—种基于V-BLAST技术的多跳协作式传感网络节能MAC跨层设计

协作式(虚拟)MIMO技术被认为是新兴有效的传感器网络节能解决方案之一.本文在考虑网络电路能耗的情况下,采用跨层设计方法提出了一种能量高效的多跳协作式V-BLAST传输策略.为了达到网络寿命最大化的目标,本文建立并分析了系统能耗模型,在此基础上对传输速率、传输跳数、分簇个数和协作式天线节点个数等网络参数进行了联合优化.仿真结果表明,通过选取最优网络参数,本文所提出的策略相比传统的多跳路由协议和LEACH协议能显著降低节点传输能耗和延长网络寿命.     

无线传感器网络中基于链的虚拟MIMO策略

无线传感器网络能量受限,策略应尽可能地减少能量消耗,以延长网络寿命。提出一种基于链的能量高效的虚拟MIMO传输策略,对该传输策略进行能耗和时延建模,确定最优的虚拟MIMO链的个数、协作节点个数以及传输速率等网络通信参数。仿真结果表明,即使考虑到电路能耗和信道训练开销,该传输策略也能有效节省能量,提高网络生命期,同时降低时延。     

一种改进的无线传感器网络最小跳数路由协议

针对无线传感器网络最小跳数路由协议数据包多路径冗余传输,能量消耗不均衡等问题,提出了一种改进的无线传感器网络最小跳数路由协议。该协议通过引入侦听机制在网络中建立传输路径,同时采用一种新的能量均衡策略解决关键节点能耗过快的问题,以有效延长网络寿命。通过自主研发的无线传感器网络仿真平台进行仿真,比较最小跳数路由协议和改进协议的性能。实验结果表明:改进协议能够很好的均衡网络能量消耗,提高网络能量有效性,延长了网络寿命。     

无线传感器网络中一种基于分簇的能量高效虚拟MIMO传输策略

协作式MIMO技术被认为是传感器网络中有效的节能解决方案之一.针对中小规模传感器网络设计了一种基于分簇的能量高效的协作式虚拟MIMO传输策略(ECCM).在考虑了分布式STBC编码信道训练开销的情况下,分析了该传输策略的系统总体能耗.基于该能耗模型,建立了一种基于端到端的全网能耗最优化模型,并用该模型来求解最优的虚拟MIMO域(分簇)个数、协作节点(虚拟天线)个数以及传输速率等网络通信参数.仿真结果表明,通过选取最优协议参数,即使考虑到电路能耗和信道训练开销,ECCM策略也能显著降低节点传输能耗,延长网络寿命.     

无线传感器网络跨层自适应唤醒算法研究

时钟同步与能耗有效性是无线传感器网络多跳传输关键问题.提出一种自适应唤醒算法,在MAC层和网络层进行跨层优化,节点按需自适应唤醒,实现多跳网络的协同传输,能够有效降低系统能耗.该算法不需要节点间的周期性同步,减少了频繁的包交换带来的数据冲突与能量浪费,从而提高了网络可靠性和能耗效率,提高了基于IEEE802.15.4标准的多跳网络的节能效率.为了验证算法有效性,工作分别在NS-2仿真环境和实际应用场景下进行了仿真与测试验证,结果表明在传输可靠性和节能效率上均由较大提高.跨层自适应唤醒算法可进一步推广到大规模异构自组织网络中.     

井下无线传感器网络能量空洞问题研究

提出利用虚拟多输入多输出的思想来解决煤矿无线传感器网络的能量空洞问题,并提出了一种基于能量均衡的多跳非均匀分层分簇协议MUHC;阐述了MUHC传输模型,并分析了基于MUHC的虚拟多输入多输出系统能耗。Matlab仿真结果表明,与经典的LEACH协议及EEUC协议相比,MUHC协议能够平衡整个网络的能量,延长网络生存时间,缓解能量空洞问题。     

虚拟MIMO传感器网络中一种联合网络效用和生存时间优化的分布式算法

虚拟(协作式)MIMO技术被认为是传感器网络中有效的节能解决方案之一,然而,现有虚拟MIMO传输策略的设计大多只关注如何有效降低网络能耗,而很少关注反映网络性能的其他指标,例如网络效用(Network Utility),该指标反映了网络数据采集和传输量的多少.为了联合优化网络效用和网络生存时间这两个网络性能参数.本文首先分析虚拟MIMO传输能耗特点,然后基于网络效用最大化(Network Utility Maximization)思想对虚拟MIMO传感器网络进行联合网络生存时间和网络效用的优化建模.在该模型的求解过程中,通过使用对偶分解技术将原需要集中计算的优化问题分解为可以在不同节点上进行计算的子优化问题,并得出一种联合优化网络效用和生存时间的分布式优化算法.该算法的仿真结果显示,网络中的虚拟MIMO节点仅需要交互邻居节点信息,通过有限次的迭代计算,就能收敛到全局最优的发送速率以及功率值.从而使系统总的效用和网络生存时间之间能够达到帕累托(Pareto)最优平衡.     

一种基于水声信道的无线传感器网络路由协议

以无线传感器网络的水下应用所面对的挑战为背景,针对水声信道的传输特点,在最小代价算法和目的节点序列距离矢量DSDV(Destination-Sequenced Distance-Vector)路由协议的基础上,提出了一种均衡节点能耗的路由协议算法.该协议按照最小能量代价建立多跳路由表,从而在数据传送时能够均衡各节点的能量消耗,达到延长网络生命周期的目的.仿真结果表明,相对于DSDV协议,本文提出的协议能够实现能量均衡,有效的延长网络生存周期.     

无线传感器网络的能量均衡路由算法

针对大部分无线传感器网络路由协议只能实现局部能量均衡的问题,提出一种改进的能量均衡路由算法,把传感器网络构建成按最小跳数分层的网络,利用节点直接传输和逐跳转发相结合的混合传输策略,在多跳传输时,使用改进的基于多路径路由的最大能量路径算法。仿真结果表明,该算法能有效延长网络的生存时间。     

MIMO多跳簇结构无线传感器网络的路由算法及其能耗研究

由于分层簇结构协议能有效地解决无线传感器网络的能耗问题,文中针对基于MIMO的多跳簇结构无线传感器网络,提出了一种基于距离矢量的改进路由算法,同时在J-sim仿真平台上进行了相应的仿真,从而证明了改进路由算法的有效性。另外也证明了该系统的节点能耗特点和MIMO技术对降低系统能耗所具有的一定作用,但在低信噪比时其效果不明显。     

基于MIMO模式的无线传感器网络数据传输协议

在对分簇无线传感器网络在簇群内和簇群之间数据传输能耗进行分析的基础上,提出了一种在簇群间采用MIMO模式进行数据传输的方法。该方法以HEED协议为基础,将MIMO模式引入到簇群间的数据传输过程中,极大地降低了传输能耗,并且创建了一种基于MIMO技术的分簇传感器网络能耗模型,推导出实现网络能耗最小化时系统参数的最优值。实验结果显示,与HEED协议相比,该方法更显著地降低了网络的总体能耗,使网络具有更长的生存期。     

Joint rate and cooperative MIMO scheme optimization for uniform energy distribution in Wireless Sensor Networks

An energy efficient adaptive rate cooperative MIMO selection scheme is proposed for uniform load distribution in the cluster based wireless sensor networks. The intrinsic data flow direction in multi-hop cluster based sensor networks causes uneven load distribution in the network. The transit clusters and the clusters near the base station carry more network traffic than the other clusters. Cooperative MIMO can artistically reduce the per bit energy consumption, Space–Time Block Codes are designed to achieve maximum diversity for a given number of transmit and receive antennas with very simple decoding algorithm. In radio fading channel, STBC require less transmission energy than SISO technique for the same Bit Error Rate and can be employed practically in Wireless Sensor Networks by using the cooperative MIMO scheme. Considering Alamouti and Tarokh Space–Time Block Codes, the number of antennas at both the transmission and the reception sides are selected with respect to the cluster load. The crude energy consumption per cluster then refined through adaptive rate transmission. It has been shown that the load based joint adaptive selection of rate and cooperative nodes in clusters renders uniform energy consumption in the network.     

基于控制的低能耗多跳分簇路由协议

针对无线传感器网络(WSN)的多跳分簇协议中,Sink节点附近的簇头能量消耗过快,簇头分布不够均匀,多跳链路不够高效等关键问题,提出了基于控制的低能耗多跳分簇路由协议。通过控制成簇数量与大小、多跳链路能耗、轮数与每一轮中的数据传输量来解决以上问题。仿真结果表明：所提协议与低功耗自适应分簇(LEACH)协议和基于非均匀分簇的无线传感器网络路由协议(EEUC)相比,网络稳定期分别延长了138%和13%,网络生命期分别延长了13%和8%,因此能够有效地降低网络能耗,均衡网络负载,延长网络生存时间。     

基于虚拟栅格的传感网能量空洞缓解方法

为延长无线传感网的生命期,提出了一种能量空洞缓解方法。网络被划分为若干虚拟栅格,以便于多跳传输。树形结构的数据上传路径则由各个簇头和移动Sink构成。此外,为缓解能量空洞的出现,Sink的移动轨迹被设计为可控的,从而有效均衡了能耗。仿真结果表明,该方法在多跳传感网络的节能方面表现较为良好。     

Unifying eigen-mode MIMO transmission

Multiple-input multiple-output (MIMO) technique plays a key role in improving the spectrum and power efficiency in future mobile communication systems. Exploiting a unified MIMO transmission scheme that can adapt with various channel conditions is well motivated both in theory and practical applications. An eigen-mode based closed-loop MIMO transmission over frequency selective fading MIMO channels, which considers receive correlation, transmit correlation and line of sight (LOS) components, is investigated by maximizing the upper bound of channel capacity under the assumption that the channel is partially known at the transmitter and perfectly known at the receiver. Based on the eigen-mode transmission, several key techniques including linear precoding, stream selection, virtual spatial hopping and online capacity estimation are proposed, and a unified MIMO transmission scheme is established. Both computer simulation and field test results show that the proposed scheme can significantly improve the spectral efficiency and link reliability under various channel conditions.     

An energy-efficient,transport-controlled MAC protocol for wireless sensor networks

In wireless sensor networks (WSNs), one major cause of wasted energy is that the wireless network interface is always on to accept possible traffic. Many medium access control (MAC) protocols therefore adopted a periodic listen-and-sleep scheme to save energy, at sacrifice of end-to-end latency and throughput. Another cause is packet dropping due to network congestion, necessitating a lightweight transport protocol for WSNs. In this paper, we suggest a transport-controlled MAC protocol (TC-MAC) that combines the transport protocol into the MAC protocol with the aims of achieving high performance as well as energy efficiency in multi-hop forwarding. Although TC-MAC also works through a periodic listen-and-sleep scheme, it lowers end-to-end latency by reserving data forwarding schedules across multi-hop nodes during the listen period and by forwarding data during the sleep period, all while increasing throughput by piggybacking the subsequent data forwarding schedule on current data transmissions and forwarding data consecutively. In addition, TC-MAC gives a fairness-aware lightweight transport control mechanism based on benefits of using the MAC-layer information. The results show that TC-MAC performs as well as an 802.11-like MAC in end-to-end latency and throughput, and is more efficient than S-MAC in energy consumption, with the additional advantage of supporting fairness-aware congestion control.     

Power control based topology construction for the distributed wireless sensor networks

Wireless sensor network consists of large number of sensor nodes with limited battery power, which are randomly deployed over certain area for several applications. Due to limited energy resource of sensors, each of them should minimize the energy consumption to prolong the network lifetime. In this paper, a distributed algorithm for the multi-hop wireless sensor network is proposed to construct a novel energy efficient tree topology, without having location information of the nodes. Energy conservation of the nodes is accomplished by controlling transmission power of the nodes. Besides, maintenance of the network topology due to energy scarcity of the gateway nodes is also proposed in the protocol. Simulation results show that our distributed protocol can achieve energy conservation up to an optimum level similar to the centralized algorithm that we have considered and can extend the network lifetime as compared to other distributed algorithms without any power control.