Preview

Journal of the Russian Universities. Radioelectronics

Advanced search

Spectral Efficiency of Wireless Relay Network in Frequency Non-Selective Channel

https://doi.org/10.32603/1993-8985-2020-23-4-25-37

Abstract

Introduction. A wireless communication system based on a relay network where a link between a source and a destination is carried out through a network of relay nodes have been considered. Relay networks operate according with amplifier-and-forward protocol where each relay node performs reception, amplifying, phase shifting and retranslation of a signal to the destination node. As a result a task of powers and phases optimization in the relay nodes (i.e. the complex weighted coefficients optimization) becomes actual. Complex weighted coefficients of the relay nodes are optimized in such a way as to ensure the maximum signal to noise ratio at the receiver while limiting a power emitted by the relay nodes. In the paper, optimization of spatial processing with different a priori channel state information (i.e. instantaneous channel state information and the second order statistics) have been considered.

Aim. Spectral efficiency analysis of a relay network in a multipath channel where the relay network was optimized by using of two types a priori information: an instantaneous channel state information and second order statistics.

Materials and methods. Optimization of spatial signal processing in the relay network was based on methods of statistical theory and optimization using analytics of linear algebra and methods of mathematical programming. Performances of the relay network were analyzed using Monte Carlo simulation. The simulation was performed in MATLAB program environment using CVX toolbox for solving convex optimization task.

Results. In the paper optimal solutions for spatial signal processing in the relay network were presented. The solutions were based on maximum of signal to noise ratio while limiting total relay power and individual power of relay nodes. Monte Carlo simulation was performed to provide performances of the relay network for different types of channel state information and channel parameters. Mean capacities versus mean source power, a budget of relay nodes power and a ratio between random and deterministic power of the channel were gained for the Rayleigh model of multipath channel.

Conclusions. The results have a practical application. Thus, the use of the second order statistics is possible in relay networks when direct visibility with a low level of background from local objects is provided. In urban areas, where shading and multipath propagation of signals occur, it is possible to use only an approach based on the knowledge of channel instantaneous state.

About the Authors

E. A. Mavrychev
Nizhny Novgorod State Technical University n. a. R. E. Alekseev
Russian Federation
Evgeny A. Mavrychev, Cand. Sci. (Eng.) (2003), Associate Professor (2012) on the Department of Information Radio Systems, 24, Minin St., Nizhny Novgorod 603950, Russia


E. N. Pribludova
Nizhny Novgorod State Technical University n. a. R. E. Alekseev
Russian Federation
Elena N. Pribludova, Cand. Sci. (Eng.) (2000), Associate Professor (2002) on the Department of Information Radio Systems, 24, Minin St., Nizhny Novgorod 603950, Russia


S. B. Sidorov
Nizhny Novgorod State Technical University n. a. R. E. Alekseev
Russian Federation
Sergey B. Sidorov, Cand. Sci. (Eng.) (2000), Associate Professor (2002) on the Department of Information Radio Systems, 24, Minin St., Nizhny Novgorod 603950, Russia


References

1. Telatar I. E. Capacity of Multi-Antenna Gaussian Channels. Eur. Trans. Telecommun. 1999, vol. 10, no. 6, pp. 585–595. doi: 10.1002/ett.4460100604

2. Foschini G. J., Gans M. J. On Limits of Wireless Communications in a Fading Environment when using Multiple Antennas. Wireless Personal Communications. 1998, vol. 6, no. 3, pp. 311–335. doi: 10.1023/A:1008889222784

3. Gupta P., Kumar P. R. The Capacity of Wireless Networks. IEEE Trans. on Inform. Theory. 2002, vol. 46, no. 2, pp. 388–404. doi: 10.1109/18.825799

4. Goldsmith A., Jafar S. A., Jindal N., Vishwanath S. Capacity Limits of MIMO Channels. IEEE J. on Selected Areas in Commun. 2003, vol. 21, no. 5, pp. 684–702. doi: 10.1109/JSAC.2003.810294

5. Sendonaris A., Erkip E., Aazhang B. User Cooperation Diversity. Pt. I. System description. IEEE Trans. on Commun. 2003, vol. 51, no. 11, pp. 1927–1938. doi: 10.1109/TCOMM.2003.818096

6. Sendonaris A., Erkip E., Aazhang B. User Cooperation Diversity. Pt. II. Implementation Aspects and Perfromance Analysis. IEEE Trans. on Commun. 2003, vol. 51, no. 11, pp. 1939–1948. doi: 10.1109/TCOMM.2003.819238

7. Laneman J., Tse D., Wornell G. Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior. IEEE Trans. on Inform. Theory. 2004, vol. 50, no. 12, pp. 3062–3080. doi: 10.1109/TIT.2004.838089

8. Kramer G., Gastpar M., Gupta P. Cooperative Strategies and Capacity Theorems for Relay Networks. IEEE Trans. on Inform. Theory. 2005, vol. 51, no. 9, pp. 3037–3063. doi: 10.1109/TIT.2005.853304

9. Bolcskei H., Nabar R. U., Oyman O., Paulraj A. J. Capacity Scaling Laws in MIMO Relay Networks. IEEE Trans. on Wireless Commun. 2006, vol. 5, no. 6, pp. 1433–1444. doi: 10.1109/TWC.2006.1638664

10. Gastpar M., Vetterli M. On the Capacity of Wireless Networks: The Relay Case. Proc. 21st Annual Joint Conf. of the IEEE Computer and Communications Societies. New York, USA, 23–27 June 2002, vol. 3, pp. 1577–1586. doi: 10.1109/INFCOM.2002.1019409

11. Havary-Nassab V., Shahbazpanahi S., Grami A., Luo Z.-Q. Distributed Beamforming for Relay Networks based on Second-Order Statistics of the Channel State Information. IEEE Trans. on Signal Processing. 2008, vol. 56, no. 9, pp. 4306–4316. doi: 10.1109/TSP.2008.925945

12. Danilov A. A., Mavrychev E. A. Efficiency of optimization of spatial signal processing in relay networks with a priori channel information. Rep. of the V all-Rus. Сonf. "Radar and communications", Moscow, 21-25 Nov. 2011, pp. 421-426. (In Russ.)

13. Janani M., Hedayat A., Hunter T. E., Nosratinia A. Coded Cooperation in Wireless Communications: Space–Time Transmission and Iterative Decoding. IEEE Trans. on Signal Process. 2004, vol. 52, no. 2, pp. 362–371. doi: 10.1109/TSP.2003.821100

14. Laneman J. N., Wornell G. W. Distributed space-time coded protocols for exploiting cooperative diversity in wireless network. IEEE Trans. on Inform. Theory, Oct. 2003, vol. 49, pp. 2415–242. doi: 10.1109/GLO-COM.2002.1188045

15. Jing Y., Hassibi B. Distributed space-time coding in wireless relay networks. IEEE Trans. Wireless Commun. 2006, vol. 5, no. 12, pp. 3524–3536. doi: 10.1109/TWC.2006.256975

16. Jing Y., Jafarkhani H. Using Orthogonal and Quasi-Orthogonal Designs in Wireless Relay Networks. IEEE Trans. on Inform. Theory. 2007, vol. 53, no. 11, pp. 4106–4118. doi: 10.1109/TIT.2007.907516

17. Chen H., Gershman A. B., Shahbazpanahi S. Filter-and-Forward Distributed Beamforming in Relay Networks With Frequency Selective Fading. IEEE Trans. on Signal Process. 2010, vol. 58, no. 3, pp. 1251–1262. doi: 10.1109/TSP.2009.2035986

18. Zhang W., Mitra U., Chiang M. Optimization of Amplify-and-Forward Multicarrier Two-Hop Transmission. IEEE Trans. on Commun. 2011, vol. 59, no. 5, pp. 1434–1445. doi: 10.1109/TCOMM.2011.022811.100017

19. Nabar R. U., Bolcskei H., Kneubuhler F. W. Fading relay channels: Performance limits and space-time signal design. IEEE J. on Selected Areas in Commun. 2004, vol. 22, no. 6, pp. 1099–1109. doi: 10.1109/JSAC.2004.830922

20. Jing Y., Jafarkhani H. Network Beamforming Using Relays with Perfect Channel Information. IEEE Trans. on Inform. Theory. 2009, vol. 55, no. 6, pp. 2499–2517. doi: 10.1109/TIT.2009.2018175

21. Scaglione A., Pagliari R., Krim H. The Decentralized Estimation of the Sample Covariance. 42nd Asilomar Conf. on Signals, Systems and Computers, Pacific Groove, CA. Pacific Grove, USA, 26–29 Oct. 2008, pp. 1722–1726. doi: 10.1109/ACSSC.2008.5074720

22. Boyd S., Vandenberghe L. Convex Optimization. Cambridge, Cambridge Univ. Press, 2004. 722 p. doi: 10.1017/CBO9780511804441

23. Voevodin V. V. Linejnaya algebra [Linear algebra]. Textbook. 4th ed. Saint Peterburg. Izd-vo LAN’, 2008, 416 p.

24. Mattingley J., Boyd S. Real-Time Convex Optimization in Signal Processing. IEEE Signal Processing Magazine. 2010, vol. 27, no. 3, pp. 50–61. doi: 10.1109/MSP.2010.936020

25. Luo Z.-Q., Ma W.-K., So A. M.-C., Ye Y., Zhang S. Semidefinite Relaxation of Quadratic Optimization Problems. IEEE Signal Processing Magazine. 2010, vol. 27, no. 3, pp. 20–34. doi: 10.1109/MSP.2010.936019

26. CVX Research. CVX: Matlab Software for Disciplined Convex Programming. Ver. 2.2. Available at: http://cvxr.com/cvx/ (accessed 22.06.2020)


Review

For citations:


Mavrychev E.A., Pribludova E.N., Sidorov S.B. Spectral Efficiency of Wireless Relay Network in Frequency Non-Selective Channel. Journal of the Russian Universities. Radioelectronics. 2020;23(4):25-37. (In Russ.) https://doi.org/10.32603/1993-8985-2020-23-4-25-37

Views: 660


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1993-8985 (Print)
ISSN 2658-4794 (Online)