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Automatic Control and Computer Sciences

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01-03-2020

Energy Efficient Node Deployment Optimization for CTS Based on Cooperative Beamforming in Single-Hop Wireless Sensor Networks

Published in: Automatic Control and Computer Sciences | Issue 2/2020

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Abstract

Node deployment has an influence on energy dissipation of cooperative transmission scheme (CTS) in wireless sensor networks. In order to reduce the energy dissipation in single-hop wireless sensor networks, the problem of node deployment for cooperative beamforming (CBF) based CTS is studied in this paper. First, the energy dissipation for CTS based on CBF is studied, then the node’s position and the modulation size is optimized through two-step optimization to minimize energy dissipation. Numerical results show that the optimized node deployment and CBF scheme can greatly reduce the energy dissipation.

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Feng, D., Jiang, C., Lim, G., Cimini, L.J., Feng, G., and Li, G.Y., A survey of energy-efficient wireless communications, IEEE Commun. Surv. Tutor., 2013, vol. 15, no. 1, pp. 1089–1098.

Jayaweera, S.K. and Poor, H.V., Capacity of multiple-antenna systems with both receiver and transmitter channel state information, IEEE Trans. Inf. Theory, 2003, vol. 49, no. 10, pp. 2697–2709.MathSciNetCrossRef

Krunz, M., Siam, M.Z., and Nguyen, D.N., Clustering and power management for virtual MIMO communications in wireless sensor networks, Ad Hoc Networks, 2013, vol. 11, no. 5, pp. 1571–1587.CrossRef

Cui, S., Goldsmith, A.J., and Bahai, A., Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks, IEEE J. Sel. Areas Commun., 2004, vol. 22, no. 6, pp. 1089–1098.CrossRef

Gao, Q., Zuo, Y., Zhang, J., and Peng, X.H., Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation, IEEE Trans. Veh. Technol., 2010, vol. 59, no. 8, pp. 3956–3965.CrossRef

Chung, J.M., Kim, J., and Han, D., Multihop hybrid virtual MIMO scheme for wireless sensor networks, IEEE Trans. Veh. Technol., 2012, vol. 61, no. 9, pp. 4069–4078.CrossRef

Yao, L.P., Xi, L., Hong, J., and Xu, Q.S., Systematic energy-balanced cooperative transmission scheme in wireless sensor networks, J. China Univ. Posts Telecommun., 2012, vol. 19, no. 6, pp. 14–18.CrossRef

Li, J., Jiang, X., and Lu, I.T., Energy balance routing algorithm based on virtual MIMO scheme for wireless sensor networks, J. Sensors, 2014.

Xu, H., Huang, L., Qiao, C., Wang, X., and Sun, Y.E., Topology control with vMIMO communication in wireless sensor networks, IEEE Trans. Wireless Commun., 2013, vol. 12, no. 12, pp. 6328–6339.CrossRef

10.

Jayaweera, S.K., V-BLAST-based virtual MIMO for distributed wireless sensor networks, IEEE Trans. Commun., 2007, vol. 55, no. 10, pp. 1867–1872.MathSciNetCrossRef

11.

Rafique, Z., Seet, B.C., and Al-Anbuky, A., Performance analysis of cooperative virtual MIMO systems for wireless sensor networks, Sensors, 2013, vol. 13, no. 6, pp. 7033–7052.CrossRef

12.

Fan, J.C., Yin, Q.Y., Wang, W.J., and Feng, A., Analysis of energy efficiency for cooperative beamforming in wireless sensor networks, J. Commun., 2008, vol. 29, no. 11, pp. 145–151.

13.

Bejar Haro, B., Zazo, S., and Palomar, D.P., Energy efficient collaborative beamforming in wireless sensor networks, IEEE Trans. Signal Process., 2014, vol. 62, no. 2, pp. 496–510.MathSciNetCrossRef

14.

Cui, S., Goldsmith, A.J., and Bahai, A., Energy-constrained modulation optimization, IEEE Trans. Wireless Commun., 2005, vol. 4, no. 5, pp. 2349–2360.CrossRef

15.

Jiang, R.Y., Wei, J., and Zheng, B.Y., Joint optimization of energy dissipation in cooperative wireless sensor networks, J. Electron. Inf. Technol., 2010, vol. 32, no. 6, pp. 1475–1479.

16.

Weiguang Shi, Xiaoli Qi, Jianxiong Li, Shuxia Yan, and Liying Chen, Simple solution to the optimal deployment of cooperative nodes in two-dimensional TOA-based and AOA-based localization system, EURASIP J. Wireless Commun. Networking, 2017.

17.

Jaison, A., Kavitha, N., and Janardhanan, P.S., Docker for optimization of Cassandra NoSQL deployments on node limited clusters, 2016 International Conference on Emerging Technological Trends (ICETT), 2017.

18.

Kumar, V., Singh, P., and Patra, S.K., Achievable rate and power efficiency of massive MIMO in cooperative network with ZF receivers, TENCON 2017—2017 IEEE Region 10 Conference, 2017.

19.

Sheikh, J.A., et al., A new method of speech transmission over space time block coded co-operative MIMO–OFDM networks using time and space diversity, Int. J. Speech Technol., 2017.

Title: Energy Efficient Node Deployment Optimization for CTS Based on Cooperative Beamforming in Single-Hop Wireless Sensor Networks
Publication date: 01-03-2020
Published in: Automatic Control and Computer Sciences / Issue 2/2020
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411620020066

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