本文選題：認(rèn)知無線網(wǎng)絡(luò) + 頻譜檢測�。� 參考：《北京郵電大學(xué)》2014年博士論文

【摘要】：隨著無線通信業(yè)務(wù)的飛速增長,無線用戶數(shù)量急劇上升,異構(gòu)網(wǎng)絡(luò)林立,不僅導(dǎo)致了頻譜資源日益緊缺,也造成了網(wǎng)絡(luò)端到端性能的下降。為了提高頻譜資源利用效率,提升網(wǎng)絡(luò)端到端效能,認(rèn)知無線網(wǎng)絡(luò)這一致力于對頻譜資源進(jìn)行動態(tài)共享、促進(jìn)異構(gòu)網(wǎng)絡(luò)融合的智能網(wǎng)絡(luò)應(yīng)運(yùn)而生。認(rèn)知技術(shù)是認(rèn)知無線網(wǎng)絡(luò)實(shí)現(xiàn)的關(guān)鍵技術(shù),而其中的頻譜檢測則是認(rèn)知技術(shù)的核心,也是實(shí)現(xiàn)頻譜資源高效利用的前提。因此,頻譜檢測成為了業(yè)內(nèi)研究的熱點(diǎn)。 盡管學(xué)者們針對頻譜檢測進(jìn)行了大量的研究,提出了多種頻譜檢測算法,但是頻譜檢測仍然面臨許多挑戰(zhàn)。本文主要針對頻譜檢測面臨的難點(diǎn)展開細(xì)致深入的研究。首先在前兩章中介紹了認(rèn)知無線電及認(rèn)知無線網(wǎng)絡(luò)的基本原理,并對相關(guān)的頻譜檢測技術(shù)、研究現(xiàn)狀及頻譜檢測所面臨的難點(diǎn)與挑戰(zhàn)進(jìn)行了分析與討論。隨后,我們提出了一種準(zhǔn)確高效的循環(huán)平穩(wěn)特征頻譜檢測算法,深入的分析了算法在不同衰落信道中的檢測性能,并全面分析了基于多天線檢測的算法性能,主要取得了以下幾個方面的研究成果： 1)準(zhǔn)確高效的循環(huán)平穩(wěn)特征檢測算法：現(xiàn)有的循環(huán)平穩(wěn)特征檢測雖然檢測準(zhǔn)確性高但存在著計算復(fù)雜度大、檢測時間長的問題。針對這個問題,本文提出了一種準(zhǔn)確高效的循環(huán)平穩(wěn)特征頻譜檢測算法。通過簡化現(xiàn)有循環(huán)平穩(wěn)特征檢測的檢驗(yàn)統(tǒng)計量,有效的降低了算法的計算復(fù)雜度,并根據(jù)該檢驗(yàn)統(tǒng)計量在不同條件下的概率密度函數(shù),推導(dǎo)了改進(jìn)算法檢測性能的閉合表達(dá)式。大量仿真結(jié)果驗(yàn)證了改進(jìn)算法的有效性和準(zhǔn)確性：首先,通過對計算復(fù)雜度的分析,本文所提出的改進(jìn)算法與現(xiàn)有算法相比,計算復(fù)雜度得到顯著降低；其次,檢測性能的理論值與仿真值能夠很好的吻合,驗(yàn)證了簡化后的檢驗(yàn)統(tǒng)計量的有效性及檢測性能閉合表達(dá)式的準(zhǔn)確性；雖然,簡化檢驗(yàn)統(tǒng)計量導(dǎo)致改進(jìn)算法的檢測性能與原有算法相比有0.36dB的性能損失,但卻以較小的性能損失換取了計算復(fù)雜度的大大降低,并且改進(jìn)算法仍保持了較高的檢測性能,為頻譜檢測的優(yōu)化設(shè)計提供了基礎(chǔ)。 2)改進(jìn)算法在衰落信道中的檢測性能研究：針對主用戶與次用戶之間的信道為多徑衰落和陰影衰落的實(shí)際場景,本文對不同的多徑衰落信道和復(fù)合多徑-陰影衰落信道中的改進(jìn)算法檢測性能進(jìn)行了深入的分析。為了準(zhǔn)確量化衰落信道對改進(jìn)算法檢測性能的影響,本文針對Nakagami衰落信道、瑞利衰落信道、萊斯衰落信道和復(fù)合瑞利-對數(shù)正態(tài)陰影衰落信道、復(fù)合Nakagami-對數(shù)正態(tài)陰影衰落信道中的檢測性能進(jìn)行定量分析,并分別利用概率密度函數(shù)(PDF, Probability Density Function)方法和矩母函數(shù)(MGF, Moment Generation Function)方法分別推導(dǎo)了改進(jìn)算法在相應(yīng)衰落信道中檢測性能的閉合表達(dá)式。通過比較,MGF方法簡單易行但有局限性,而PDF方法復(fù)雜但更具普適性,雖然這兩種檢測性能的分析方法各有利弊,但均為分析衰落信道下的檢測性能提供了有力的手段,并且這些分析方法不僅適用于分析循環(huán)平穩(wěn)特征檢測的性能,同樣也適用于分析其他檢測方法的性能。 3)基于多天線的改進(jìn)算法檢測性能研究：現(xiàn)有的針對基于多天線的循環(huán)平穩(wěn)特征檢測研究較少,且僅有的研究均針對獨(dú)立多天線,而沒有考慮更實(shí)際的相關(guān)多天線的情況。由于多天線的相關(guān)性會削弱多天線的分集增益,造成檢測性能的下降。因此,為了對多天線的檢測性能進(jìn)行全面的研究,本文全面分析了基于獨(dú)立多天線和相關(guān)多天線的改進(jìn)算法的檢測性能。對于獨(dú)立多天線檢測,首先考慮到認(rèn)知無線網(wǎng)絡(luò)中完整的信道狀態(tài)信息不易獲得的實(shí)際情況,本文采用了無需完整信道狀態(tài)信息的平方律合并方式,隨后研究了改進(jìn)算法在衰落信道中的檢測性能；對于相關(guān)多天線檢測,重點(diǎn)研究了常數(shù)相關(guān)、指數(shù)相關(guān)、線性陣列任意相關(guān)多天線的檢測性能。最后,利用MGF方法,推導(dǎo)了基于平方律合并的獨(dú)立多天線和相關(guān)多天線的檢測性能閉合表達(dá)式。仿真結(jié)果表明,盡管信道衰落與多天線的相關(guān)性會削弱檢測性能,但是多天線技術(shù)依然顯著的提高了檢測的準(zhǔn)確性,該研究有助于量化基于多天線的循環(huán)平穩(wěn)特征檢測的可達(dá)性能,并為該方法的實(shí)際應(yīng)用起到積極的促進(jìn)作用。 本文最后,我們對所做的工作進(jìn)行了總結(jié),并就下一步的研究方向及重點(diǎn)進(jìn)行了展望。
[Abstract]:With the rapid increase of wireless communication service , the number of wireless users has increased sharply , and heterogeneous network forest stands , which not only leads to the increasing frequency spectrum resources , but also reduces the end - to - end performance of the network . In order to improve the utilization efficiency of spectrum resources , improve the end - to - end efficiency of the network , the cognitive wireless network is devoted to dynamic sharing of the spectrum resources . The cognitive technology is the key technology of the cognitive radio network , and the spectrum detection is the premise of the efficient utilization of the spectrum resources . Therefore , the spectrum detection becomes the hot spot in the industry research .

In the first two chapters , we introduce the basic principle of cognitive radio and cognitive wireless network , and analyze and discuss the difficulties and challenges faced by the spectrum detection technology , research situation and spectrum detection .

1 ) An accurate and efficient algorithm for detecting cyclostationary features : The detection accuracy is high , and the detection time is long . In view of this problem , this paper proposes a kind of accurate and efficient algorithm for detecting circular stationary feature spectrum . By simplifying the test statistic of the existing circular stationary feature detection , the closed expression of the improved algorithm detection performance is deduced .
Secondly , the theoretical value and the simulation value of the detection performance can be well matched , and the validity of the simplified test statistic and the accuracy of the closed expression of the detection performance are verified ;
Although the simplified test statistic results in the performance loss of 0.36 dB compared with the original algorithm , the performance loss is reduced in exchange for the lower computational complexity , and the improved algorithm still keeps higher detection performance , which provides the basis for the optimization design of spectrum detection .

In order to accurately quantify the effect of fading channel on detection performance of fading channel , this paper makes a quantitative analysis of the performance of the improved algorithm in the fading channel of multi - path fading channel , Rayleigh fading channel , Rice fading channel and composite Rayleigh - log fading channel .

3 ) Based on multi - antenna improved algorithm detection performance research : The existing research on multi - antenna based loop smooth feature detection is few , and only the research is aimed at independent multi - antenna , and the detection performance of multi - antenna is not taken into account . Therefore , in order to study the detection performance of multi - antenna , the paper comprehensively analyzes the performance of the improved algorithm based on independent multi - antenna and related multi - antenna .
Based on the MGF method , the closed expression of the detection performance of independent multi - antenna and related multi - antenna based on square law is studied . The simulation results show that , although the correlation of channel fading and multi - antenna can weaken the detection performance , the simulation results show that the multi - antenna technology can improve the accuracy of detection , which can help quantify the accessibility of the multi - antenna based circular stationary feature detection and play a positive role in the practical application of the method .

In the end , we summarize the work done , and look forward to the research direction and focus of the next step .

【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN92

【參考文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 王再勵;認(rèn)知無線網(wǎng)絡(luò)中的協(xié)作頻譜檢測技術(shù)研究[D];北京郵電大學(xué);2011年

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本文編號：1830882