Skip to main content
Log in

Efficient Data Transmission of Wireless Sensor Networks Through Compressive Sensing and Matrix Completion

  • Published:
International Journal of Wireless Information Networks Aims and scope Submit manuscript

Abstract

Data transmission has attracted widely concerning from worldwide researchers in wireless sensor networks. Jointly considered compressive sensing and matrix completion, a novel cross-layer optimal data transmission algorithm by maximizing utility function is proposed, which develops the stability control signal and valid link capacity. Original signals, with low-rank and sparsity, are processed that lead to the transmission is much less than original traffic. At same time, link capacity is allocated in a fair way, which avoids the congestion for data flow too large. Simulation results demonstrate that the algorithm is significantly effective for network lifetime and energy consumption.

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
Fig. 4

Similar content being viewed by others

References

  1. Li Shancang, Xu Lida and Wang Xinheng. Compressed Sensing Signal and Data Acquisition in Wireless Sensor Networks and Internet of Things[J]. IEEE Transactions on Industrial Informatics, 2013, 9(4): 2177–2186.

  2. Xue Tong, Dong Xiaodai, Shi Yi. Multiple Access and Data Reconstruction in Wireless Sensor Networks Based on Compressed Sensing[J]. IEEE Transactions on Wireless Communications, 2013, 12(7): 3399–3411.

  3. Zheng Haifeng, Xiao Shilin, Wang Xinbing, Tian Xiaohua, Guizani Mohsen. Capacity and Delay Analysis for Data Gathering with Compressive Sensing in Wireless Sensor Networks[J]. IEEE Transactions on Wireless Communications, 2013, 12(2): 917–927.

  4. Cheng Jie, Ye Qiang, Jiang Hongbo, Wang Dan, Wang Chonggang. STCDG: An Efficient Data Gathering Algorithm Based on Matrix Completion for Wireless Sensor Networks[J]. IEEE Transactions on Wireless Communications, 2013, 12(2): 850–861.

  5. Candµes E J, Romberg J, Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2): 489–509.

  6. Xu Songcen, Lamare Rodrigo C. de, Poor H.Vincent. Distributed compressed Estimation Based on Compressive Sensing[J]. IEEE Signal Processing Letters, 2015, 22(9):1311–1315.

  7. Rui-Ping Wen, Xi-Hong Yan. A new gradient projection method for matrix completion[J]. Applied Mathematics and Computation, 2015, 258:537–544.

  8. H. Zhang, L.Z. Cheng, W. Zhu. A lower bound guaranteeing exact matrix completion via singular value thresholding algorithm[J]. Applied and Computational Harmonic Analysis, 2011, 31: 454–459.

  9. Chen Lijun, Steven H. Low and John C. Doyle. Cross-layer Design in Multihop Wireless Networks[J]. Computer Networks, 2011,55:480-496.

  10. Li Bin, Li Ruogu, Eryilmaz Atilla. Throughput-Optimal Scheduling Design With Regular Service Guarantees in Wireless Sensor Networks[J]. IEEE Transactions on Networking, 2015, 23(5): 1542–1552.

Download references

Acknowledgments

This work has been supported by the National Natural Science Foundation of China under Grant No. 61374097, Fundamental Research Funds for the Central Universities of China N142303013, Program of Science and Technology Research of Hebei University QN2014326, School Funds Project of Northeastern University at Qinhuangdao XNB2015004.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chengtie Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, C., Wang, J. & Li, M. Efficient Data Transmission of Wireless Sensor Networks Through Compressive Sensing and Matrix Completion. Int J Wireless Inf Networks 23, 135–140 (2016). https://doi.org/10.1007/s10776-016-0303-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10776-016-0303-6

Keywords

Navigation