通信工程毕业设计的论文外文翻译一个新的协作频谱感知算法认知无线电络

1、鱼陂科扶學院毕业设计（论文）外文参考资料及译文译文题目： 一个新的协作频谱感知算法认知无线电网络学生姓名：学 号：专 业：通信工程所在学院：龙蟠学院指导教师：田甜职 称：讲师2011年 12 月 1 日说明：要求学生结合毕业设计（论文）课题参阅一篇以上的外文资料， 并翻译至少一万印刷符（或译出 3千汉字）以上的译文。译文原则上 要求打印（如手写，一律用 400 字方格稿纸书写），连同学校提供的 统一封面及英文原文装订，于毕业设计（论文）工作开始后 2周内完 成，作为成绩考核的一部分。A New Cooperative Spectrum Sensing Algorithmfor Cognitiv

2、e Radio NetworksAbstractspectrum sensing is a critical phase in building a cognitive radio network. However, the bandwidth for reporting secondary users sensing results will be insufficient, when the number of secondary user is very large. In this paper, we propose a new cooperative spectrum sensing

3、 algorithm to alleviate the bandwidth problem of reporting channel. Compared with conventional method, only the secondary users with reliable information are allowed to report their sensing results. When no user with reliable information, only the secondary user with highest reputation will report i

4、ts sensing result. Simulation results show that our algorithm achieves better sensing performance and the average number of sensing bits decrease greatly.Keywords cognitive radio; cooperative spectrum sensing; double threshold; reputationI . INTRODUCTIONDue to the increasingly development of wireles

5、s applications, more and more spectrum resources are needed to support numerous emerging wireless service. However, recent measurements by Federal Communication Commission (FCC) have 1shown that 70% of the allocated spectrum in US is not utilized . In order to increase the efficiency of spectrum uti

6、lization, cognitive radio technology was recently proposed2, 3.A requirement of cognitive radios is that their transmission should not cause harmful interference to primary users. Namely, the secondary users can use the licensed spectrum as long as the primary user is absent. However, when the prima

7、ry user comes back into operation, the secondary users should vacate the spectrum instantly to avoid interference with the primary user. Accordingly, spectrum sensing is a crucial phase in building a cognitive radio system.One of the great challenges of implementing spectrum sensing is the hidden te

8、rminal problem which caused by the fading of the channels and the shadowing effects. In order to deal with the hidden terminal problem, cooperative spectrum 4, 5.sensing has been studied to improve the spectrum sensing performance In6, due to control channel for each cognitive radio to report its se

9、nsing result is usually bandwidth limited, a censoring method which has two thresholds is given to decrease the average number of sensing bits to the common receiver. By censoring the collected local observations, only the secondary users with enough information will send their local decisions to th

10、e common receiver.In this paper, we present a new double threshold cooperative spectrum sensing method with reputation. In our system, every cognitive user will firstly obtain an observation independently and only the users with reliable information send their local decisions to the common receiver

11、based on double thresholds. If no user is reliable, only the cognitive user with the highest reputation is selected to sensethe spectrum. Simulation results show that the spectrum sensing performance under AWGN channels is improved and the communication traffic is also reduced as opposed to the conv

12、entional method.The rest of the paper is orga ni zed as follows. In sect ion n , system model is briefly in troduced. Sensing performa nee is an alyzed in Secti on 川.In Sectio n IV, we present the simulation results of our cooperative spectrum sensing method. Finally, we draw our conclusions in Sect

13、ion V .II. SYSTEM MODELIn cognitive radio systems, spectrum sensing is a critical element as it should be firstly performed before allowing secondary users to access a vacant licensed channel. Cooperative spectrum sensing has been widely used to detect the primary user with a high agility and accura

14、cy. The esse nee of spectrum sensing is a binary hypothesis-testi ng problemH0 :primary user is abse nt;H1:primary user is prese nt.For implementation simplicity, we restrict ourselves to energy detection in the spectrum sensing. The local spectrum sensing is to decide betwee n the followi ng two hy

15、potheses:(1)x(t)(t),H0lh(t) s(t)+ n(t),H1Where x(t) is the sig nal received by sec on dary user, s(t)is primary user s transmitted signal,n(t) is AWGN, and h(t) is the temporary amplitude gain of the cha nn el.Accord ing to en ergy detecti on theory 7, we have the followi ng distributi on:XL, HeX2m(

16、 ), HiWhere is the en ergy value collected by sec on dary user,is in sta ntan eousSNR and follows exponentially distribution with the mean value, m is the time2bandwidth product of the energy detector, 2m represents a central chi-square distribution with 2m degrees of freedom and. ；m( ) represents a

17、 non-central chi-square distribution with 2m degreesof freedom and a non-centrality parameter 2 .In conven ti onal en ergy detect ion method, the local decisi on is made by comparing the observation with a pre-fixed threshold as Fig.1 (a). When the collected energy 二 exceeds the threshold , decision

18、 H 0 will be made. Otherwise decision H1 will be made. In contrast, the system model which has two thresholds of our interest is shown inFig.1 (b). Where Decision “H0 ” and “ Decision ” represent the absenee and the presenee of licensed user, respectivelyNo decision ” means that the observati on is

19、not reliable eno ugh and the i th cog nitive user will send nothing to the com mon receiver. But whe n all the sec on dary users don tend their local decisions, only the cognitive user with the highest reputation is selected to sensespectrum based on conven ti onal en ergy detect ion method, and sen

20、d its local decisi on to the com mon receiver.Reputation is obtained based on the accuracy of cognitiveuser s sensing results. The reputati on value is set to zero at the beg inning. Whe never its local spectrum sensing report is consistent with the final sensing decision, its reputation is in creme

21、 nted by one; otherwise it is decreme nted by one. Un der this rule, assu ming the i th cognitive user s repvOdtieris 1, the last sensing report of cognitive user i send to com mon receiver is u , and the final decisi on is ui ,the n i is updated according to the following relation:i :一 -i(_1)ui uFo

22、r the cog nitive radio users with the en ergy detector, the average probabilities of detect ion, the average probabilities of missed detecti on, and the average probabilities of false alarm over AWGN cha nn els are give n, respectively, bj:Pd |比)(、2 ,)(3)Rn = p(d|Hi) =1 - Pd_ - (m, /2)r(m)Where (a),

23、 - (a,b) are complete and in complete gamma function respectively, and Qm(a,b) is the generalized Marcum function.In this paper, we consider cooperative spectrum sensing with ibit quantization.Let Kavg represent the normalizedD=1D=0Figi. (a)C onven tio nal detecti on method(b)Double threshold en erg

24、y detect ion methodIaverage nu mber of sensing bit.Let TK and TN _k represe nt he eve nt that there are K un lice nsed users report ing 1-bit decisi on and N-K users not report ing to the com mon receiver,respectively.ThePTk二1p(1 i ： 2)k,Kavg =PoX|HoPT“ |H。KA lK 丿PTn 上二P( h ：K ： 2)n k .and then the

25、average number of sensing bits for our method can be derived as:HiPTnHiK4 K(6)For simplicity, we defi ne:二 P(11 ： 2|Ho),L = P(1 ： 3 ： 2 |Ho)(7)Let Knavgdenote the normalized average number of sensing bits, then, we obtain Knavg as follows：Kavgi-RAo-RI(8)From (8), It can be seen that, the normalized

26、average number of sensing bitsnavg is always smaller tha n 1. the com muni cati on traffic of our method is are deduced as opposed to the conven ti onal en ergy detecti on method.III. the performance analysis of spectrumSENSINGIn this sect ion, the spectrum sensing performa nee of the proposed metho

27、d will be an alyzed. Assume the con trol cha nnel betwee n the un lice nsed users and the com mon receiver is perfect, the local decisions are reported without any error. Let F () and G( ) denote the cumulative distribution function (CDF) of the local test statistic r under the hypothesis H 0 and H1

28、, respectively. Then, we hav10:F()FL|Ho)Z - (m, /2)(9)0(m)G)= . f(r H1)d(10)0Obviously,二0 - FCJ FC?)，二G( -2G( 1).If no any local decisi on is reported to the com mon receiver, i.e., K=0 , we call that fail sensing. For this case, the com mon receiver will request the user which has the highest reput

29、ation to send its local decision based on conventional energy detect ion method. Let -0 a ndde note the probability of fail sensing un derhypothesis H 0 and H1, respectively. Here we have:=PK =0|H=(F(入 2) F(葛)N =或(11)J =PK H =(G(2)-G(r)N -叮(12)Apparently, B0and % =虜.In our scheme, the false alarm pr

30、obabilityQf ,the detection probabilityQd ,and the missing probability Qm:Qf 二 Pu =1,K _0| H0= PK _1|HPu =1|H,K -1(13)=(1)(15)Qm = Pu =0,K _0|出 =1-Qd(14)Qd 二 Pu = 1,K _ 0|比二 PK _ 1| H 1 Pu = 1| H1, K - 1(15)二(1 -aj(1 - P JFor simplicity, we assume the cha nnel betwee n the un lice nsed users and the

31、base station are ideal, the local decision will be reported without any error. So PA stand for the probability of the eve nt that un der hypothesis H 0 , all the K users claimH 0 and other N-K users make no local decisi ons.PA 二 Pu =0,K _0|出 =1_QdN *N i匹|Fa1)k(F2)-F1)zK= K 丿= F(2)N - -0( 16)Pb =G(2)

32、1(17)IV. SIMULATION RESULTSIn this sect ion, some simulatio n results are prese nted to illustrate the system performa nee of our cooperative spectrum sensing algorithm based on reputati on. The results of the conven ti onal one threshold en ergy detecti on method are also show n for a comparis on.

33、In our simulati on, the com mon simulatio n parameters are give n as follows:Table 1. Simulation parametersQd andFig.2Qf . 0 =0.1 .It can be observed that, compared it with the conventional method, the detect ion performa nce has improved sig nifica ntly. For example, while Qf = 0.001, our method ac

34、hieves extra 0.019 detection probability. Fig.3 shows the decrease of the normalized transmission bits for different values of fail sensing, i.e. 0= 0, 0.001, 0.01,0.1. Compared with conven ti onal method, i.e., whe n0 = 0, the no rmalized average number of sensing bits is dramatically decreased and

35、 bandwidth limited problem of the reporting channel is relieved. For example, when Qf = 0.01, almost 44% and 38% reduct ion of the no rmalized average nu mber of sensing bits can be obta ined for 0= 0.001 and 0 = 0.01, respectively .In our algorithm, Qf is upper bounded and lower bounded because of

36、the probability of fail sensing 0and the false alarm probability are based on (7), (13).-e o0.995oses0.9807!0.97D.S650.96Y苜观駁览栓雋甘汎畢于疽任阻的呱门限悔屈料谓感知岸法10，fFig 2.Qd vs.Qf,二 o 二 0.1Fig 3. Knavg vs.Qf , 0 =00,0.001,0.01,0.1V. CONCLUSIONIn this paper, a new scheme in cooperative spectrum sensing for cogniti

37、ve radio networks under bandwidth constraints was proposed. In our method, only the sec on dary users with reliable in formatio n are allowed to report their sensing results. When no user has reliable in formati on, on ly he sec on dary user with highest reputation will report its sensing result.We

38、an alyzed the closed expressi on for the probabilityof the detection and the false-alarm. From the preliminary simulation results, we dem on strated the average nu mber of sensing bits decreasegreatly and the sensing performa nee is also improved.REFERENCES1 Federal Communications Commission. Spectr

39、um Policy Task Force, Rep. ET Docket no. 02-135 R. Nov. 2002.2 J. Mitola and G. Q. Maguire. Cognitive radio: Making software radios more personalC,IEEE Perso nal Com mun icatio n. vol. 6, pp. 13 8, Aug. 1999.3 S. Haykin. Cognitive radio: brain-empowered wireless communications J. IEEE J. Sel. Areas

40、Com mun icati on. vol. 23, pp. 201 -220, Feb. 2005.4 AKYLDIZ IF. Next generation/dynamic spectrum access/cognitive radio wireless networks: A Survey J. ELSEVIER Computer Networks, 2006(50):2127-2159.5 D. Cabric, S. M. Mishra, and R. W. Brodersen. Implementation issues in spectrum sensing for cogniti

41、ve radiosC/ in Proc. Of A silomar Conf. on Signals, Systems, and Computers, Pacific Grove,CA, USA, Nov. 7-10, 2004, pp. 772 - 776.6 A.Ghasemi and E. S. Sousa. Collaborative spectrum sensing for opportunistic access infading environmentsC/ in Proc. 1st IEEES ymp. New Frontiers in Dynamic Spectrum Acc

42、ess Networks, Baltimore, USA, Nov. 8-1,2005, pp. 131 -36.7 Chunhua Sun, Wei Zhang, Letaief K.B. Cooperative spectrum sensing for cognitive radios under bandwidth constraintsC/ in Proc. IEEE WCNC, March 11-15, 2007, pp. 1-5.8 H. Urkowitz. Energy detection of unknown deterministic signals C. Proceedin

43、gs of IEEE, vol.55, pp. 523-531, April 1967.9 Ruiliang Chen, Jung-Min Park, Kaigui Bian. Robust Distributed Spectrum Sensing in Cognitive Radio NetworksC. in Proc. IEEEINFOCOM, April 2008, pp. 1876-1884.10 F. F. Digham, M. -S. Alouini, and M. K. Simon. On the energy detection of unknown signals over

44、 fading channelsC. in Proc. IEEE ICC, Anchorage, AK, USA, May 11-15, 2003, pp.3575-3579.译文:摘要频谱遥感是一个关键阶段构建认知无线电网络。 然而，带宽报告认知用户的 检测结果是不够的，当一些次要用户非常大。首先每个认知用户基于双检测门限 独立进行频谱感知，但只有部分可靠的认知用户通过控制信道向认知无线网络基 站发送本地感知结果。当所有的用户都不可靠时，选取信任度最高的认知用户发 送本地感知结果进行判决。理论分析和仿真表明，同常规能量检测算法相比较， 该算法能够在控制信道带宽受限条件下，以较少的网络开销获得

45、更好的频谱感知 性能。关键词：认知无线电；频谱感知；信任度；双门限1引言随着无线通信技术的飞速发展，有限的频谱资源与不断增长的无线通信需求 的矛盾越来越突出。然而根据现有的固定分配频谱资源策略，绝大多数频谱资源 得不到有效利用。据FCC的调查统计，70%的已分配频谱资源没有得到有效利用。为了提高频谱资源的利用率，认知无线电技术由Joseph Mitola川提出并得到了广泛的关注 丄5。频谱感知技术是认知无线电网络的支撑技术之一。通常它又可以分为能量检测法、匹配滤波器法和循环平稳特征法4。能量检测算法因为应用简单且无需知道任何授权用户信号的先验知识成为研究热点。认知用户在接入授权频带之前，必须首

46、先感知该频带空闲即授权用户没有工作，否则会对授权用户造成干扰。一旦授权用户重新工作，认知用户必须退避，实现在不对授权 用户产生干扰的情况下对频谱资源的共享。由于实际信道中的多径和阴影效应， 单个认知用户频谱感知的性能并不乐观，针对这个问题D. Cabric等人提出了协同 频谱感知算法5-6。协同频谱感知算法性能较好，但是当认知用户数量很大的时 候，控制信道的带宽将不够用。文献7中提出了一种在控制信道带宽受限条件下 的基于双检测门限的频谱感知算法， 该算法能够以较小的网络开销，获得接近普 通单门限频谱检测算法的性能。针对认知无线电频谱感知的需要，本文提出了认 知无线电环境下一种基于信任度的双门限

47、协同频谱感知算法。该算法中每个认知用户基于双检测门限独立进行频谱感知，但只有部分可靠的认知用户通过控制信 道向认知无线网络基站发射感知报告。 当所有的用户都不可靠时，选取信任度最 高的认知用户发射感知报告进行判决。本文对该算法进行了性能分析并通过仿真表明，本文方法比较常规能量检测算法，在减小网络开销的同时提高了检测性能2系统模型假设一个认知无线电网络有Nt认知用户和一个认知无线网络基站，如图 1 所示。认知无线网络基站负责管理和联系 N个认知用户，在收到认知用户的检测 报告后做出最终判决。频谱感知的实质是一个二元假设问题，即(1)n(t),H h(t) s(t) n(t)H其中x(t)代表认知

48、用户接收到的信号，s(t)表示授权用户的发送信号，h(t)代表授权用户与认知用户之间信道的衰落因子。 H。代表授权用户没有工作，出代表授权用户正在工作。从以下分布：设日是认知用户接收信号的能量，根据能量检测理论，日服/ 2X；m,Ho日2 ( 2) 、X；m(Y), H1其中 表示瞬时信噪比，并且其服从均值为 的指数分布，X；m表自由度为2m 的中心卡方分布，X；m()代表自由度为2m非中心参数为 的卡方分布，m表示 时间带宽积。在能量检测算法本地判决中，每个认知用户把接收到的能量二跟预设的门限进行比较，如图2 (a)所示。当二 时，本地能量检测器做出本地判决 D =1， 表示授权用户在工作，

49、否则判决 D为0。而双门限能量检测算法本地判决如图 3(b)所示，本地能量检测器判决规则如下：0,0 ： v ： 1(3)D = ND ,妇日v九21,1 吒 8 W 九 2其中ND表示认知用户接受到的能量值不可靠， 认知用户不作出任何判决，发送感知报告给认知无线电网络基站。如果出现所有认知用户都不作出判决的情况，则选择信用度最高的认知用户依据单门限能量检测算法作出本地判决。并发送感知报告给认知无线电网络基站。本地判决D=0本地判决D=1本地判决D=0ND1(b)图2. (a) 般能量检测算法本地判决示意图(b )双门限能量检测算法本地判决示意图信用度获取方法采取文献9的方法：在最开始阶段，认

50、知无线电网络基站把 每个认知用户数目的可信度设为 0,当某认知用户本地判决结果与认知无线电网 络基站的最终判决结果一致时，该认知用户可信度加1,否则减1。假设认知用户i的可信度是i，则其更新过程如(4):(4)i(-1广 u其中u是认知用户传送给认知无线电网络基站的判决结果，U1是认知无线电网络基站的最终判决结果。据文献可知，认知用户在高斯信道下的平均检测概率、平均漏检概率和平均虚警概率如下所示：Pd |HJ =QmC、2 ,)Pm 5 IH1) =1Pf 二 pU |Ho)= 5 /2)l(m)出于对授权用户的保护，认知无线电网络基站最终采用OR准则作出判决3频谱感知性能分析3.1网络开销在

51、1bit量化条件下，K avg代表归一化平均感知位数，Tk和Tn _k分别代表K个已向认知无线电网络基站发送数据和N-K个未向认知无线电网络基站发送报则：PTk =1p(Xi cd 弋爲加，PTnG =PG cd 0，则基于双门限的频谱检测算法的检测性能与常规能量算 法的检测性能近似，可知在控制信道带宽受限制的情况下以较小的性能损失大大 降低了网络开销。4仿真及分析本节通过计算机仿真来评估所提出的基于信任度的双门限协同频谱感知算法的性能。仿真参数设置如表1所示。表1仿真参数设置图3给出了在 爲=0.1的情况下算法的检测性能。可以看出同常规能量检测算法 相比较，本文所提出算法的检测性能得到了明显

52、的改善。例如当 Qf “aQI时, 基于信任度的双门限协同频谱感知算法的检测概率 Qd比常规能量检测算法高出 Q.Q19。0.95104r I n I 厂I 门7 I-I i- I- l-1-in- 厂厂门rrII I I _ILI,11 I, I常is能遇检sin沅 _T 駁于仿任瞳的叹门限晦同轲谓的知WSA0怨0.W0.965o.-er0.565?心肿一 5 - I一 N-tLm4-rL Ku _r 丄 h n-丄 -4 l-4 I J I II J I 47I4IITI4l-i_L I！1！厂I！厂I -fc J BB1 FJrBlI J厂_厂1_厂厂厂门1101图3检测性能示意图图4描

53、述了在不同1。的条件下，基于信任度的双门限协同频谱感知算法对网络 开销的影响。同常规能量检测算法即o=Q时相比较，本文所提出算法的归一化平均感知位数Kavg急剧下降，控制信道带宽与认知用户数量之间的矛盾得到了缓解。例如当Qf =Q.Q1，：Q= Q.Q1时，基于信任度的双门限协同频谱感知算法的归一化平均感知位数Kavg下降了 38%。当Qf =0.01,-0=0.001时，归一化平均感知位数Kavg则下降了 44%图4不同飞条件下算法对网络开销的影响5结束语频谱感知技术是认知无线电网络的支撑技术之一。 当认知用户数量很大的时 候，控制信道的带宽将不够用。本文提出了认知无线电环境下一种基于信任度的 双门限协同频谱感知算法。每个认知用户基于双检测门限独立进行频谱感知，但只有部分可靠的认知用户通过控制信道向认知无线网络基站发射感知报告。当所有的用户都不可靠时，选取信任度最高的认知用户发射感知报告进行判决。本文 对该算法进行了性能分析并通过仿真表明，本文方法比较常规能量检测算法，在 减小网络开销的同时提高了检测性能。参考文献1联邦通信委员会。频谱政策专责小组，代表等 02-135摘要号码M 。 11月 2002 2J .mitola 和克马奎尔。认知无线电：软件无线电多个人文集 M ，个人通信。6 卷，13 页-18, 1999。3赫金。认知