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

【摘要】：無線傳感器網(wǎng)絡（Wireless Sensor Networks，WSN）是目前科研領域的熱點研究方向，被廣泛應用于各個領域但帶來信息傳輸數(shù)量和質量的巨大壓力。研究人員提出一種協(xié)作傳輸技術（Cooperative Transmission, CT），利用攜帶單天線的無線網(wǎng)絡節(jié)點組建虛擬MIMO（Multiple Input Multiple Output）系統(tǒng)獲得空間分集增益，擴大無線網(wǎng)絡的覆蓋范圍以減輕該壓力。該理論在通訊、控制等領域得到了廣泛關注，但在利用節(jié)點數(shù)量有限的無線傳感器網(wǎng)絡完成長距離數(shù)據(jù)傳輸或在指定位置進行遠距離信息采集等類似的研究較少，且不利于實際應用，沒有將協(xié)作傳輸?shù)臄U展覆蓋范圍特性應用到多跳無線傳感器網(wǎng)絡中。 本課題“基于協(xié)作傳輸?shù)娜褐悄軣o線傳感器網(wǎng)節(jié)點部署研究”，在對協(xié)作傳輸以及無線傳感器網(wǎng)絡研究基礎上，分析兩者結合帶來的增益效果，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，應用協(xié)作傳輸技術組建在直線上可以獲得最遠傳輸距離的無線傳感器網(wǎng)絡，以充分利用有限節(jié)點完成數(shù)據(jù)傳輸任務。針對不同場合不同需求下的數(shù)據(jù)傳輸任務，研究并改進了多種智能優(yōu)化算法以提高節(jié)點部署的計算精度減少計算時間，并提出了相應的節(jié)點部署策略。在災后信息獲取、結構健康監(jiān)測、作戰(zhàn)單元信息傳遞、個域網(wǎng)構建等領域具有重要應用。本文的主要研究工作如下： 針對固定節(jié)點數(shù)目的線形無線傳感器網(wǎng)絡節(jié)點部署問題，提出利用協(xié)作傳輸理論構建自動解碼轉發(fā)（Auto Decode and Forward，ADF）節(jié)點部署模型，利用最大比合并（Maximal Ratio Combining，MRC）方法合并多徑信號，用解碼轉發(fā)協(xié)議對中繼信號進行譯碼轉發(fā)，以實現(xiàn)協(xié)作傳輸技術在無線傳感器網(wǎng)絡上應用并獲得傳輸距離的擴展。實驗表明，與非協(xié)作傳輸方法DET-CA相比，ADF節(jié)點部署模型可以獲得更遠的傳輸距離，覆蓋距離增大。為了避免出現(xiàn)節(jié)點不能譯碼導致不工作的情況，提出數(shù)據(jù)共享解碼轉發(fā)（Message SharingDecode and Forward，MS-DF）協(xié)作模型，該方法在同一簇內(nèi)節(jié)點進行數(shù)據(jù)共享，所有無線傳感器網(wǎng)絡節(jié)點全部工作，增大網(wǎng)絡的分集增益。實驗表明，MS-DF模型有效可行，與ADF協(xié)作模型相比，在保證信號傳輸質量前提下，極大地提高了無線傳感器網(wǎng)絡的直線傳輸距離。以5節(jié)點為例，比DET-CA傳輸距離增長5%-54%。 針對協(xié)作傳輸MS-DF節(jié)點部署模型無法常規(guī)求解問題，提出改進的蟻群優(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。實驗表明，改進的蟻群方法可以有效收斂，并且獲得最優(yōu)解，適用于要求計算結果誤差小，但對計算時間要求不高的環(huán)境。仿真實驗表明，，7節(jié)點時蟻群算法種群數(shù)量是10，迭代次數(shù)100次時結果誤差僅為0.07%，驗證了該算法的可行性和有效性，可以應用于優(yōu)化求解協(xié)作傳輸節(jié)點部署模型。 針對要求無線傳感器網(wǎng)絡節(jié)點部署計算時間短但對計算結果誤差要求不高的部署問題。提出應用螢火蟲群優(yōu)化算法，通過改進螢火蟲移動函數(shù)和啟發(fā)因子以適應協(xié)作模型求解問題需要，改進決策半徑更新函數(shù)和步進函數(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)計算優(yōu)勢減少計算時間獲得最優(yōu)解。實驗表明，在保證最優(yōu)值穩(wěn)定收斂情況下，改進螢火蟲群優(yōu)化算法可以有效地減少計算時間，以13節(jié)點為例，螢火蟲算法耗時僅是蟻群算法的30%。適合應用于要求計算時間短的場合。 針對具有大量節(jié)點的無線傳感器網(wǎng)絡的節(jié)點部署問題，提出了基于協(xié)作傳輸技術的等數(shù)目節(jié)點簇，簇間距相等的節(jié)點部署方案。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)點數(shù)目相同，每簇節(jié)點中心間距離相等，兩種方法均具有網(wǎng)絡結構簡單、部署速度快的優(yōu)點，實驗結果表明，可以有效地進行大量節(jié)點的快速部署。
[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.

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

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