Skip to main content

Advertisement

Log in

MAP Based V-BLAST Transmission to Improve Network Lifetime in Virtual MIMO Based Wireless Sensor Networks

  • Short Communication
  • Published:
National Academy Science Letters Aims and scope Submit manuscript

Abstract

One of the major issues in wireless sensor network is to reduce the energy consumption and to improve the network lifetime. Present work describes about the maximum a posterior estimate based V-BLAST transmission is used to improve the network life time of energy constrained networks. Here the sensors are randomly distributed and for data transmission V-BLAST method is used. Before transmitting data, the source node has to choose cooperative nodes and at each hop the selection of cooperative nodes is necessary. For proper selection of cooperative nodes, both prior and posterior probabilities are considered. The posterior probability is calculated with the knowledge of prior probability. The prior parameters are residual energy (\( {\text{R}}_{\text{e }} \)) and distance (\( {\text{D}}_{\text{t }} \)) of the intermediate nodes. The post conditions are channel interference (\( {\text{C}}_{\text{i }} \)), delay for transmitting (\( {\text{T}}_{\text{d }} \)) data to intermediator node, overload (\( {\text{O}}_{\text{l }} \)) at an intermediator node.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

References

  1. Garg J, Mehta P, Gupta K (2013) A review on cooperative communication protocols in wireless world. Int J Wirel Mob Netw IJWMN 5(2):107–126. doi:10.5121/ijwmn.2013.520

    Google Scholar 

  2. Nosratinia A, Hunter TE (2004) Cooperative communication in wireless networks. IEEE Commun Mag 42:74–80

    Article  Google Scholar 

  3. Ohize HO (2011) Emerging issues in wireless sensor networks. J Softw Autom 2:11–15

    Google Scholar 

  4. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Elsevier Comput Netw 52:2292–2330

    Article  Google Scholar 

  5. Rohde and schwarz (2009) Introduction to MIMO, application note, Schindler, Schulz, 1M A142_0e:1-23

  6. Heath RW, Larsson EG, Murch R, Nehorai A, Uysal M (2004) Multiple-input multiple-output (mimo) communications. Wirel Commun Mob Comput 4:693–696. doi:10.1002//wcm.247

    Article  Google Scholar 

  7. de Lamare RC, Haardt M, Joham M, Le Ruyet D, Love DJ (2011) Recent advances in multiuser MIMO systems. EURASIP J Wirel Commun Netw. doi:10.1186/1687-1499-2011-157

    Google Scholar 

  8. Burdin J, Dunyak J (2005) Enhancing the performance of wireless sensor networks with MIMO communications. In: MILCOM 2005, vol, 4. pp 2321–2326. doi:10.1109/MILCOM.2005.1606015

  9. Jayaweera SK (2006) Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks. IEEE Trans Wirel Commun 5(5):984–989. doi:10.1109/TWC.2006.1633350

    Article  Google Scholar 

  10. Zhou Y, Adachi F, Wong K-K, Xia X-G, Toumpakaris D, Steendam H, Zhu W-P, Yang L-L (2013) Guest editorial: virtual MIMO. IEEE J Sel Areas Commun 31(10):1977–1980. doi:10.1109/SAC.2013.131001

    Article  Google Scholar 

  11. Bravos GN, Kanatas AG (2007) Energy efficiency of MIMO-based sensor networks with a cooperative node selection algorithm. In: ICC 2007, pp 3218–3223. doi:10.1109/ICC.2007.534

  12. Ahmed I, Peng M, Wang W (2007) Optimal number of energy efficient cooperative nodes selection in wireless sensor networks-in Ricean fading environment. In: IEEE conference proceedings, pp 2384-2387. doi:10.1109/WICOM.2007.594

  13. Ben M, Raoof K, Bouallegue A (2011) Sensor nodes selection in wireless sensor networks over a rich scattering environment. In: CCCA, pp 1–5. doi:10.1109/CCCA.2011.6031465

  14. Ratnayake R, Kavcic A, Wei G-Y (2007) A high-throughput Maximum a posteriori probability detector. In: Custom intergrated circuits conference (CICC), pp 455–458, doi:10.1109/CICC.2007.4405772

  15. Jayaweer SK (2007) V-BLAST-based virtual MIMO for distributed wireless sensor networks. IEEE Trans Commun 55(10):1867–1872. doi:10.1109/TCOMM.2007.906389

    Article  Google Scholar 

  16. Xu K, Chizun D (2007) A V-BLAST based virtual MIMO transmission scheme for sensor network lifetime maximization. In: Proceedings of the 66th IEEE vehicular technology conference, pp 377–381. doi:10.1109/VETECF.2007.91

  17. Rajeswari K, Bhagyaveni MA (2014) Probabilistic approach for selecting cooperative nodes in virtual MIMO based wireless sensor networks. Int J Appl Eng Res 9(21):11225–11234

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Rajeswari.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rajeswari, K., Bhagyaveni, M.A. MAP Based V-BLAST Transmission to Improve Network Lifetime in Virtual MIMO Based Wireless Sensor Networks. Natl. Acad. Sci. Lett. 40, 409–414 (2017). https://doi.org/10.1007/s40009-017-0578-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40009-017-0578-x

Keywords

Navigation