摘要
无线传感器网络（Wireless Sensor Networks，WSN）是目前科研领域的热点研究方向，被广泛应用于各个领域但带来信息传输数量和质量的巨大压力。研究人员提出一种协作传输技术（Cooperative Transmission, CT），利用携带单天线的无线网络节点组建虚拟MIMO（Multiple Input Multiple Output）系统获得空间分集增益，扩大无线网络的覆盖范围以减轻该压力。该理论在通讯、控制等领域得到了广泛关注，但在利用节点数量有限的无线传感器网络完成长距离数据传输或在指定位置进行远距离信息采集等类似的研究较少，且不利于实际应用，没有将协作传输的扩展覆盖范围特性应用到多跳无线传感器网络中。
本课题“基于协作传输的群智能无线传感器网节点部署研究”，在对协作传输以及无线传感器网络研究基础上，分析两者结合带来的增益效果，寻找最佳部署方案，提出利用仅携带单天线能量充足的数量固定类似基站的特殊节点，应用协作传输技术组建在直线上可以获得最远传输距离的无线传感器网络，以充分利用有限节点完成数据传输任务。针对不同场合不同需求下的数据传输任务，研究并改进了多种智能优化算法以提高节点部署的计算精度减少计算时间，并提出了相应的节点部署策略。在灾后信息获取、结构健康监测、作战单元信息传递、个域网构建等领域具有重要应用。本文的主要研究工作如下：
针对固定节点数目的线形无线传感器网络节点部署问题，提出利用协作传输理论构建自动解码转发（Auto Decode and Forward，ADF）节点部署模型，利用最大比合并（Maximal Ratio Combining，MRC）方法合并多径信号，用解码转发协议对中继信号进行译码转发，以实现协作传输技术在无线传感器网络上应用并获得传输距离的扩展。实验表明，与非协作传输方法DET-CA相比，ADF节点部署模型可以获得更远的传输距离，覆盖距离增大。为了避免出现节点不能译码导致不工作的情况，提出数据共享解码转发（Message SharingDecode and Forward，MS-DF）协作模型，该方法在同一簇内节点进行数据共享，所有无线传感器网络节点全部工作，增大网络的分集增益。实验表明，MS-DF模型有效可行，与ADF协作模型相比，在保证信号传输质量前提下，极大地提高了无线传感器网络的直线传输距离。以5节点为例，比DET-CA传输距离增长5%-54%。
针对协作传输MS-DF节点部署模型无法常规求解问题，提出改进的蚁群优化算法来寻找模型最优解。该方法使用离散分段方式改进蚁群算法的启发函数，提出引入丛林法则加大信息素更新量，提出融合贪婪算法到禁忌列表（tabulist）更新原则加快算法收敛速度，逐步获得最优解。实验表明，改进的蚁群方法可以有效收敛，并且获得最优解，适用于要求计算结果误差小，但对计算时间要求不高的环境。仿真实验表明，7节点时蚁群算法种群数量是10，迭代次数100次时结果误差仅为0.07%，验证了该算法的可行性和有效性，可以应用于优化求解协作传输节点部署模型。
针对要求无线传感器网络节点部署计算时间短但对计算结果误差要求不高的部署问题。提出应用萤火虫群优化算法，通过改进萤火虫移动函数和启发因子以适应协作模型求解问题需要，改进决策半径更新函数和步进函数加快算法的收敛速度，避免局部最优以及极值震荡问题，利用算法的多维并发计算优势减少计算时间获得最优解。实验表明，在保证最优值稳定收敛情况下，改进萤火虫群优化算法可以有效地减少计算时间，以13节点为例，萤火虫算法耗时仅是蚁群算法的30%。适合应用于要求计算时间短的场合。
针对具有大量节点的无线传感器网络的节点部署问题，提出了基于协作传输技术的等数目节点簇，簇间距相等的节点部署方案。该方案分别基于MS-DF协作模型和满分集增益的协作传输模型，每簇节点数目相同，每簇节点中心间距离相等，两种方法均具有网络结构简单、部署速度快的优点，实验结果表明，可以有效地进行大量节点的快速部署。
Wireless Sensor Networks (WSN) is a hot research pot in science and technologywhich has been applied in different fields, and caused great pressure to dataacquasion and transmission. In order to reduce the pressure, reserachers proposedcooperative transmission (CT) technology, which is virtual distributed multiple-input-multiple-output (MIMO) system in the diversity configuration with only oneantenna in every node to expand the coverage area. It is widely concered in thecommunication and control area. There is not enough research on the long distancedata transmission by limit number of nodes or data acquasion where is far awayfrom the source node, and which is not suitable to practical application. There is noapplication by using the range expansion of CT to WSN.
In this dissertation of “Research on swarm intelligent wireless sensor networknodes deployment based on cooperative transmission”, the cooperative transmissiontheory and WSN is researched and analyzed to see the gain by combining the twotheories, to find the optimal deployment method. This dissertation proposed to usethe fixed number of mobile wireless sensor network nodes which has only oneantenna in every node and enough energy like a base station to get the maximumrange expansion along an appointed line by combining the CT technology. Everynode in the network would work very well without waste. Aiming at problem toapply this model to different environments, this dissertation compared and improveddifferent optimization algorithms to reduce time cost and improve the precision, andgive some rules for nodes deployment. There are some applications for thisstraight-line deployment such as disaster area data acquisition, structure healthmonitoring, communication between combat units, and personal area network, et al.The main research contents of this dissertation is as follows:
Aiming at the problem that build WSN nodes deployment model with fixednumber of nodes based on CT technology. This dissertation proposed ADF (AutoDecode and Forward) model by using the MRC (Maximal Ratio Combining) methodto combine the copies in each orthogonal channel and use decode and forwardprotocol to receive and retransmit the signals, and to realize the maximum rangeexpansion of WSN. The simulation results show that the ADF model is useful andeffective to get longer end-to-end distance. In order to avoid no decode and not workof any node, this dissertation proposed the MS-DF (Message Sharing Decode andForward) model. This novel model supposed the message sharing of all the nodes inthe same cluster, and then forward to the next hop which could avoid the waste ofnodes in the network and improve the gain of the network. Simulation results show that comparing between MS-DF and ADF models, the MS-DF model great improvesthe range expansion under the same constraint of transmission quality requirement.Take5nodes as an example, the transmission distance of MS-DF is longer thanDET-DA5%to54%.
Aiming at the problem that there is no solution of the MS-DF model by traditionalmethod. This dissertation proposed the improved ant colony algorithm (IACA) toget the optimal result of the CT models. IACA improved the heuristic function bydiscreting segements of the distance; proposed novel pheromone update rule basedon the law of jungle, proposed the novel tabu list combined the greedy algorithm, toget the optimal results systematically. Simulation results show that the IACA isconvergent, useful and effective, which is suitable for the application requirement ofhigh precision but do not care about time cost. Take7nodes as an example, whilethe ant number is10, the iteration times is100, the inaccuracy is only0.07%, whichprove the IACA is useful to get the optimal result of CT model.
Aiming at application requirement of short time cost but do not care much aboutprecision. This dissertation proposed the improved glowworm swarm optimization(IGSO) algorithm to solve this problem, which improved the glowworms’ movementprobability function and heuristic factor to adapt to the CT model, improved thelocal-decision range and movement direction function to increase the algorithmconvergent speed and avoid the extremum value shock. By using the advantage ofparallel computing to reduce the calculation time cost. Simulation results show thatIGSO algorithm is useful and effective to reduce the cost time under the constraintof the algorithm is convergent to the optimal result. Take13nodes as an example,the IGSO cost only30%of IACA to solve the model, which is more suitable to theapplication of short time cost.
Aiming at the problem that build the deployment model of big number of WSNnodes based on CT technology, this dissertation proposed two deployment methodsbased on the same number of nodes in every cluster and same distance between twoneighbor clusters. This dissertation proposed the two methods based on the MS-DFmodel and full diversity gain theory, separately. The simulation results show that thetwo methods are both useful and effective, with the advantage of simple topology,which could deploy a big number of nodes quickly.
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