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姓名 李政修(Jheng-Siou Lee) 查詢紙本館藏 畢業系所 電機工程學系 論文名稱 在頻譜異構之隨意式感知無線電網路下利用空域-頻域-時域特性之多頻段能量偵測演算法
(Exploiting Spatial-Spectral-Temporal Properties for Heterogeneous Spectrum Sensing in Cognitive Radio Ad-Hoc Networks)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 本論文提出應用於頻譜異構之隨意式感知無線電網路下的多頻段能量偵測演算法,此演算法利用通道在空域、頻域與時域上的特性,來改善頻譜偵測效能。感知無線電下的次要使用者並無授權頻段的使用權,若其欲使用頻譜資源,必須在事前對頻譜進行週期性的偵測以確認頻譜空洞的存在,當發現頻譜空洞時,還須在不干擾主要使用者的前提之下,以機會性方式對頻譜資源進行存取。從次要使用者對頻譜進行使用的過程中可發現,頻譜偵測是感知無線電中最為重要的課題,其相關研究也將在本篇論文中繼續被探討。異構頻譜環境下不同的次要使用者會感受到相異的頻譜使用狀況,但部分次要使用者會因地理環境的緣故,而感受到相似的頻譜使用情形,這類有相似頻譜使用情況的環境又稱之為同構頻譜環境。為了使同構頻譜環境下的次要使用者們能彼此合作,利用插入權重定位演算法對主要使用者傳送端做定位,並根據次要使用者與主要使用者傳送端之間的距離來判斷次要使用者是否位在主要使用者傳送端的傳輸範圍內,進而推斷出次要使用者之間是異構還是同構的關係。同構頻譜環境的次要使用者們隨著所處的環境不同,將遭受不同程度的衰減。為了有效提高對頻譜的偵測能力,次要使用者們利用空間與時間上的多樣性,並透過馬可夫鏈的能量遞迴運算方式,使次要使用者與鄰居之間進行資訊交換,以提高資訊可信度;為了善用頻段之間的相關性,建議所有的次要使用者對頻譜進行寬頻頻譜偵測,SNR-based weighted wideband spectrum sensing便是利用頻段之間在使用上的關聯性對寬頻頻段偵測結果做權衡,以提升偵測精準度。
在硬體設計中,插入權重定位演算法與能量遞迴運算需要經過多次遞迴計算,將造成硬體成本的增加,但若採用以時間換取空間的方式,將資料回傳再運算,則可大大節省硬體面積。適當地插入管線不僅有助於排程,更能提高運算吞吐量。最終的硬體設計將以FPGA型號:Spartan6 XC6SLX150來做驗證,複雜的硬體僅使用9顆CORDIC除法器與8顆CORDIC絕對值器,綜觀而言,實屬一低複雜度的硬體設計。
摘要(英) In this paper, we propose an algorithm for heterogeneous spectrum sensing in cognitive radio ad-hoc network. This algorithm utilizes the spatial domain, frequency domain and time domain characteristics of the primary user occupancy to improve the spectrum sensing performance. In the heterogeneous spectrum environment, different secondary users may experience similar or dissimilar spectrum usage due to the geographical location. In the transmission range of the primary user, a similar spectrum occupancy appears. It is called the homogeneous spectrum environment. The weighted interpolation positioning algorithm (WIP) is used to locate the position of the primary transmitter and thus those secondary users can cooperate with each other when they are identified as nodes in the homogeneous environments. Given the assumption of the fixed transmitter of the primary user, tracking mechanism is used to enhance the accuracy of localization. On the other hand, the energy recursion algorithm based on Markov-chain to exchange information among neighboring secondary users can generate converged energy detection result after several iterations. In addition, wideband spectrum sensing is also adopted. Secondary users utilize the correlation of spectrum occupancy to detect the activity of the wide-band spectrum with SNR-based weighted wideband spectrum sensing technique. Thus, the network level detection performance can be improved with these algorithms that exploit the spatial, spectral, temporal properties to detection spectrum holes for opportunistic spectrum accesses of the secondary users.
For the hardware design, the weighted interpolation positioning algorithm(WIP) and the energy recursive operation is calculated iteratively. With the time-sharing technique, the hardware complexity can be reduced. Only 9 CORDIC dividers and 8 CORDIC absoluters exist in the 8 parallel-processing wide-band spectrum sensing modules. Finally, the design is verified by FPGA, Spartan6
XC6SLX150.
關鍵字(中) ★ 感知無線電
★ 頻譜異構環境
★ 能量偵測關鍵字(英) ★ Cognitive radio
★ Heterogeneous spectrum environment
★ Energy detection論文目次 第一章 緒論 1
1.1研究動機 1
1.2研究方法 1
1.3論文組織 2
第二章 背景及相關知識介紹 3
2.1 頻譜使用模式 3
2.1.1交織式(Interweave) 3
2.1.2隱藏式(Underlay) 4
2.1.3重疊式(Overlay) 4
2.2 感知無線電網路架構 5
2.2.1基礎建設型的感知無線電網路 6
2.2.2隨意式感知無線電網路 6
2.3 頻譜管理機制 7
2.3.1頻譜偵測(Spectrum Sensing). 8
2.3.2頻譜決定(Spectrum Decision) 14
2.3.3頻譜分享(Spectrum Sharing) 15
2.3.4頻譜移動(Spectrum Mobility) 16
第三章 無線通道與無線電傳播模型 17
3.1 大尺度傳播模型(Large Scale Propagation Model) 17
3.1.1路徑損耗模型與遮蔽效應(Path Loss Model and Shadowing Effect) 17
3.2 小尺度傳播模型(Small Scale Propagation Model) 18
3.2.1多重路徑傳播效應(Multipath Propagation Effect) 18
3.2.2都普勒延遲(Doppler Spread) 20
3.3 加成性白高斯雜訊 22
3.4系統通道模型 23
第四章 利用空域-頻域-時域特性之多頻段能量偵測演算法 25
4.1系統架構 25
4.1.1訊號模型 26
4.1.2能量偵測模型 26
4.1.3網路模型 30
4.2定位式用戶分群法 36
4.2.1插入權重定位演算法(Weighted Interpolation Positioning Algorithm) 36
4.3分散式共識演算法 38
4.3.1一般平均共識(Average Consensus-Based) 39
4.3.2權重平均共識(Weighted Average Consensus) 43
4.3.3接收機操作特性曲線 45
4.4寬頻頻譜偵測 47
4.4.1以訊雜比為權重的多頻段頻譜偵測機制 47
4.4.2利用空域-頻域-時域特性之多頻段能量偵測演算法 49
4.5模擬結果與討論 51
4.5.1模擬參數 51
4.5.2定位與能量統計量的收斂分析 53
4.5.3定位誤差分析 55
4.5.4偵測效能分析 58
第五章 硬體設計與實現 64
5.1 硬體設計流程 64
5.2硬體架構設計 65
5.2.1功能方塊圖 65
5.2.2部件架構 69
5.3硬體共用與資料流 74
5.3.1資料流 74
5.3.2硬體共用部分 78
5.4硬體實現與結果 78
5.4.1量化分析 78
5.4.2硬體模擬結果 79
第六章 結論 82
參考文獻 83
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