119.
17. Gradshteyn I.S., Ryshik I.M. Table of Integrals, Series, and Products. 6th Ed. London, U.K.: Academia. 2000.
Review
For citations:
Tuzlukov V.P. Approximation of Capacity in MIMO Systems. Doklady BGUIR. 2022;20(2):53-61. (In Russ.) https://doi.org/10.35596/1729-7648-2022-20-2-53-61
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