Simulation on Eliminating Interference in Long-Distance Communication

Abstract:

Due to wide frequency band, the long-distance communication is prone to be jammed by traditional radios. Furthermore, severe interference will lead to serious deterioration of performance. To solve this problem, the paper proposes energy-balance interference eliminated method and mixed communication algorithm, namely interference cancellation system model. The system elects a cluster head by utilizing the residual energy of nodes and the distance between cluster heads to balance the energy consumption and maximum the life cycle of the network. A Boolean vector corresponding to a random number defined is applied to this interference cancellation system. Experimental results show that under the premise of accurate channel estimation, systems using this technology to eliminate external interference in long-distance communication system have practical significance.

• Periodical: Applied Mechanics and Materials (Volumes 602-605)
• Pages: 3676-3679
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.602-605.3676
• Online since: August 2014
• Authors: Rong Fang Mei, Bai Chuan Cai*, Jian Guo Mei, Xiu Ying Li
• Keywords: Interference Cancellation, Long-Distance Communication, Noise Cancellation

References

[1] Ramakrishna B, Wang Jing, and Chang C I, et al. Spectral/spatial hyperspectral image compression in conjunction with virtual dimensionality. Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XI, Proc. 5806, SPIE, 2005: 772-781.

DOI: 10.1117/12.604128

[2] MANJESSHWAR A, GRAWAL D P. TEEN: a protocol for enhanced efficiency in wireless sensor networks[A]. Proc of the 15th Parallel and Distributed Processing Symp[C]. San Francisco: IEEE Computer Society, 2001. 2009-(2015).

DOI: 10.1109/ipdps.2001.925197

[3] Santhanaraman Gopalakrishnan, Wu Jiesheng, Huang Wei, et al. Designing zero-copy message passing interface derived data type communication over InfiniBand: alternative approaches and performance evaluation[J]. International Journal of High Performance Computing Applications, 2005, 19(2): 129-142.

DOI: 10.1177/1094342005054259

[4] Stephan K, Hibbitts C A, and Hoffmann H, et al. Reduction of instrument-dependent noise in hyperspectral image data using the principal component analysis: Applications to Galileo NIMS data[J]. Planetary and Space Science, 2008, 56(3): 406-419.

DOI: 10.1016/j.pss.2007.11.021

[5] Zhao Y and Swamy MNS. Design of least-asymmetric compactly supported orthogonal wavelets via optimization. IEEE Canadian Journal of Electrical and Computer Engineering, 2001; 26(1): 21.

DOI: 10.1109/ccece.1999.808069