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無線傳感網(wǎng)絡(luò)量化及能量優(yōu)化策略

呂敬祥,  羅文浪

呂敬祥, 羅文浪. 無線傳感網(wǎng)絡(luò)量化及能量優(yōu)化策略[J]. 電子與信息學(xué)報(bào), 2020, 42(5): 1118-1124. doi: 10.11999/JEIT190185
引用本文: 呂敬祥, 羅文浪. 無線傳感網(wǎng)絡(luò)量化及能量優(yōu)化策略[J]. 電子與信息學(xué)報(bào), 2020, 42(5): 1118-1124. doi: 10.11999/JEIT190185
Jingxiang Lü, Wenlang LUO. Quantization and Energy Optimization Strategy of Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1118-1124. doi: 10.11999/JEIT190185
Citation: Jingxiang Lü, Wenlang LUO. Quantization and Energy Optimization Strategy of Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1118-1124. doi: 10.11999/JEIT190185

無線傳感網(wǎng)絡(luò)量化及能量優(yōu)化策略

doi: 10.11999/JEIT190185
  • 1.

    井岡山大學(xué)電子與信息工程學(xué)院 吉安 343009

  • 2.

    流域生態(tài)與地理環(huán)境監(jiān)測國家測繪地理信息局重點(diǎn)實(shí)驗(yàn)室 吉安 343009

基金項(xiàng)目: 國家自然科學(xué)基金(51867011)，江西省教育廳科技計(jì)劃項(xiàng)目(GJJ180576)，省部重點(diǎn)實(shí)驗(yàn)室開放基金(WE2016014)
詳細(xì)信息
    作者簡介:

    呂敬祥：男，1977生，博士，講師，研究方向?yàn)槲锫?lián)網(wǎng)

    羅文浪：男，1967生，博士，教授，研究方向?yàn)橹悄苄畔⑻幚?/p>

    通訊作者:

    羅文浪　lpanpan2005@sina.com.cn

  • 中圖分類號: TN915.04

Quantization and Energy Optimization Strategy of Wireless Sensor Networks

  • 1.

    Faculty of Electronics and Information Engineering, Jing Gang Shan University, Ji’an 343009, China

  • 2.

    Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, National Administration of Surveying, Mapping and Geoinformation, Ji’an 343009, China

Funds: The National Natural Science Foundation of China (51867011), The Education Office Science and Technology Plan Project of Jiangxi Province (GJJ180576), The Provincial Key Laboratory Open Fund (WE2016014)
  • 摘要:

    由于無線傳感網(wǎng)絡(luò)(WSN)存在能量和帶寬的限制，在網(wǎng)絡(luò)中直接傳送模擬信號受到了極大地制約，因此對模擬信號量化是節(jié)省網(wǎng)絡(luò)能量和保證有效帶寬的重要手段。為此，該文以融合中心的重構(gòu)絕對均值誤差最小為原則，設(shè)計(jì)一種網(wǎng)絡(luò)量化及能量優(yōu)化方法。首先，針對單傳感器，在能量固定的情況下推導(dǎo)了最優(yōu)量化位數(shù)及在量化位數(shù)固定的情況下推導(dǎo)了最優(yōu)能量分配。其次，在單傳感器的基礎(chǔ)上，進(jìn)一步推導(dǎo)多傳感器情況下最優(yōu)量化位數(shù)及最優(yōu)能量分配。以上兩種情況都考慮了傳感器測量噪聲及信道衰落損耗。最后，通過數(shù)值仿真方法驗(yàn)證了文中所提方法的正確性，并將其與等能量分配進(jìn)行了比較，獲得了較好的效果。

    Abstract:

    Due to the limitation of energy and bandwidth in Wireless Sensor Networks(WSN), the direct transmission of analog signals in the network is greatly restricted. Therefore, quantization of analog signals is an important means to save network energy and ensure effective bandwidth. To this end, based on the principle of minimum absolute mean reconstruction error a network quantization and energy optimization method is designed in this paper. Firstly, for single sensor, the optimal quantization bit number is derived under the condition of fixed energy and the optimal energy distribution is derived under the condition of fixed quantization bit number. Secondly, on the basis of single sensor, the optimal quantization bit number and optimal energy allocation are further deduced in multi-sensor case. In both cases, the sensor measurement noise and channel fading loss are considered. Finally, the numerical simulation results show that the proposed method is correct and better than the equal energy distribution.

    • HTML全文

  • 圖  1  單傳感器傳播到融合中心模型圖

    圖  2  多鏈路模型

    圖  3  等能量和最優(yōu)能量分配重構(gòu)誤差比較

    圖  4  最優(yōu)能量分配因子

    圖  5  等能量分配時(shí)不同信噪比重構(gòu)誤差

    圖  6  量化位長度固定時(shí)重構(gòu)誤差比較

    圖  7  量化位長度不固定時(shí)重構(gòu)誤差比較

    圖  8  最優(yōu)量化位固定時(shí)最優(yōu)能量分配

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  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2019-03-26
  • 修回日期:  2019-11-07
  • 網(wǎng)絡(luò)出版日期:  2019-11-13
  • 刊出日期:  2020-06-04

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