【作者】 叶佥昱；

【导师】 周炯槃；

【作者基本信息】 北京邮电大学 ， 信号与信息处理， 2009， 博士

【摘要】 无线传感器网络诞生于大规模集成电路高速发展,无线通信技术逐步成熟和微电机技术日新月异的今天。由于其对传感器节点大小的苛求,导致了传感器节点供电系统的先天不足。这种能量的有限性使得所有着眼于无线传感器网络的研究都要首先考虑一个重要的问题,能量有效性。本文从两个方面来探讨实现无线传感器网络的能量有效性,对节点间传递信息的压缩和实现能量有效的路由算法。由于无线传感器网络中节点的能量受限,因此在设计算法时要考虑尽量避免节点间的过多通信,所以分布式算法是一种适合于无线传感器网络的设计方法。根据仙农的信道编码定理可知,如果对多个信源进行联合压缩则多个信源的联合熵可以作为发送这些信息的总速率以实现无损译码。但是在无线传感器网络中,能否利用分布式压缩来实现信息的压缩呢?分布式信源编码理论证明在具有相关性的信源间进行分布式无损压缩,仍然可以采用联合熵作为总的传输速率。本文首先介绍分布式信源编码定理,详细的介绍了Slepian-Wolf和Wyner-Ziv关于分布式信源编码的理论基础,然后介绍了一种利用伴随式和卷积码译码实现分布式信源编码的方法。通过对译码过程的分析,本文给出了这个译码算法的修正方法,并且通过对错误比特的分类统计详细地分析了改进算法的作用和它对错误比特的纠正。同时,本文实现了基于上述算法原理的二进制信道下的分布式信源编码方法,并对译码错误情况的仿真结果进行了分析,结果表明由于受到卷积码译码器性能的影响,如果需要获得较好的译码性能需要采用更加高效的信道编码系统。然后本文介绍了近几年在信道编码领域引起高度重视的性能优异的LDPC编码算法,介绍了LDPC编码在分布式信源编码领域的应用,同时介绍了一种基于伴随式的LDPC码的分布式信源编码方法。在对这种方法进行分析时,本文没有力求表现出它的优异性能,而是从独特的视角进行分析。本文考察LDPC方法在不同码长下的性能,仿真的结果显示LDPC方法的译码性能随着码字长度的减少呈快速下降趋势,瀑布型的仿真曲线逐渐趋缓,因此基于LDPC编码的分布式信源编码方法适用于码字长度较长的应用环境。随后,我们提出了一种应用多进制LDPC编码实现多进制分布式信源编码的方案,与前人的工作不同,我们采用了更为普通的高斯信源作为输入信源,同时多进制LDPC编码方案也改进了基于卷积码的分布式信源编码方案的译码性能,仿真的结果表明在一定的压缩率下,这个方法可以获得非常好的译码结果。路由是无线传感器网络中非常重要的技术之一,其中分簇式的路由协议由于其具有较强的鲁棒性,灵活性和能量有效性成为研究者关注的重点。本文并没有将研究的重点放在改进协议本身上,而是将其他技术与路由协议相结合来实现传感器网络的能量有效性。首先,通过对分簇路由算法能量模型的分析,我们提出利用本地信噪比这个指标有目的地选择簇内节点传输数据,从而避免了大量节点传递数据的能量消耗。仿真的结果表明该算法能够有效的平衡不同类型能量的消耗,节省节点的能量消耗,延长网络的生存期,并且不会对目标状态的判断造成较大的影响。为了克服无法准确判断目标与节点间的位置而影响目标跟踪的问题,我们提出了一种基于距离比例的方法来估计目标的位置。节点所估计的目标的状态大多与距离成一定的比例关系,因此本方法可以与状态估计相结合来判断目标的位置信息。仿真的结果表明这种方法描绘的目标路径比较贴近目标的真实路径,可以有效的估计目标的位置信息。最后,本文给出了一个简单的架构将分布式信源编码与分簇式路由协议相结合。该方法利用簇头上的数据作为边信息来解码从簇内节点传送过来的压缩信息,仿真的结果表明利用两者结合可以较好的实现网络的能量有效性。更多还原

【Abstract】 Nowadays, with the development of wireless communication and electronics, a new kind of network has become a hot research area, that is wireless sensor networks. Because of the needs for small size sensor nodes, the power supply of this kind of network is always limited. Thus, the most important factor of designing the protocols for wireless sensor networks is energy efficiency. In this paper, the energy efficiency of wireless sensor networks is discussed in two aspects, information compression and energy efficient routing protocols.Due to the limitation of power supply, avoiding the unnecessary communication among sensors is preferred. One way that can achieve this goal is to adopt distributed algorithms. According to Shannon’s theory, joint entropy is enough for transferring correlated sources when they can communicate with each other. But, if distributed compression is needed, the joint entropy can also be sufficient?Distributed source coding theory demonstrates that the joint entropy limit can also be achieved by distributed compression. In this paper, distributed source coding theory is firstly introduced, especially Slepian-Wolf and Wnyer-Ziv’s milestone theories. After that a distributed source coding method by using syndromes is presented. This paper explores the decoding process and gives the modification methods. After analyzing the classified decoding errors, the results demonstrate that the proposed methods can effectively improve the decoding performance. This method is also implemented under binary channels. The simulation results show that in order to obtain a better decoding performance, the powerful channel codes such as Turbo code and LDPC code must be adopted.Next, the LDPC code which attracts much attention during these years in channel code field is introduced. And its applications in distributed source coding areas are also presented. A syndrome based method is presented and analyzed in a new view. The simulation does not focus on getting better performance, but on comparing the error probabilities under different code lengths. The results show that the decoding performance drops quickly with the decreasing of code length. It means that LDPC method should better be used in a larger code length circumstance. At the end, a non-binary LDPC method is proposed. As difference from others work, here, a more general source generating method is used. The simulation results show that this method achieves much better decoding performance under lower compression rate.Routing is one of the most important techniques in wireless sensor networks. Because of its robustness, flexibility and energy efficiency, clustered routing protocols attract much attention. This paper does not focus on modifying the protocols, but on adopting other technologies to cooperate with routing protocols to realize energy efficiency. First, by analyzing the energy model of clustered routing protocols, a local SNR aid method is proposed. By choosing suitable inner cluster sensors for data transferring, it avoids consuming the energy on all sensors and save a large amount of energy. The simulation results show that this method can balance the different kinds of energy consumptions, save the power of sensor nodes, prolong network life time and do not affect the target state estimation results. Second, a target tracking method by using the proportion of distance is proposed. In some cases, it is hard to decide the distance between sensor nodes and the target, but the value of most target state estimation result is proportion to the distance between target and sensor nodes. So this proportion can be used to estimate the target position. The simulation results show that the locus of target drawn by this method is close to the original locus, so it can be used estimate the target location.At last, a simple architecture to combine distributed source coding and clustered routing protocols is proposed. The information on cluster head can be used as side information and help decoding the compressed information transferred from inner cluster sensor nodes. The simulation results show that with the cooperation of these two technologies, it effectively realizes the energy efficiency.更多还原