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Energy Conservation Technique for Multiple Radio Incorporated Smart Phones

  • Shalini PrasadEmail author
  • S. Balaji
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 464)

Abstract

Nowadays the advanced radio system in mobile devices is utilized as part of wireless communication towards an upgrade of channel capacity. Top end applications have allowed high-speed networking interfaces to connect the mobile network with many wireless routers, which helps in data transmission in mobile systems. These network interfaces require huge power for high-speed data transmission. In this, diversity and spatial gains are the two principle points of interest of mobile devices with higher delivery of throughput that are utilized to concentrate on improving bit-rate by increasing the quantity of transceiver antenna systems. This paper introduces an energy conservation mechanism for mobile devices. The key idea in antenna management is to remove adaptively percentage of the antennas and additionally their RF chains to reduce energy dissipation due to circuit power. This mechanism will reduce the power consumption and improve power efficiency by disabling the subset antennas and its RF chains. The proposed system will decide the active antennas for power minimization while achieving its data rate requirements. Matlab simulation is used in the proposed study, and the results are validated using the performance parameters such as data rate, transmit power and data rate constraints.

Keywords

Antenna management Energy per bit MIMO interface Mobile system Power saving management 

References

  1. 1.
    Hsu, C.-C., Chang, J.M., Chou, Z.-T., Abichar, Z.: Optimizing spectrum-energy efficiency in downlink cellular networks. IEEE Trans. Mob. Comput. 13(9), 2100–2112 (2014)CrossRefGoogle Scholar
  2. 2.
    Nigus, H.R., Kim, K-H., Hwang, D., Hussen, H.R.: Multi-antenna channel capacity enhancement in wireless communication. In: Seventh International Conference on Ubiquitous and Future Networks (ICUFN), pp. 77–82 (2015)Google Scholar
  3. 3.
    Gross, C., Kaup, F., Stingl, D., Richerzhagen, D., Hausheer, D., Steinmetz, R.: EnerSim: an energy consumption model for large-scale overlay simulators. IEEE-Local Comput. Netw. 252–255 (2013)Google Scholar
  4. 4.
    Haverinen, H., Siren, J., Eronen, P.: Energy consumption of always-on applications in WCDMA networks. In: IEEE Vehicular Technology Conference, Dublin, Ireland, pp. 964–968 (2007)Google Scholar
  5. 5.
    Vergara, E.J., Tehrani, S.N.: Energybox: a trace-driven tool for data transmission energy consumption studies. In: Energy Efficiency in Large Scale Distributed Systems, pp. 19–34. Springer, Heidelberg (2013)Google Scholar
  6. 6.
    Balasubramanian, N., Balasubramanian, A., Venkataramani, A.: Energy consumption in mobile phones: a measurement study and implications for network applications. In: ACM Internet Measurement Conference, pp. 280–293, Chicago, USA (2009)Google Scholar
  7. 7.
    Kelenyi, I., Nurminen, J.K.: Energy aspects of peer cooperation—measurements with a mobile DHT system. In: IEEE International Conference on Communications, pp. 164–168, Beijing, China (2008)Google Scholar
  8. 8.
    Lane, N.D., Chon, Y., Zhou, L., Zhang, Y., Li, F.: Piggyback Crowd Sensing (PCS): energy efficient crowd sourcing of mobile sensor data by exploiting smart phone app opportunities. In: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems (2013)Google Scholar
  9. 9.
    Damasevicius, R., Stuikys, V., Toldinas, J.: Methods for measurement of energy consumption in mobile devices. Metrol. Meas. Syst. 3, 419–430 (2012)Google Scholar
  10. 10.
    Perälä, P.H.J., Barbuzzi, A., Boggia, G., Pentikousis, K.: Theory and practice of RRC state transitions in UMTS networks. In: IEEE Broadband Wireless Access Workshop, pp. 1–6, Hawaii, USA (2009)Google Scholar
  11. 11.
    Han, H., Yu, J., Zhu, H., Chen, Y.: Energy-efficient engine for frame rate adaptation on smartphones. In: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, vol. 15 (2013)Google Scholar
  12. 12.
    Sun, L., Sheshadri, R.K., Zheng, W., Koutsonikolas, D.: Modeling WiFi active power/energy consumption in smartphones. In: IEEE-34th International Conference on Distributed Computing Systems, pp. 41–51 (2014)Google Scholar
  13. 13.
    Prasad, S., Balaji, S.: Effectiveness of energy management in mobile devices: a study. Int. J. Electron. Commun. Eng. Technol. (IJECET) 5(3), 58–69 (2014)Google Scholar
  14. 14.
    Prasad, S., Balaji, S.: Real-time energy dissipation model for mobile devices. Emerg. Res. Comput. Inf. Commun. Appl. 281–288 (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of E&CEJain UniversityBengaluruIndia
  2. 2.Center for Engineering Technologies, Jain Global CampusJain UniversityJakkasandra Post, Kanakapura Taluk, Ramanagara District, BengaluruIndia

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