5th International ICST Conference on Communications and Networking in China

Research Article

CRAT: A novel routing algorithm for wireless sensor networks based on cooperative MIMO

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  • @INPROCEEDINGS{10.4108/chinacom.2010.128,
        author={Pingyuan Liang and Xingcheng Liu},
        title={CRAT: A novel routing algorithm for wireless sensor networks based on cooperative MIMO},
        proceedings={5th International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2011},
        month={1},
        keywords={Wireless Sensor Networks Cooperative MIMO Energy Consumption Routing Algorithm CRAT},
        doi={10.4108/chinacom.2010.128}
    }
    
  • Pingyuan Liang
    Xingcheng Liu
    Year: 2011
    CRAT: A novel routing algorithm for wireless sensor networks based on cooperative MIMO
    CHINACOM
    ICST
    DOI: 10.4108/chinacom.2010.128
Pingyuan Liang1,2,*, Xingcheng Liu1,*
  • 1: School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China
  • 2: College of Physics Science and Information Engineering, Jishou University, Jishou, China
*Contact email: liangpingyuan123@163.com, isslxc@mail.sysu.edu.cn

Abstract

Cooperative MIMO technology can be used to reduce the total energy consumption compared with traditional SISO technology under condition that the transmission distances surpass a threshold in wireless sensor networks. In order to solve the routing optimization problem of multi-hop extensible wireless sensor networks based on cooperative MIMO, a novel cost-based routing algorithm with thresholds (CRAT) is proposed. In the algorithm, the routing paths stretch out unboundedly from monitor node and reach the base station ultimately fixed on thresholds, and the routing structure of the CRAT algorithm is different from other cost-based routing algorithms. The energy consumption and thresholds of the algorithm have been analyzed. After that, we define the cost function of CRAT algorithm according to relevant parameters including energy consumption, residual energy, hops and antennas. Finally, the experiments verify the effectiveness of the CRAT algorithm in saving energy, and the reasonableness of the cost function.