Channel Assignment Strategy Based on the Sustained-Transmission Rule of Nodes in Cognitive Radio Sensor Network

Xinbin Li; Zequn Huang; Song Han; Jianmei Chen

doi:10.11959/j.issn.1000-0801.2015062

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Channel Assignment Strategy Based on the Sustained-Transmission Rule of Nodes in Cognitive Radio Sensor Network

Ressearch and development | 更新时间：2024-06-05

- Channel Assignment Strategy Based on the Sustained-Transmission Rule of Nodes in Cognitive Radio Sensor Network
- Telecommunications Science Vol. 31, Issue 3, Pages: 109-114(2015)
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- DOI：10.11959/j.issn.1000-0801.2015062
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- Published Online：2015-03，
  
  Published：20 March 2015
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Xinbin Li, Zequn Huang, Song Han, et al. Channel Assignment Strategy Based on the Sustained-Transmission Rule of Nodes in Cognitive Radio Sensor Network[J]. Telecommunications science, 2015, 31(3): 109-114.
DOI：

Xinbin Li, Zequn Huang, Song Han, et al. Channel Assignment Strategy Based on the Sustained-Transmission Rule of Nodes in Cognitive Radio Sensor Network[J]. Telecommunications science, 2015, 31(3): 109-114. DOI： 10.11959/j.issn.1000-0801.2015062.

摘要

在异构分级式认知传感器网络中，为提高数据分组的传输成功率，提出将节点划分为具备持续传输条件和不具备持续传输条件两类，两类节点分别以牺牲较多能耗和分配较优信道的方式提高数据分组的传输成功率，并由此得到一种集中式信道分配策略。为了降低节点在信息传输过程中每比特平均能耗，对数据分组自适应调节机制进行了优化，确保不具备持续传输条件的节点得到最优的传输数据分组大小。仿真结果证明，提出的分配策略和优化机制能够有效提高能量的使用效率，改善网络性能。

Abstract

In order to improve the success rate of data packet transmission in heterogeneous and hierarchical cognitive radio sensor network

the nodes were divided into sustained-transmission and non-sustained-transmission conditions.The ways of improving the success rate of data packet transmission are more energy consumption and better channel assignment

so that there is a type of centralized channel assignment strategies.At the same time

in order to reduce the energy consumption per bit in information transmission process of nodes

the packet size adaptation mechanism was optimized

ensuring the optimal packet size of non-sustained-transmission nodes.Simulation results demonstrate that the channel assignment strategy and the optimization mechanism improve the efficiency of energy utilization and the performance of network.

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references

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