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博碩士論文 etd-0803115-004824 詳細資訊
Title page for etd-0803115-004824
論文名稱
Title
感知無線電系統之單用戶與多用戶頻譜偵測效能研究
Performance Investigation of Single-user and Multiuser detectors for Spectrum Sensing in Cognitive Radio Networks
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
76
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2015-07-24
繳交日期
Date of Submission
2015-09-03
關鍵字
Keywords
能量偵測、馬可夫鍊隨機程序、頻譜偵測、吞吐量、感知無線電
Markov chain random process, energy detection, spectrum sensing, cognitive radio, throughput
統計
Statistics
本論文已被瀏覽 5680 次,被下載 422
The thesis/dissertation has been browsed 5680 times, has been downloaded 422 times.
中文摘要
在現今的無線電管制架構下,無線電頻譜是非常稀有的資源。此外,實際頻譜使用的量測結果指出已授權頻段的寬光譜段使用率低。因此,感知無線電技術被廣泛提出來解決頻譜無法有效利用的問題。眾所周知的是感知無線電的基本概念是分享稀有的頻譜資源。動態頻譜存取技術允許感知無線電使用最佳的頻道。換句話說,在感知無線電中,次要使用者必須感測出未被占用頻道並且試著使用這些頻道傳輸,以避免干擾到主要使用者。
傳統的頻譜分享技術主要有兩個,一個是頻譜隱匿式,一個是頻譜重疊式。最近還有一個隱匿/重疊混式也被使用於分享頻譜。本論文為了分析這三個頻譜分享技術,因而提出一個聯合頻譜偵測模型。

感知無線電技術通常包含四大功能性: 頻譜偵測,頻譜決策/管理,頻譜分享與頻譜變動。
頻譜偵測技術是感知無線電的核心技術,決定市府頻帶是否閒置。在此研究中,我們主要研究的是感知無線電的頻譜偵測問題,其中系統中有一個主要使用者,多個次要使用者,還要考慮頻道間互相干擾。
這篇論文首先研究頻譜隱匿式、頻譜重疊式還有一個隱匿/重疊混和式的效能分析。並且想要比較次要使用者訊號吞吐量與主要使用者接收端受到的干擾。
另外,為了增進頻譜偵測效能,合作式頻譜偵測技術開始被研究。合作式頻譜偵測技術會利用一個融合中心收集所有本地偵測結果來做最終的頻譜偵測結果。接著我們推導並得到使用合作式頻譜偵測技術的系統效能分析。利用功率分配,合作式的頻譜偵測技術可以帶來最佳的無縣感知系統最大的訊號吞吐量。
不只有分析未使用功率分配的頻譜偵測效能,使用功率分配的頻譜偵測效能亦有所研究。
最後,我們可以分析訊號吞吐量與次要使用者個數之間的取捨問題。
Abstract
Within the current radio regulatory framework, the radio spectrum is a very scarce resource.
In addition, the actual spectrum usage measurement indicates low utilization in wide spectral ranges of licensed frequency bands.
Therefore, the cognitive radio (CR) networks scheme has been widely proposed to solve these current spectrum inefficiency problems.
It is well known that the basic idea of CR networks is to share the rare spectrum resource.
The dynamic spectrum access techniques allow the cognitive radio networks to operate in the best available channel.
In other words, in CR networks, the secondary users (SUs) have to sense the unoccupied spectrum bands and try to use them for transmission while avoiding the interference to primary users (PUs).
There are two traditional spectrum-sharing technologies called spectrum overlay and spectrum underlay.
Recently, a hybrid overlay/underlay paradigms has been proposed to discuss the spectrum sensing problems.
In analyzing the present approaches of spectrum-sharing, a unified distributed spectrum sensing model is proposed in this thesis.

The cognitive radio technology generally includes four functionalities, namely, spectrum sensing, spectrum decision/management, spectrum sharing and spectrum mobility.
The spectrum sensing technology determining whether a spectrum band is vacant arises as the heart of CR techniques.
In this study, we focus on investigating the spectrum sensing problem in CR networks where one primary channel and multiple SU pairs exist, and the co-channel interference is present.
This thesis firstly carries out the performance of overlay, underlay, and hybrid overlay/underlay paradigms, and then conducts the analysis of the throughput of SUs and the signal to interference and noise (SINR) at PUs.
%The present approaches of spectrum-sharing usually applied to CR systems are overlay (opportunistic), underlay, and hybrid overlay/underlay approach.
%The performances of the CR system with these paradigms are also combined to be analyzed using the proposed unified model.
%From the SUs' point of view, they desire to achieve high throughput which is an important attribute of CR networks and related to CR system performance.
目次 Table of Contents
1. Introduction 1
1.1. Overview of Cognitive Radio Networks 1
1.2. Literature Review on Spectrum Sensing 5
1.3. Contribution of This Thesis 8
1.4. Organization of the Thesis. 11
2. Spectrum Sensing Using A single Secondary User 12
2.1. A Unified Spectrum Sensing Model in CR Networks 14
2.2. Throughput Analysis 18
2.3. Simulation Result 24
3. Spectrum Sensing Using Multiple Secondary Users with Fusion 28
3.1. Cooperative Spectrum Sensing 28
3.2. Decision Fusion without Power Allocation 31
3.3. Decision Fusion with Power Allocation 40
4. Conclusion 49
Appendix PDF of the Test Statistic 51
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