基于馬爾科夫模型的認(rèn)知無(wú)線電動(dòng)態(tài)雙門(mén)限能量檢測(cè)策略

劉玉磊; 梁俊; 肖楠; 扈瑜龍; 胡猛

doi:10.11999/JEIT151400

基于馬爾科夫模型的認(rèn)知無(wú)線電動(dòng)態(tài)雙門(mén)限能量檢測(cè)策略

doi: 10.11999/JEIT151400

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61501496)，陜西省自然科學(xué)基金(2012JM8004)，航空科學(xué)基金(2013ZC15008)

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- 文章訪問(wèn)數(shù): 1330
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-12-14
- 修回日期: 2016-05-16
- 刊出日期: 2016-10-19

Dynamic Double Threshold Energy Detection Based on Markov Model in Cognitive Radio

Funds:

The National Natural Science Foundation of China (61501496), The Natural Science Foundation of Shaanxi Province (2012JM8004), The Aeronautical Science Foundation of China (2013ZC15008)

摘要

摘要: 該文針對(duì)低信噪比條件下頻譜感知精度低的問(wèn)題，提出一種基于馬爾科夫模型的動(dòng)態(tài)雙門(mén)限能量檢測(cè)算法。該算法根據(jù)信道時(shí)變特性建立基于馬爾科夫的頻譜占用模型，利用信道歷史狀態(tài)信息實(shí)現(xiàn)模型參數(shù)的修正。然后采用先聽(tīng)后說(shuō)的機(jī)制對(duì)處于雙門(mén)限之間的困惑信道狀態(tài)進(jìn)行判決，并詳細(xì)分析了噪聲不確定性對(duì)頻譜感知性能的影響。在此基礎(chǔ)上，為了克服噪聲不確定性的影響，以頻譜檢測(cè)概率最大為優(yōu)化目標(biāo)，對(duì)雙門(mén)限進(jìn)行實(shí)時(shí)更新。仿真結(jié)果表明，所提頻譜感知算法在減小噪聲不確定性影響的同時(shí)增加了頻譜感知精度，降低了認(rèn)知用戶的感知時(shí)間。
- 頻譜感知 /
- 能量檢測(cè) /
- 馬爾科夫模型 /
- 動(dòng)態(tài)雙門(mén)限
Abstract: With the development of the technology of cognitive radio, the standards of spectrum sensing performance become the higher and the higher, especially in low Signal-to-Noise Ratio (SNR) environments. A Dynamic Double-threshold Energy sensing method based on Markov Model (DDEMM) is proposed in this paper. By following the double-threshold energy sensing approach, the modified Markov model that accounts for the time varying nature of the channel occupancy is presented to resolve the confused channel state. Furthermore, in order to overcome the effect of noise uncertainty, a dynamic double-threshold spectrum sensing method is proposed, which adjusts its thresholds according to the achievable maximal detection probability. The results of extensive simulation demonstrate that the proposed DDEMM can achieve better detection performance than the conventional double-threshold energy sensing schemes, especially under very low SNR region.
- Spectrum sensing /
- Energy detection /
- Markov model /
- Dynamic double-threshold

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參考文獻(xiàn)(20)

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