1、畢 業 設 計（論 文）外 文 參 考 資 料 及 譯 文譯文題目： 一個新的協作頻譜感知算法認知無線電網絡 學生姓名： 學號： 專業： 通信工程 所在學院： 龍蟠學院 指導教師： 田甜 職稱： 講師 2011年 12月 1日說明：要求學生結合畢業設計（論文）課題參閱一篇以上的外文資料，并翻譯至少一萬印刷符（或譯出3千漢字）以上的譯文。譯文原則上要求打印（如手寫，一律用400字方格稿紙書寫），連同學校提供的統一封面及英文原文裝訂，于畢業設計（論文）工作開始后2周內完成，作為成績考核的一部分。 A New Cooperative Spectrum Sensing Algorithmfor Cog

2、nitive 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 se

3、nsing 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 rep

4、ort its sensing result. Simulation results show that our algorithm achieves better sensing performance and the average number of sensing bits decrease greatly.Keywordscognitive radio; cooperative spectrum sensing; double threshold; reputation. INTRODUCTION Due to the increasingly development of wire

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

6、utilization, cognitive radio technology was recently proposed 2, 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

7、primary 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 hid

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

9、 its sensing 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 decision

10、s to the 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 r

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

12、 the conventional method. The rest of the paper is organized as follows. In section , system model is briefly introduced. Sensing performance is analyzed in Section . In Section , we present the simulation results of our cooperative spectrum sensing method. Finally, we draw our conclusions in Sectio

13、n .II. SYSTEM MODEL In 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 accuracy.

14、 The essence of spectrum sensing is a binary hypothesis-testing problem:primary user is absent;:primary user is present. For implementation simplicity, we restrict ourselves to energy detection in the spectrum sensing. The local spectrum sensing is to decide between the following two hypotheses: (1)

15、 Where is the signal received by secondary user, is primary users transmitted signal,is AWGN, and is the temporary amplitude gain of the channel. According to energy detection theory 7, we have the following distribution: (2) Where is the energy value collected by secondary user, is instantaneous SN

16、R and follows exponentially distribution with the mean value , is the time bandwidth product of the energy detector,represents a central chi-square distribution with 2m degrees of freedom and. represents a non-central chi-square distribution with degrees of freedom and a non-centrality parameter . I

17、n conventional energy detection method, the local (a). When the collected energy exceeds the threshold , decision will be made. Otherwise decision will be made. In contrast, the system model which has two thresholds of our interest is shown inFig.1 (b). Where “ Decision ” and “Decision ” represent t

18、he absence and the presence of licensed user, respectively.“No decision” means that the observation is not reliable enough and the th cognitive user will send nothing to the common receiver. But when all the secondary users dont send their local decisions, only the cognitive user with the highest re

19、putation is selected to sense spectrum based on conventional energy detection method, and send its local decision to the common receiver. Reputation is obtained based on the accuracy of cognitive users sensing results. The reputation value is set to zero at the beginning. Whenever its local spectrum

20、 sensing report is consistent with the final sensing decision, its reputation is incremented by one; otherwise it is decremented by one. Under this rule, assuming the th cognitive users reputation value is 1, the last sensing report of cognitive user send to common receiver is , and the final decisi

21、on is ,then is updated according to the following relation: For the cognitive radio users with the energy detector, the average probabilities of detection, the average probabilities of missed detection, and the average probabilities of false alarm over AWGN channels are given, respectively, by 7: (3

22、) (4) (5) Where , are complete and incomplete gamma function respectively, and is the generalized Marcum function. In this paper, we consider cooperative spectrum sensing with 1bit quantization. Let represent the normalized D=0 D=1(a)(b)0 D=0 D=1ND0Fig1. (a)Conventional detection method (b)Double th

23、reshold energy detection methodaverage number of sensing bit. Let and represent he event that there are K unlicensed users reporting 1-bit decision and N-K users not reporting to the common receiver, respectively. The , .and then the average number of sensing bits for our method can be derived as: （

24、6）For simplicity, we define: ， （7）Let denote the normalized average number of sensing bits, then, we obtain as follows： （8）From (8), It can be seen that, the normalized average number of sensing bits is always smaller than 1. the communication traffic of our method is are deduced as opposed to the c

25、onventional energy detection method.III. THE PERFORMANCE ANALYSIS OF SPECTRUM SENSINGIn this section, the spectrum sensing performance of the proposed method will be analyzed. Assume the control channel between the unlicensed users and the common receiver is perfect, the local decisions are reported

26、 without any error. Let and denote the cumulative distribution function (CDF) of the local test statistic under the hypothesis and , respectively. Then, we have 10: (9) (10)Obviously,，.If no any local decision is reported to the common receiver, i.e., K=0 , we call that fail sensing. For this case,

27、the common receiver will request the user which has the highest reputation to send its local decision based on conventional energy detection method. Let and denote the probability of fail sensing under hypothesis and , respectively. Here we have: (11) (12)Apparently, and .In our scheme, the false al

28、arm probability ,the detection probability,and the missing probability : (13) = (14) (15)For simplicity, we assume the channel between the unlicensed users and the base station are ideal, the local decision will be reported without any error. So stand for the probability of the event that under hypo

29、thesis , all the K users claim and other N-K users make no local decisions. = = （16） （17） （18） （19）IV. SIMULATION RESULTSIn this section, some simulation results are presented to illustrate the system performance of our cooperative spectrum sensing algorithm based on reputation. The results of the c

30、onventional one threshold energy detection method are also shown for a comparison. In our simulation, the common simulation parameters are given as follows: Table 1. Simulation parametersFig.2 depicts the performance of cooperative spectrum sensing and .It can be observed that, compared it with the

31、conventional method, the detection performance has improved significantly. For example, while = 0.001, our method achieves extra 0.019 detection probability. Fig.3 shows the decrease of the normalized transmission bits for different values of fail sensing, i.e. = 0, 0.001, 0.01, 0.1. Compared with c

32、onventional method, i.e., when = 0, the normalized average number of sensing bits is dramatically decreased and bandwidth limited problem of the reporting channel is relieved. For example, when = 0.01, almost 44% and 38% reduction of the normalized average number of sensing bits can be obtained for

33、= 0.001 and = 0.01, respectively. In our algorithm, is upper bounded and lower bounded because of the probability of fail sensing and the false alarm probability are based on (7), (13).Fig 2.vs., Fig 3.vs.,=V. CONCLUSIONIn this paper, a new scheme in cooperative spectrum sensing for cognitive radio

34、networks under bandwidth constraints was proposed. In our method, only the secondary users with reliable information are allowed to report their sensing results. When no user has reliable information, only he secondary user with highest reputation will report its sensing result. We analyzed the clos

35、ed expression for the probability of the detection and the false-alarm. From the preliminary simulation results, we demonstrated the average number of sensing bits decrease greatly and the sensing performance is also improved.REFERENCES1 Federal Communications Commission. Spectrum Policy Task Force,

36、 Rep. ET Docket no. 02-135 R. Nov. 2002.2 J. Mitola and G. Q. Maguire. Cognitive radio: Making software radios more personalC,IEEE Personal Communication. vol. 6, pp. 1318, Aug. 1999.3 S. Haykin. Cognitive radio: brain-empowered wireless communications J. IEEE J. Sel. Areas Communication. vol. 23, p

37、p. 201220, 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 cognitive radiosC/ in Proc. Of A silo

38、mar 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 in fading environmentsC/ in Proc. 1st IEEES ymp. New Frontiers in Dynamic Spectrum Access Networks, Baltimore, USA,

39、 Nov. 811, 2005, pp. 131136.7 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. Proceedings of IEEE, vol.55, pp. 523-5

40、31, 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 fading channelsC. in Proc. I

41、EEE ICC, Anchorage, AK, USA, May 11-15, 2003, pp. 35753579. 譯文：摘要頻譜遙感是一個關鍵階段構建認知無線電網絡。然而，帶寬報告認知用戶的檢測結果是不夠的，當一些次要用戶非常大。首先每個認知用戶基于雙檢測門限獨立進行頻譜感知，但只有部分可靠的認知用戶通過控制信道向認知無線網絡基站發送本地感知結果。當所有的用戶都不可靠時，選取信任度最高的認知用戶發送本地感知結果進行判決。理論分析和仿真表明，同常規能量檢測算法相比較，該算法能夠在控制信道帶寬受限條件下，以較少的網絡開銷獲得更好的頻譜感知性能。關鍵詞：認知無線電；頻譜感知；信任度；雙門限1引

42、言隨著無線通信技術的飛速發展，有限的頻譜資源與不斷增長的無線通信需求的矛盾越來越突出。然而根據現有的固定分配頻譜資源策略，絕大多數頻譜資源得不到有效利用。據FCC 的調查統計，70%的已分配頻譜資源沒有得到有效利用。為了提高頻譜資源的利用率，認知無線電技術由Joseph Mitola 提出并得到了廣泛的關注。頻譜感知技術是認知無線電網絡的支撐技術之一。通常它又可以分為能量檢測法、匹配濾波器法和循環平穩特征法4。能量檢測算法因為應用簡單且無需知道任何授權用戶信號的先驗知識成為研究熱點。認知用戶在接入授權頻帶之前，必須首先感知該頻帶空閑即授權用戶沒有工作，否則會對授權用戶造成干擾。一旦授權用戶重新

43、工作，認知用戶必須退避，實現在不對授權用戶產生干擾的情況下對頻譜資源的共享。由于實際信道中的多徑和陰影效應，單個認知用戶頻譜感知的性能并不樂觀，針對這個問題D. Cabric等人提出了協同頻譜感知算法5-6。協同頻譜感知算法性能較好，但是當認知用戶數量很大的時候，控制信道的帶寬將不夠用。文獻7中提出了一種在控制信道帶寬受限條件下的基于雙檢測門限的頻譜感知算法，該算法能夠以較小的網絡開銷，獲得接近普通單門限頻譜檢測算法的性能。針對認知無線電頻譜感知的需要，本文提出了認知無線電環境下一種基于信任度的雙門限協同頻譜感知算法。該算法中每個認知用戶基于雙檢測門限獨立進行頻譜感知，但只有部分可靠的認知用戶

44、通過控制信道向認知無線網絡基站發射感知報告。當所有的用戶都不可靠時，選取信任度最高的認知用戶發射感知報告進行判決。本文對該算法進行了性能分析并通過仿真表明，本文方法比較常規能量檢測算法，在減小網絡開銷的同時提高了檢測性能。2系統模型假設一個認知無線電網絡有N個認知用戶和一個認知無線網絡基站，如圖1 所示。認知無線網絡基站負責管理和聯系N個認知用戶，在收到認知用戶的檢測報告后做出最終判決。頻譜感知的實質是一個二元假設問題，即 （1）其中x(t)代表認知用戶接收到的信號，s(t)表示授權用戶的發送信號，h(t)代表授權用戶與認知用戶之間信道的衰落因子。代表授權用戶沒有工作，代表授權用戶正在工作。設

45、是認知用戶接收信號的能量，根據能量檢測理論8，服從以下分布： （2）其中表示瞬時信噪比，并且其服從均值為的指數分布，表自由度為2m的中心卡方分布，代表自由度為非中心參數為的卡方分布，表示時間帶寬積。在能量檢測算法本地判決中，每個認知用戶把接收到的能量跟預設的門限進行比較，如圖2（a）所示。當時，本地能量檢測器做出本地判決，表示授權用戶在工作，否則判決 D 為 0。而雙門限能量檢測算法本地判決如圖3(b)所示，本地能量檢測器判決規則如下： （3）其中ND表示認知用戶接受到的能量值不可靠，認知用戶不作出任何判決，發送感知報告給認知無線電網絡基站。如果出現所有認知用戶都不作出判決的情況，則選擇信用度

46、最高的認知用戶依據單門限能量檢測算法作出本地判決。并發送感知報告給認知無線電網絡基站。本地判決D=0本地判決D=1(a)(b)0本地判決D=0本地判決D=1ND0 圖2.（a）一般能量檢測算法本地判決示意圖 （b）雙門限能量檢測算法本地判決示意圖信用度獲取方法采取文獻9的方法：在最開始階段，認知無線電網絡基站把每個認知用戶數目的可信度設為0，當某認知用戶本地判決結果與認知無線電網絡基站的最終判決結果一致時，該認知用戶可信度加1，否則減1。假設認知用戶i的可信度是，則其更新過程如（4）： （4）其中是認知用戶傳送給認知無線電網絡基站的判決結果，是認知無線電網絡基站的最終判決結果。據文獻8可知，認

47、知用戶在高斯信道下的平均檢測概率、平均漏檢概率和平均虛警概率如下所示： (5) (6) (7)出于對授權用戶的保護，認知無線電網絡基站最終采用OR準則作出判決。3頻譜感知性能分析在1bit量化條件下，代表歸一化平均感知位數，和分別代表K個已向認知無線電網絡基站發送數據和N-K個未向認知無線電網絡基站發送報告。則：，。設和，則劃歸一劃平均感知位數如式8所示： (8)定義：， 則： (9)由9式可得：可知：基于雙門限的協同頻譜檢測算法的網絡開銷始終小于常規的能量檢測算法。設和別表示在假設和下的概率分布，則根據文獻10可知: (10)= (11)顯然，。假設，分別代表在授權用戶在工作和授權用戶未工作

48、情況下沒有認知用戶發送感知報告，即當K=0時，則： (12) (13) 基于雙門限的頻譜感知算法在瑞利信道下的虛警概率，漏檢概率和檢測概率分別為： (14)= (15) (16)其中： = = (17) (18)則： (19) (20) 由上式可知當=0時，此算法與常規算法相同。當參與協同的認知用戶數目N較大時，則基于雙門限的頻譜檢測算法的檢測性能與常規能量算法的檢測性能近似，可知在控制信道帶寬受限制的情況下以較小的性能損失大大降低了網絡開銷。4 仿真及分析本節通過計算機仿真來評估所提出的基于信任度的雙門限協同頻譜感知算法的性能。仿真參數設置如表1 所示。表1 仿真參數設置數值圖3 給出了在的

49、情況下算法的檢測性能。可以看出同常規能量檢測算法相比較，本文所提出算法的檢測性能得到了明顯的改善。例如當時，基于信任度的雙門限協同頻譜感知算法的檢測概率比常規能量檢測算法高出。圖3檢測性能示意圖圖4 描述了在不同的條件下，基于信任度的雙門限協同頻譜感知算法對網絡開銷的影響。同常規能量檢測算法即=0時相比較，本文所提出算法的歸一化平均感知位數急劇下降，控制信道帶寬與認知用戶數量之間的矛盾得到了緩解。例如當，= 0.01 時，基于信任度的雙門限協同頻譜感知算法的歸一化平均感知位數下降了38%。當，時，歸一化平均感知位數則下降了44%圖4 不同條件下算法對網絡開銷的影響5結束語頻譜感知技術是認知無線

50、電網絡的支撐技術之一。當認知用戶數量很大的時候，控制信道的帶寬將不夠用。本文提出了認知無線電環境下一種基于信任度的雙門限協同頻譜感知算法。每個認知用戶基于雙檢測門限獨立進行頻譜感知，但只有部分可靠的認知用戶通過控制信道向認知無線網絡基站發射感知報告。當所有的用戶都不可靠時，選取信任度最高的認知用戶發射感知報告進行判決。本文對該算法進行了性能分析并通過仿真表明，本文方法比較常規能量檢測算法，在減小網絡開銷的同時提高了檢測性能。參考文獻 1聯邦通信委員會。頻譜政策專責小組，代表等02-135摘要號碼 M 。11月2002。 2J .mitola和克馬奎爾。認知無線電：軟件無線電多個人文集 M ，個

51、人通信。6卷，13頁18，1999。 3赫金。認知無線電與協同通信M 。美國學者選擇。地區通信。23卷，201頁220，2月2005。 4akyldiz如果。下一代/動態頻譜接入/認知無線電無線網絡：一項調查M 。愛思唯爾計算機網絡，2006（50）：2127-2159。 5D .cabric，S . M .米斯拉，和R .W .布羅德森。執行問題在認知無線電頻譜檢測 J/過程中。一個silomar比較信號，系統，和電腦，太平洋格羅夫，加利福尼亞州，美國，11月7，2004，頁772 -776。 6A加斯米和E . S .索薩。協作頻譜感知機會進入衰落環境 J /過程中。第一ieees項目實施

52、。動態頻譜接入網絡前沿，巴爾的摩，美國，十一月八日11，2005，pp . 131136。 7淳化太陽，張衛，letaief英國高等法院的認知無線電協作頻譜檢測帶寬限制下的 J /過程中。美國wcnc，3月15，2007，頁1 - 5。 8H .urkowitz。未知確定性信號能量檢測 J。程序，vol.55，523-531頁，四月1967。 9人民陳，jung-min公園，開貴邊。強大的分布式認知無線電網絡中的頻譜檢測 J。在過程中。四月ieeeinfocom，2008，頁1876-1884。 10F .F .digham，M-Salouini，和M .K .西蒙。基于能量檢測未知信號衰落信

53、道 D。在過程中。國際刑事法院，錨固，正義與發展黨，美國，可能較大，2003，頁3575 -3579。原文已完。下文為附加文檔，如不需要，下載后可以編輯刪除，謝謝！施工組織設計本施工組織設計是本著“一流的質量、一流的工期、科學管理”來進行編制的。編制時，我公司技術發展部、質檢科以及項目部經過精心研究、合理組織、充分利用先進工藝，特制定本施工組織設計。工程概況：西夏建材城生活區27#、30#住宅樓位于銀川市新市區，橡膠廠對面。本工程由寧夏燕寶房地產開發 開發，銀川市規劃建筑設計院設計。本工程耐火等級二級，屋面防水等級三級，地震防烈度為8度，設計使用年限50年。本工程建筑面積:27#m2;30#

54、m2。室內地坪 m為準，總長27#m；30# m。總寬27#m；30# m。設計室外地坪至檐口高度18.6 00m，呈長方形布置，東西向，三個單元。本工程設計屋面為坡屋面防水采用防水涂料。外墻水泥砂漿抹面，外刷淺灰色墻漆。內墻面除衛生間200300瓷磚，高到頂外，其余均水泥砂槳罩面，刮二遍膩子；樓梯間內墻采用50厚膠粉聚苯顆粒保溫。地面除衛生間200200防滑地磚，樓梯間50厚細石砼1：1水泥砂漿壓光外，其余均采用50厚豆石砼毛地面。樓梯間單元門采用樓宇對講門，臥室門、衛生間門采用木門，進戶門采用保溫防盜門。本工程窗均采用塑鋼單框雙玻窗，開啟窗均加紗扇。本工程設計為節能型住宅，外墻均貼保溫板。

55、本工程設計為磚混結構，共六層。基礎采用C30鋼筋砼條形基礎，上砌MU30毛石基礎，砂漿采用M10水泥砂漿。一、二、三、四層墻體采用M10混合砂漿砌筑MU15多孔磚；五層以上采用M混合砂漿砌筑MU15多孔磚。本工程結構中使用主要材料：鋼材： = 1 * ROMAN I級鋼， = 2 * ROMAN II級鋼；砼：基礎墊層C10，基礎底板、地圈梁、基礎構造柱均采用C30，其余均C20。本工程設計給水管采用PPR塑料管，熱熔連接；排水管采用UPVC硬聚氯乙烯管，粘接；給水管道安裝除立管及安裝IC卡水表的管段明設計外，其余均暗設。本工程設計采暖為鋼制高頻焊翅片管散熱器。本工程設計照明電源采用BV銅芯線

56、，插座電源等采用BV4銅芯線；除客廳為吸頂燈外，其余均采用座燈。施工部署及進度計劃1、工期安排本工程合同計劃開工日期：2004年8月21日，竣工日期：2005年7月10日，合同工期315天。計劃2004年9月15日前完成基礎工程，2004年12月30日完成主體結構工程，2005年6月20日完成裝修工種，安裝工程穿插進行，于2005年7月1日前完成。具體進度計劃詳見附圖1（施工進度計劃）。2、施工順序 = 1 * GB2 基礎工程工程定位線（驗線）挖坑釬探（驗坑）砂礫墊層的施工基礎砼墊層刷環保瀝青 基礎放線（預檢）砼條形基礎刷環保瀝青 毛石基礎的砌筑構造柱砼地圈梁地溝回填工。 = 2 * GB2

57、 結構工程結構定位放線（預檢）構造柱鋼筋綁扎、定位（隱檢）磚墻砌筑（50cm線找平、預檢）柱梁、頂板支模（預檢）梁板鋼筋綁扎（隱檢、開盤申請）砼澆筑下一層結構定位放線重復上述施工工序直至頂。 = 3 * GB2 內裝修工程門窗框安裝室內墻面抹灰樓地面門窗安裝、油漆五金安裝、內部清理通水通電、竣工。 = 4 * GB2 外裝修工程外裝修工程遵循先上后下原則，屋面工程（包括煙道、透氣孔、壓頂、找平層）結束后，進行大面積裝飾，塑鋼門窗在裝修中逐步插入。施工準備現場道路本工程北靠北京西路，南臨規劃道路，交通較為方便。場內道路采用級配砂石鋪墊，壓路機壓。機械準備 = 1 * GB2 設2臺攪拌機，2臺水

58、泵。 = 2 * GB2 現場設鋼筋切斷機1臺，調直機1臺，電焊機2臺，1臺對焊機。 = 3 * GB2 現場設木工鋸，木工刨各1臺。 = 4 * GB2 回填期間設打夯機2臺。 = 5 * GB2 現場設塔吊2臺。3、施工用電施工用電已由建設單位引入現場；根據工程特點，設總配電箱1個，塔吊、攪抖站、攪拌機、切斷機、調直機、對焊機、木工棚、樓層用電、生活區各配置配電箱1個；電源均采用三相五線制；各分支均采用鋼管埋地；各種機械均設置接零、接地保護。具體配電箱位置詳見總施工平面圖。施工用水施工用水采用深井水自來水，并砌筑一蓄水池進行蓄水。樓層用水采用鋼管焊接給水管，每層留一出水口；給水管不置蓄水池

59、內，由潛水泵進行送水。生活用水生活用水采用自來水。勞動力安排 = 1 * GB2 結構期間：瓦工40人；鋼筋工15人；木工15人；放線工2人；材料1人；機工4人；電工2人；水暖工2人；架子工8人；電焊工2人；壯工20人。 = 2 * GB2 裝修期間抹灰工60人；木工4人；油工8人；電工6人；水暖工10人。四、主要施工方法1、施工測量放線 = 1 * GB2 施工測量基本要求A、西夏建材城生活區17#、30#住宅樓定位依據：西夏建材城生活區工程總體規劃圖，北京路、規劃道路永久性定位B、根據工程特點及建筑工程施工測量規程DBI012195，4、3、2條，此工程設置精度等級為二級，測角中誤差12，

60、邊長相對誤差1/15000。C、根據施工組織設計中進度控制測量工作進度，明確對工程服務，對工程進度負責的工作目的。 = 2 * GB2 工程定位A、根據工程特點，平面布置和定位原則，設置一橫一縱兩條主控線即27#樓：（A）軸線和（1）軸線；30#樓：（A）軸線和（1）軸線。根據主軸線設置兩條次軸線即27#樓：（H）軸線和（27）軸線；30#樓：（H）軸線和（27）軸線。 B、主、次控軸線定位時均布置引樁，引樁采用木樁，后砌一水泥砂漿磚墩；并將軸線標注在四周永久性建筑物或構造物上，施測完成后報建設單位、監理單位確認后另以妥善保護。C、控軸線沿結構逐層彈在墻上，用以控制樓層定位。D、水準點：建設單