MIMO Spectral Efficiency over Energy Consumption Requirements: Application to WSNs


This paper presents the evaluation of the “capacity to the total energy consumption per bit ratio” of multiple antennas systems with distributed fashion. We propose an adequate geometric channel modeling for the wireless communication system which operates in indoor propagation environment with scatterers. The channel model is derived in function of both the line of sight (LOS) and the non line of sight (NLOS) components. The aim of this paper is to study the limits in the gain concerning the capacity to the total energy consumption ratio when additional antennas are implemented in the communication system. To do so, we have evaluated by simulations both the capacity and the total energy consumption per bit. Then, we have determined the capacity to the total energy consumption ratio. Finally, the computational capacity to the total energy ratio is obtained for different system configurations. We have shown that the gain in capacity increases with the number of antennas but it stills be limited by the total energy consumption. The limits for increasing the number of transmit antennas are determined in function of the separation distances between the transmitter and the receiver sides of the communication system. Optimal power allocation strategy via water-filling algorithm has been carried out for evaluating the capacity to energy ratio. We find by simulation that optimal power allocation brings a gain in the addressed metric reaching a level of about 1.7 at transmit signal to noise ratio of 8 dB if comparing to the case when transmit energy is equally split among transmit antennas.

Share and Cite:

M. Zid, K. Raoof and A. Bouallègue, "MIMO Spectral Efficiency over Energy Consumption Requirements: Application to WSNs," International Journal of Communications, Network and System Sciences, Vol. 5 No. 2, 2012, pp. 121-129. doi: 10.4236/ijcns.2012.52016.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] K. Raoof, M. Ben Zid, N. Prayongpun and A. Bouallègue, “Advanced MIMO Techniques: Polarization Diversity and Antenna Selection,” 2011. http://www.intechopen.com
[2] K. Raoof and H. Zhou, “Advanced MIMO Systems,” Scientific Research Publishing, USA, 2009.
[3] M. Ben Zid, K. Raoof and A. Bouallègue, “MIMO Systems and Cooperative Networks Performances,” In: K. Raoof, et al., Cognitive Radio, Scientific Research Publishing, USA, 2011, pp. 113-140.
[4] E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith and A. Paulraj, “MIMO Wireless Communications,” Cambridge University Press, Cambridge, 2007.
[5] B. Lang, T. Han and X. Gu, “A Robust Non-Coherent Sequential Code Acquisition Scheme for DS/SS Communications,” Proceedings of the 9th International Conference on Signal Processing (ICSP’08), Beijing, 26-29 October 2008, pp. 1939-1942.
[6] G. S. Hosangadi and C. W. Baum, “Hybrid Sequential Acquisition Schemes for Noncoherent Chip-Asynchro- nous DS/SS Systems,” Proceedings of the IEEE International Conference on Communications (ICC’98), Atlanta, 7-11 June 1998, pp. 1242-1247.
[7] M. Ben Zid, K. Raoof and A. Bouallègue, “A Novel Metric for Measuring Multiple Antennas System Capacity over Energy Consumption Requirements,” Proceedings of the 7th International Conference Wireless Communications, Networking and Mobile Computing (WiCOM), Wuhan, 23-25 September 2011, pp. 1-4.
[8] M. A. Khalighi, J.-M.Brossier, G. V. Jourdain and K. Raoof, “Waterfilling Capacity of Rayleigh MIMO Channels,” Proceedings of the 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, San Diego, 30 September-3 October 2001, pp. 155-158.
[9] S. Cui, A. J. Goldsmith and A. Bahai, “Energy-Efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks,” IEEE Journal on Selected Areas in Communications, Vol. 22, No. 6, 2004, pp. 1089-1098. doi:10.1109/JSAC.2004.830916.
[10] S. Cui, A. J. Goldsmith, and A. Bahai, “Energy-constrained modulation optimization,” IEEE Transactions on Communications, Vol. 4, No. 5, 2005, pp. 2349-2360.
[11] K. Kaemarungsi and P. Krishnamurthy, “Modeling of Indoor Positioning Systems Based on Location Finger-printing,” Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, Hong Kong, March 2004, pp. 1012-1022.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.