發(fā)布時間：2018-04-04 10:57

  本文選題：無線傳感器網(wǎng)絡(luò)　切入點(diǎn)：節(jié)點(diǎn)部署　出處：《哈爾濱工業(yè)大學(xué)》2014年博士論文

【摘要】：無線傳感器網(wǎng)絡(luò)（Wireless Sensor Networks，WSN）是目前科研領(lǐng)域的熱點(diǎn)研究方向，被廣泛應(yīng)用于各個領(lǐng)域但帶來信息傳輸數(shù)量和質(zhì)量的巨大壓力。研究人員提出一種協(xié)作傳輸技術(shù)（Cooperative Transmission, CT），利用攜帶單天線的無線網(wǎng)絡(luò)節(jié)點(diǎn)組建虛擬MIMO（Multiple Input Multiple Output）系統(tǒng)獲得空間分集增益，擴(kuò)大無線網(wǎng)絡(luò)的覆蓋范圍以減輕該壓力。該理論在通訊、控制等領(lǐng)域得到了廣泛關(guān)注，但在利用節(jié)點(diǎn)數(shù)量有限的無線傳感器網(wǎng)絡(luò)完成長距離數(shù)據(jù)傳輸或在指定位置進(jìn)行遠(yuǎn)距離信息采集等類似的研究較少，且不利于實(shí)際應(yīng)用，沒有將協(xié)作傳輸?shù)臄U(kuò)展覆蓋范圍特性應(yīng)用到多跳無線傳感器網(wǎng)絡(luò)中。 本課題“基于協(xié)作傳輸?shù)娜褐悄軣o線傳感器網(wǎng)節(jié)點(diǎn)部署研究”，在對協(xié)作傳輸以及無線傳感器網(wǎng)絡(luò)研究基礎(chǔ)上，分析兩者結(jié)合帶來的增益效果，尋找最佳部署方案，提出利用僅攜帶單天線能量充足的數(shù)量固定類似基站的特殊節(jié)點(diǎn)，應(yīng)用協(xié)作傳輸技術(shù)組建在直線上可以獲得最遠(yuǎn)傳輸距離的無線傳感器網(wǎng)絡(luò)，以充分利用有限節(jié)點(diǎn)完成數(shù)據(jù)傳輸任務(wù)。針對不同場合不同需求下的數(shù)據(jù)傳輸任務(wù)，研究并改進(jìn)了多種智能優(yōu)化算法以提高節(jié)點(diǎn)部署的計(jì)算精度減少計(jì)算時間，并提出了相應(yīng)的節(jié)點(diǎn)部署策略。在災(zāi)后信息獲取、結(jié)構(gòu)健康監(jiān)測、作戰(zhàn)單元信息傳遞、個域網(wǎng)構(gòu)建等領(lǐng)域具有重要應(yīng)用。本文的主要研究工作如下： 針對固定節(jié)點(diǎn)數(shù)目的線形無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)部署問題，提出利用協(xié)作傳輸理論構(gòu)建自動解碼轉(zhuǎn)發(fā)（Auto Decode and Forward，ADF）節(jié)點(diǎn)部署模型，利用最大比合并（Maximal Ratio Combining，MRC）方法合并多徑信號，用解碼轉(zhuǎn)發(fā)協(xié)議對中繼信號進(jìn)行譯碼轉(zhuǎn)發(fā)，以實(shí)現(xiàn)協(xié)作傳輸技術(shù)在無線傳感器網(wǎng)絡(luò)上應(yīng)用并獲得傳輸距離的擴(kuò)展。實(shí)驗(yàn)表明，與非協(xié)作傳輸方法DET-CA相比，ADF節(jié)點(diǎn)部署模型可以獲得更遠(yuǎn)的傳輸距離，覆蓋距離增大。為了避免出現(xiàn)節(jié)點(diǎn)不能譯碼導(dǎo)致不工作的情況，提出數(shù)據(jù)共享解碼轉(zhuǎn)發(fā)（Message SharingDecode and Forward，MS-DF）協(xié)作模型，該方法在同一簇內(nèi)節(jié)點(diǎn)進(jìn)行數(shù)據(jù)共享，所有無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)全部工作，增大網(wǎng)絡(luò)的分集增益。實(shí)驗(yàn)表明，MS-DF模型有效可行，與ADF協(xié)作模型相比，在保證信號傳輸質(zhì)量前提下，極大地提高了無線傳感器網(wǎng)絡(luò)的直線傳輸距離。以5節(jié)點(diǎn)為例，比DET-CA傳輸距離增長5%-54%。 針對協(xié)作傳輸MS-DF節(jié)點(diǎn)部署模型無法常規(guī)求解問題，提出改進(jìn)的蟻群優(yōu)化算法來尋找模型最優(yōu)解。該方法使用離散分段方式改進(jìn)蟻群算法的啟發(fā)函數(shù)，提出引入?yún)擦址▌t加大信息素更新量，提出融合貪婪算法到禁忌列表（tabulist）更新原則加快算法收斂速度，逐步獲得最優(yōu)解。實(shí)驗(yàn)表明，改進(jìn)的蟻群方法可以有效收斂，并且獲得最優(yōu)解，適用于要求計(jì)算結(jié)果誤差小，但對計(jì)算時間要求不高的環(huán)境。仿真實(shí)驗(yàn)表明，，7節(jié)點(diǎn)時蟻群算法種群數(shù)量是10，迭代次數(shù)100次時結(jié)果誤差僅為0.07%，驗(yàn)證了該算法的可行性和有效性，可以應(yīng)用于優(yōu)化求解協(xié)作傳輸節(jié)點(diǎn)部署模型。 針對要求無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)部署計(jì)算時間短但對計(jì)算結(jié)果誤差要求不高的部署問題。提出應(yīng)用螢火蟲群優(yōu)化算法，通過改進(jìn)螢火蟲移動函數(shù)和啟發(fā)因子以適應(yīng)協(xié)作模型求解問題需要，改進(jìn)決策半徑更新函數(shù)和步進(jìn)函數(shù)加快算法的收斂速度，避免局部最優(yōu)以及極值震蕩問題，利用算法的多維并發(fā)計(jì)算優(yōu)勢減少計(jì)算時間獲得最優(yōu)解。實(shí)驗(yàn)表明，在保證最優(yōu)值穩(wěn)定收斂情況下，改進(jìn)螢火蟲群優(yōu)化算法可以有效地減少計(jì)算時間，以13節(jié)點(diǎn)為例，螢火蟲算法耗時僅是蟻群算法的30%。適合應(yīng)用于要求計(jì)算時間短的場合。 針對具有大量節(jié)點(diǎn)的無線傳感器網(wǎng)絡(luò)的節(jié)點(diǎn)部署問題，提出了基于協(xié)作傳輸技術(shù)的等數(shù)目節(jié)點(diǎn)簇，簇間距相等的節(jié)點(diǎn)部署方案。該方案分別基于MS-DF協(xié)作模型和滿分集增益的協(xié)作傳輸模型，每簇節(jié)點(diǎn)數(shù)目相同，每簇節(jié)點(diǎn)中心間距離相等，兩種方法均具有網(wǎng)絡(luò)結(jié)構(gòu)簡單、部署速度快的優(yōu)點(diǎn)，實(shí)驗(yàn)結(jié)果表明，可以有效地進(jìn)行大量節(jié)點(diǎn)的快速部署。
[Abstract]:Wireless sensor network (Wireless Sensor Networks, WSN) is currently a hot research direction in the field of scientific research, is widely used in various fields but the huge pressure on the quantity and quality of information transmission. The researchers propose a cooperative transmission technology (Cooperative Transmission CT), using MIMO to build virtual wireless network node with single antenna (Multiple Input Multiple Output) system to obtain spatial diversity gain, expanding the coverage of the wireless network in order to alleviate the pressure. The theory in communication, control and other fields has been widely concerned, but in the use of a limited number of nodes complete the long-distance data transmission of remote information collection or less similar to the location specified in the wireless sensor network, and is not conducive to the practical application, there will be extended cooperative transmission coverage characteristics applied to multi hop wireless sensor networks.
The research of "cooperative transmission group of intelligent wireless sensor networks deployment research based on the cooperative transmission and wireless sensor networks on the basis of analysis of both gain the effect brought by the search for the best plan, put forward by carrying only a fixed number of similar special node base station single antenna energy sufficient, application of cooperative transmission technology set up in a straight line can be obtained in wireless sensor network far transmission distance, to make full use of the limited node data transmission. The data transmission task of different needs of different occasions, studied and improved several intelligent optimization algorithm to improve the calculation accuracy of the node deployment to reduce the computing time, and put forward the corresponding node deployment strategy. In the post disaster information acquisition, structural health monitoring, combat unit information transmission, network construction and other fields has important application in this paper. The main research work is as follows:
The linear wireless sensor network node deployment problem for a fixed number of nodes is proposed using automatic decode and forward cooperative transmission theory (Auto Decode and Forward, ADF) node deployment model, using the maximum ratio combining (Maximal Ratio, Combining, MRC) method combined with multipath signal, decode and forward relay protocol for signal decode and forward, to achieve cooperation transmission technology in wireless sensor network applications and extend the transmission distance. Experimental results show that compared with the non cooperative transmission method DET-CA, ADF node deployment model can obtain the transmission distance more far, covering the distance increased. In order to avoid decoding node cannot causes on working conditions, puts forward the data sharing Message SharingDecode and Forward (decode and forward MS-DF), cooperation model, the method of nodes in the same cluster data sharing, all wireless sensor network node All the work, increase the diversity gain of the network. Experimental results show that the MS-DF model is feasible and effective, compared with the ADF cooperation model, in the premise of ensuring the quality of signal transmission, greatly improves the transmission distance of the wireless sensor network with 5 nodes. For example, the transmission distance than the DET-CA growth of 5%-54%.
MS-DF for cooperative transmission node deployment model cannot solve the problem of the conventional and proposed optimization to find the optimal solution of the improved ant colony algorithm. The method uses heuristic function discrete mode improved ant colony algorithm, proposed the introduction of the law of the jungle to increase the amount of pheromone, proposed fusion greedy algorithm to update the tabu list (tabulist) principle to speed up the convergence of the algorithm and gradually get the optimal solution. Experimental results show that the improved ant colony approach can effectively convergence, and obtain the optimal solution, suitable for the calculation error is small, but not high on the computational time requirements of the environment. Simulation results show that the 7 node number of ant colony algorithm population is 10, the number of iterations is 100 times the error is only 0.07% and verify the feasibility and effectiveness of the algorithm can be applied to the optimization of cooperative transmission node deployment model.
According to the requirement of wireless sensor network node deployment short calculation time but the calculation error requirements of the deployment problem. Proposed glowworm swarm optimization algorithm, by improving the firefly mobile function and heuristic factor in order to meet the need of cooperation model to solve the problem, an improved decision radius update function and step function to accelerate the convergence speed and avoid local optimal and extreme vibration problems, using multidimensional concurrent computational advantages reduce the computation time of optimal solution is obtained. Experimental results show that the optimal value in ensuring stable convergence conditions, improved glowworm swarm optimization algorithm can effectively reduce the computation time, with 13 nodes as an example, the firefly algorithm is time-consuming only ant colony algorithm suitable for 30%. for short computation time occasions.
Node deployment problem in wireless sensor networks with a large number of nodes, this paper proposes a cooperative transmission technology such as the number of cluster nodes based on node deployment scheme for cluster equal spacing. The scheme based on cooperative transmission MS-DF cooperation model and full diversity gain model, the same number of clusters per day, each cluster node is equal to the distance between the center. The two methods have simple structure, fast deployment, the experimental results show that the rapid deployment can be effectively carried out a large number of nodes.

【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TP212.9;TN929.5

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