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姓名 劉家煜(Chia-yu Liu)  查詢紙本館藏   畢業系所 資訊工程學系在職專班
論文名稱 一個在感知無線電中利用PHY error來偵測PU的方法
(A PHY error-based PU detection scheme for Cognitive Radio networks)
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摘要(中) 近年來由於無線通訊技術的快速發展與普及,固定式的頻譜資源分配方法造成了頻譜使用率不佳的問題。感知無線電網路(Cognitive radio network, CRN)是一種動態頻譜存取技術 (Dynamic Spectrum Access, DSA),能夠在不干擾 PU (Primary user) 的情況下讓 SU (Secondary user) 去使用尚未被PU使用到的頻譜,當 PU要使用頻譜的時候,SU會迅速的離開目前使用的頻譜,並切換到其它可以使用的頻譜繼續進行傳輸,藉以改善無線頻譜的使用率。在感知無線電網路中 PU偵測是一項相當重要的功能,當PU存在時但是 SU 卻沒有偵測到,會干擾到PU的傳輸,當PU不存在但是SU卻誤認為 PU 存在時,則會造成頻譜使用率不佳。
目前常用來實作感知無線電的硬體平台的有三種:USRP [1][2][3]、KNOWS[4]及 SpiderRadio[5] [6],KNOWS 與SpiderRadio都使用 Atheros 無線網路卡來實作感知無線電網路,原因是因為目前只有Atheros 的無線網路晶片有提供Linux 開放原始碼的驅動程式- MADWIFI可以修改,在三種平台中 SpiderRadio 只有使用Atheros 無線網路卡及PC來實作感知無線電,因此是硬體成本最便宜的平台。
目前感知無線電網路中常用的PU偵測方法有三種:分別為能量偵測 (Energy detection)、匹配濾波器偵測 (Matched filter detection)、訊號特徵偵測(Feature detection)[6],但是Atheros 的硬體只支援能量偵測,而且這個功能被封裝在硬體上,無法MADWIFI 驅動程式去執行能量偵測。當Atheros 硬體接收到的IEEE 802.11封包中的 Preamble 有錯誤時,就會回報PHY error 的訊息給MADWIFI 驅動程式。文獻[13] 在實驗中發現,當PU訊號存在時Atheros 硬體會產生PHY error與CRC error,因此在 Atheros 硬體上實作PU偵測時會使用PHY error或是CRC error 來進行PU偵測。
PB42是一個Atheros的嵌入式系統平台,PB42的優點是移動性較高、成本低、體積、耗電量也小但是運算速度慢,由於嵌入式系統平台的軟硬體限制,SpiderRadio 偵測 PU時所使用的計算方法不適合使用在嵌入式系統平台,我們進行了一些實驗來觀察PHY error 的特性,並針對嵌入式系統平台提出了使用更簡單並有效的方法來實作PU的偵測。
摘要(英) Due to the fast development and wide spread of wireless communication technology in recent years, the current method of resource allocation cause poor utilization of spectrum. Cognitive Radio Network (CRN) is one of Dynamic Spectrum Access (DSA), which allows SU (Secondary User) using spectrums not being used by PU (Primary User). In order to improve utilization of spectrums, SU would leave current spectrum rapidly and switch to other usable spectrum to continue the transmission due to the presence of primary users. PU sensing is an important function in Cognitive Radio Network (CRN). When SU does not detect the presence of PU, SU would interfere the transmission of PU. When SU detected PU but it was absent, SU would cause poor utilization of spectrums.
Currently there are three types of hardware platforms of Cognitive Radio that are commonly used, which are USRP [1][2][3], KNOWS[4], and SpiderRadio[5]. Both KNOWS and SpiderRadio use Atheros wireless adapter and PC to implement Cognitive Radio Network (CRN). This is because currently only Atheros wireless adapter provides Linux open source driver - MADWIFI. Among the three platforms, SpiderRadio is the one that entirely uses Atheros wireless adapter to implement CRN. Therefore, it is the cheapest platform in hardware costs.
There are three commonly-used methods of PU sensing in CRN, which are Energy detection, Matched filter detection, and Feature detection. However, the hardware of Atheros can only support Energy detection and this function is implemented in hardware, there is no way to get modified. When Atheros receives error of Preamble in IEEE 802.11 Packet, it would report a “PHY error” and “CRC error” to MADWIFI driver. The finding in the experiment of recent research [13] shows that when PU signal presents, Atheros hardware would report “PHY error”. Hence, it uses “PHY error” to sense PU in Atheros hardware platform.
PB42 is an embedded system of Atheros, the advantages of PB42 are high movement, low cost, small size and low power consumption but low computation speed. Due to restrictions of hardware and software in embedded systems, PU detection scheme of SpiderRadio is not suitable in embedded system platform. We conducted several experiments to observe the characteristics of PHY error and we focused on more simple and effective method to implement PU detection in embedded system.
關鍵字(中) ★ 感知無線電
★ 嵌入式系統
★ PU感測
關鍵字(英) ★ Cognitive Radio Networks
★ IEEE 802.11
★ Embedded system
★ PU sensing
論文目次 Chapter 1 Introduction 1
Chapter 2 Related Work 4
2.1 USRP 4
2.2 KNOWS 5
2.3 SpiderRadio 5
Chapter 3 PHY-based PU detection scheme implementation 8
3.1 PHY/CRC Error observation setup 9
3.2 PHY/CRC Error number observation 10
3.3 PHY/CRC Error observation with moving average 13
3.4 PHY/CRC Error threshold with moving average and multiple 15
3.5 Hardware development environment 17
3.6 Software development environment 17
3.7 CR Network Model 19
Chapter 4 Experiment 20
4.1 SpiderRadio 20
4.2 PB42 Implementation 23
Chapter 5 Experiment Evaluation 26
Chapter 6 Conclusions 28
Reference 29
參考文獻 [1] T. W. Rondeau, C. J. Rieser, B. Le, and C. W.Bostian, "Cognitive Radios with Genetic Algorithms: Intelligent Control of Software Defined Radios," in SDR Forum Technical Conference, Phoenix, 2004.
[2] C. R. Rieser, Thomas W. Rondeau, Charles W. Bostian, and Timothy M. Gallagher, "Cognitive Radio Testbed: Further Details and Testing of a Distributed Genetic Algorithm Based Cognitive Engine for Programmable Radios." in MILCOM 2004.
[3] D. Scaperoth, B. Le, T. Rondeau, D. Maldonado, C.W. Bostian, S. Harrison, “Cognitive Radio Platform Development for Interoperability”, in MILCOM 2006.
[4] Y. Yuan, P. Bahl, R. Chandra, P. Chou, J. Ferrell, T. Moscibroda, S. Narlanka, and Y. Wu, “Knows: Cognitive radio networks over white spaces,” in IEEE DySPAN, 2007.
[5] Kai Hong, Sengupta, S., Chandramouli, R., " SpiderRadio: A Cognitive Radio Implementation using IEEE 802.11 Components," in Mobile Computing, IEEE Transactions on 2012.
[6] Kai Hong, Sengupta, S., Chandramouli, R., "SpiderRadio: An incumbent sensing implementation for cognitive radio networking using IEEE 802.11 devices," in ICC, 2010.
[7] Paramvir Bahl, Ranveer Chandra, Thomas Moscibroda, Rohan Murty, Matt Welsh, "White space networking with wi-fi like connectivity," in ACM SIGCOMM 2009.
[8] J. Mitola, “The software radio architecture,” in IEEE Commun. Mag., 1995.
[9] FCC press release, FCC Adopts Rules for Unlicensed Use of Television White Spaces. November 2008.
[10] Kyouwoong Kim et al., "Cyclostationary Approaches to Signal Detection and Classification in Cognitive Radio," in DySPAN, 2007.
[11] Zhengwei Lu, Yi Ma, and R. Tafazolli, "A first-order cyclostationarity based energy detection approach for non-cooperative spectrum sensing ," in PIMRC, 2010.
[12] S. Narlanka, R. Chandra, P. Bahl, and I. Ferrell, "A Hardware Platform for Utilizing the TV Bands with a Wi-Fi Radio," in IEEE LANMAN, 2007.
[13] K. Shin, H. Kim, C. Cordeiro, and K. Challapali, “An experimental approach to spectrum sensing in cognitive radio networks with off-theshelf ieee 802.11 devices,” in IEEE CCNC, 2007.
[14] AR5213 Multiprotocol MAC/Baseband Processor for 5GHz and 2.4GHz Wireless LANs Advanced Data Sheet.
[15] “IEEE standard for information technology - Telecommunications and
Information exchange between systems - Local and Metropolitan area
[16] Networks-Specific requirements - Part 11: Wireless Lan medium access
control (MAC) and physical layer(PHY) specifications, ” 2007.
指導教授 張貴雲(Guey-yun Chang) 審核日期 2013-8-21
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