基于Zigbee技术外文翻译英汉对照.docx

集成低功耗无线传感器网络通信系统的设计摘要 无线传感器网络系统目前在国际社会关键应用在贸易，医疗保健和安全方面。这些系统具有独特的特点和面临的许多实施的挑战。在所有系统中，长寿命的要求是对无线传感器节点能源供应施加的最严重的设计约束。这就需要创新的设计方法来解决这一严格的要求。本文首先提供了无线传感器网络技术的概述。然后介绍了通信系统，电路设计和系统包装的考虑。在无线电架构和电路技术的选择是重点讨论了关于低功耗的实施和经营特色相匹配的传感器网络应用需求。最后，设计，实施和最具挑战性的组成部分，一个完整的低功耗CMOS接收系统，提出证明这些设计原则。简介一个无线传感器网络由自组织无线通信系统相连密集分布的节点。传感器节点架构包括传感，信号处理，嵌入式计算和无线网络组件。每个节点可配备多种应用程序特定的传感器和节点信号所需的物理环境信息的提取处理系统。相邻节点之间的合作可能有助于信号处理的敏感性和特异性环境事件检测。通过节能高效的无线通讯，局部处理的信息（需要大大减少数据未处理的传感器有效载荷的数据传输带宽）可传达给用户。低功耗是最重要的，以便为无线传感器网络的长期工作寿命。虽然这是促进了低工作周期操作，本地信号处理，多跳网络节点间的部分也可以引进，以减少传感器网络中的每个节点的通信链路的范围。由于通信路径作为一个尺度范围内的损失功法（有4或更大权力的规则在许多应用中指数），这在连接范围大幅度减少导致电力需求减少。与传统远程无线系统的特点相比，减少的范围和数据链路带宽产量为典型的无线传感器应用的一个重要的链路预算的优势。然而，极为有限的能源为无线感应器（小型电池系统）建立更强的设计挑战。随着低成本的要求，这些极大地激发了新的基于低功耗无线通信系统和传感器应用优化技术的有利互补金属氧化物半导体（CMOS）电路技术的发展。在下面的章节中，我们将介绍基于无线传感器网络的无线通信系统和电路设计。无线技术 不同的电路设计要求大大不同无线通信技术。在这里，我们将简要回顾一下正在审议的无线传感器网络通信技术的选择：单载波窄带和扩频技术（超宽带，超宽带技术是根据广泛调查，和那些已经出现在无线传感器网络应用的技术相比，并不成熟）。单载波窄带通信窄带通信方式已经在早期的无线传感器网络系统使用。窄带系统操作适用于当信道带宽(W)约等于数据速率（R），对于一个给定带宽，在加性白高斯噪声极限容量（AWGN）的通道(C)，可表示为: 其中，S和N分别是接收信号和噪声功率。由R / W的特点（每赫兹第二位）可知，对于一个传统的无线应用，重要的是要最大限度地提高带宽效率。日益复杂和高性能的方法是通过加强对收发器，必须针对功耗为代价的最高的带宽系统总吞吐量。例如，64正交调幅（QAM）的方法是采用在IEEE 802.11a / g的内实现20 MHz信道的数据传输速率高54 Mb / s的。更高的带宽效率也是一个理想的无线传感器网络。然而，在性能和功耗的平衡，必须被找到找到，因为这种复杂的无线电基带设计和更高的功率耗散的技术需求。事实上，这已经表明，在衰减的的电源支持下，调制系统会有一个高效率的结果，包括短包通信和低操作占空比操作。重要的是要注意的是窄带系统更容易受到比宽带系统的干扰。此外，监管问题需要共享频谱接入（和频率分集的指定级别）可能是一个额外的因素，防止寻找一些无线传感器网络应用的窄带技术。扩频通信扩频技术实现获得比以消耗额外的信号带宽的窄带系统更高信噪比。两种最常见的传播技术是直接序列扩频（DSSS）和跳频扩频（FHSS）。在 DSSS系统中，原来的窄带数据乘以一个芯片伪随机序列，造成噪音般的输出信号。 DSSS系统中，信号在芯片处理速度（局）。为了享有很高的处理增益，复杂的数字信号处理（DSP）电路必须工作在一个较高的速度即使在低数据率条件下。此外，在时时和同步在DSSS系统必须建立在一个芯片的间隔（1/RC）。这种基于DSSS技术是采用ZigBee标准进行讨论。FHSS技术，在蓝牙标准中的采用，和DSSS系统相比，具有简化硬件要求和简洁的同步协议。 FHSS系统可以通过传达了广泛的频率范围的信号提供一种改进的多径性能。FHSS也通过在它的跳频序列选择无干扰频道来避免干扰。虽然跳频技术对无线传感器网络的应用很有吸引力，但是挑战源于要在低功率要求下完成很宽的操作频段。这些敏捷跳频的规定条件需要快速解决频率选择的行为。开放空中接口标准选择 最近开发的和拟议的新标准下的无线传感器网络正在考虑之中。消费者应用需求驱动低功率无线空中接口标准的发展：一些可能适用于无线传感器网络。对于某些应用程序，网络通信协议栈的较低层，物理层（PHY）和介质访问控制的传感器网络（Mac），可能为那些有个人区域网络（PAN）和无线传感器的应用考虑。个人区域网标准的例子包括蓝牙协会（IEEE 802.15.1），超宽带协会（IEEE 802.15.3）和ZigBee（802.15.4）。这些标准是伴随着每一个传感器网络的限制。例如，目前可用的蓝牙设备显示功率（在40-100毫瓦为了发送和接收功能）的消费量，它在传感器网络许多类型应用过多。ZigBee物理层，现在在IEEE 802.15.4定义，指定了两个物理层，在2.4 GHz之一，在900兆赫等。 2.4 GHz的物理层使用为250 kb / s的数据速率偏移四相相移键控手（QPSK）的调制，欧洲的868MHz和北美915 MHz ，是工业，科学和医疗（ISM）频段，使用二进制PSK的数据速率（BPSK调制（QPSK）的调制与操作）调制技术，并分别提供20种数据速率为40 kb / s。此外，ZigBee可以支持比其他系统大量的节点，比蓝牙节点数目大得多。最后，低功耗无线收发器采用高度简化的信号（调幅）也进行了评估检测。同时为传感器网络提供低功率能力和快速原型的初步进展，这些简化的窄带解决方案的限制性了性能和抗干扰性能。对于综合设计无线传感器系统的选取 本节介绍了框架结构设计的考虑，现有的方法可能在传感器网络收发系统利用。重要的是要注意，大多数重点将落在接收机架构系统，因为随着低功耗和短距离的联系，典型的高复杂度接收机的能源需要足以支配低功耗低复杂度发射系统。此外，发射器占空比可能较低，而接收器占空比必须允许无线传感器节点以一种不可预知的方式来加入网络。因此，接收器的功耗通常用于无线传感器网络收发器短距离链接操作。工作频段的选择 无线传感器网络，预计工作在无牌经营的ISM频段之一。目前，CMOS实现的实际预选频段是900MHz，2.4 GHz和5 GHz频段。一般情况下，更高的频率允许在增益较小的同一个天线结构中，如此紧凑节点包装是允许的。不过，考虑到许多因素有利于低频时钟速率，包括减少和振荡器相位噪声操作。现在，同时采用先进的CMOS工艺应用在解决这些限制，系统制造成本也上升。因此，在这里讨论的无线传感器网络空中接口最低的频段是ISM频段的902-928兆赫频段。这使得成本效益的CMOS工艺（例如，0.35微米及早期技术）被用来实现成本很低的无线电系统。调制方法和数据速率选择 严格的低功耗要求决定了调制方式的选择。例如，在无线传感器网络的峰值电流消耗可能是由一个功率放大器（PA）决定。为了尽量减少峰值电流，恒定包络调制方案允许高效率的非线性功率放大器被支持。在这里，二进制频移键控（FSK）被选择。与其他信号方案相比，FSK也有简单的调制和解调电路，并且可以低功率运行。一个20 kb / s的数据速率或更低的速率被选择来提供紧凑的数据有效载荷和低功耗应用优化的操作。在带宽密集的频道和低音频率平衡的情况下，FSK的声频被选择，并且闪烁噪声直接直接影响转换接收器性能作用、体系结构和提供大音频率。因此，100千赫结构框架声频（高调制指数相对于传统的设备）被选择。用实验结果来做进一步的说明和讨论，本次评选筛选避免了CMOS闪烁噪声和直流偏移的影响，在没有采用耗电高阶滤波器过滤的情况下允许足够的相邻信道滤波。多样性的选择方法 多样性方法可用于传感器网络通信。除了刚才频率多样性的讨论，多样性也可以通过空间和时间分集技术的结合实现。空间分集需要多个天线和相应的多通道收发器，从而增加功耗，尺寸和设计复杂性。时间分集，相比之下，实现了可实施的以防止额外的复杂性和成本突发错误的低复杂度的编码和交织方法。 FHSS或DSSS技术，通过平均频率分集实现了更宽的带宽，并将被应用到未来的系统描述。总之，现有的无线标准，最适合于实现高频谱效率。不可避免地，电力消耗和能源效率成为次要的设计考虑。相比之下，能源资源是无线传感器的最宝贵的资产，一个传感器网络的成功展开要依低功率运行而定，而且可能还需要先进的电池管理和能源的清除方法。下面的讨论的无线系统设计和实现无线传感器将着重于提供必要的扶持扩频操作能力，性能和低能量的运作。低功率的无线电架构传统的高性能接收机采用超外差架构，以获得高选择性和高灵敏度。这些期望的特性依赖于复杂的接收机设计和严格的设计要求，而且往往导致高功耗。尽管这种优化的性能，可能是必要的对于蜂窝系统来说，它往往被牺牲在降低功耗的无线传感器网络。拟议的无线传感器接收器架构（图1）实现在直接转换和包括一个低中频（IF）优势的框架中。一个直接转换接收器的简洁之处在于可以提供低功耗操作，小面积，并可以在单片CMOS实现高度集成。直接转换接收器两个主要弊端是，CMOS技术中的闪烁噪声和直流偏移，它们阻碍了该架构在传统的高灵敏度收发器的使用。考虑到无线传感器网络应用需求特点的优势，这种限制是针对在前面一节中讨论的通信系统中的设计。这是在这里完成了利用可用带宽效益低噪音运行。具体而言，通过采用的FSK调制信号频率高，所需的信号存在远离高闪烁噪音区的频带中。对于一个的典型系统具有20 KB/s的数据速率和500 kHz通道空间，以100千赫频率间隔的FSK调，降频信号分配远离直流，从而减少了从闪烁噪声和直流偏移的影响。这有效地整合了低中频接收机架构的优势。虽然这种方法可以减少最小信道间隔，但是这是因为实际传感器数据处理中只占一个很小的带宽，频谱效率并不是一个主要问题。 Integrated Low-Power Communication System Design for Wireless Sensor Networks Tsung-Hsien Lin, National Taiwan UniversityWilliam J. Kaiser and Gregory J. Pottie, University of California, Los AngelesABSTRACT Wireless sensor network systems are now being applied by an international community for critical applications in commerce, healthcare, and security. These systems have unique characteristics and face many implementation challenges.Among all, the requirement of long operating life for a wireless sensor node underlimited energy supply imposes the most severe design constraints. This calls for innovative design methodologies to address this rigorous requirement. This article first provides anoverview of wireless technologies for sensor networks.It then describes communication system,circuit design, and system packaging considerations.The selection of radio architectures andcircuit techniques is discussed with an emphasison the low-power implementation and operatingcharacteristics that match requirements of sensornetwork application. Finally, the design, implementation,and performance of the most challengingcomponent, a complete low-power CMOS receiver system, is presented to demonstratethese design principles.INTRODUCTION A wireless sensor network consists of densely distributed nodes linked by self-organized wireless communication systems. Sensor node architectures include sensing, signal processing, embedded computing, and wireless networking components. Each node may be equipped with multiple application-specific sensors and onnode signal processing systems for extraction of required physical environment information.Cooperative signal processing among neighboring nodes may contribute both sensitivity and specificity to environmental event detection.Locally processed information (requiring much reduced data transport bandwidth from that of unprocessed sensor data payloads) may be conveyed to users through energy-efficient wireless communication.Low power consumption is paramount to enable a long operating lifetime for a wireless sensor network. While this is facilitated in part by low duty cycle operation and local signal processing, multihop networking among sensor nodes can also be introduced to reduce the communication link range for each node in the sensor network. Since communication path loss scales as a power law with range (with a power law exponent of 4 or greater in many applications), this reduction in link range results in massive reductions in power requirements Compared with characteristics of conventional long-range wireless systems, the reduced link range and data bandwidth yield a significant link budget advantage for typical wireless sensor applications. However, the severely limited energy sources (compact battery systems) for wireless sensors create profound design challenges. Along with the requirement of lowcost implementation, these motivate the development of dramatically new low-power communication systems and their enabling complementary metal oxide semiconductor (CMOS) circuit techniques optimized for wireless sensor applications. In the following sections, we will describe the wireless communication system and circuit design considerations for wireless sensor networksWIRELESS TECHNOLOGIESThe circuit design requirements vary drastically among different wireless communication technologies. Here, we will briefly review the communication technology choices under consideration for wireless sensor networks: single- carrier narrowband and spread-spectrum technologies (ultrawideband, UWB, technologies are under general investigation, but not mature in comparison to these technologies and have yet to appear in wireless sensor network applications.)SINGLE-CARRIER NARROWBAND COMMUNICATION Narrowband communication methods have been employed in early wireless sensor network systemsNarrowband system operation applies when channel bandwidth, W, is approximately equal to the data rate, R. For a given bandwidth, W, the ultimate capacity in an additive white Gaussian noise (AWGN) channel, C, is governedby the Shannon theorem, and can be expressed as where S and N are the received signal and noise power, respectively. For a conventional wireless application, it is important to maximize the bandwidth efficiency, characterized by R/W (bits per second per Hertz). Increasingly complex and high-performance methods are adopted to enhance the total system throughput for transceivers that must target the highest possible bandwidth at the expense of power dissipation. For example, the 64-quadrature amplitude modulation (QAM) method is employed in IEEE 802.11a/g to achieve a high data rate of 54 Mb/s within a 20 MHz channel. Higher bandwidth efficiency is also desirable in a wireless sensor network. However, a balance between performance and power must be found since such techniques demand complex radio and baseband designs and higher power dissipation. In fact, it has been shown that high-level modulation results in degraded energy efficiency for systems operating with short packet communication and low operating duty cycle . It is important to note that narrowband systems are more susceptible to interference than broadband systems. Also, regulatory considerations requiring shared spectrum access (and a specified level of frequency diversity) may be an additional factor that prevents narrowband technology from finding applications in some wireless sensor networks.SPREAD SPECTRUM COMMUNICATION Spread spectrum techniques achieve higher effective signal-to-noise ratio (SNR) than narrowband systems at the cost of excess signal bandwidth. The two most common spreading techniques are direct sequence spread spectrum(DSSS) and frequency hopping spread spectrum(FHSS). In a DSSS system, the original narrowband data is multiplied by a pseudo-random chip sequence, resulting in a noise-like output signal. In a DSSS system, the signal is processed at the chip rate (RC). In order to enjoy a high processing gain, complex digital signal processing (DSP)circuitry must operate at a high speed even under conditions of low data rate. Furthermore,timing and synchronization in a DSSS system must be established within a fraction of the chip interval (1/RC). The DSSS technique is adopted in the Zigbee standard to be discussed. The FHSS technique, adopted in the Bluetooth standard, generally has simplified baseband hardware requirements and simplified synchronization protocols compared to those of DSSS systems. An FHSS system can provide improved multipath performance by conveying signals over a broad range of frequencies. FHSS may also avoid interference by selecting interference-free channels in its hopping sequence. While FHSS methods appear attractive for wireless sensor network applications, challenges in their implementation result from requirements for operation at low power over a broad operating band. These set requirements for agile frequency hopping require fast settling behavior for frequency selection.AIR INTERFACE SELECTION OPEN STANDARDS Recently developed and proposed new standards are under consideration for wireless sensor networking. Consumer application demands have driven development of low-power wireless air interface standards: some may be applicable to wireless sensor networks. For some applications, the lower layers of the network communication protocol stack, physical (PHY) and medium access control (MAC), of a sensor network may be compared to those of a personal area network (PAN) and considered for wireless sensor application. Examples of PAN standardsinclude those of Bluetooth (IEEE 802.15.1), UWB (IEEE 802.15.3), and Zigbee (IEE 802.15.4). Each of these standards is accompanied by limitations for sensor networks. For example, currently available Bluetooth devices show power consumption (on the order of 40100 mW for transmit and receive functions, respectively) thatis excessive for many classes of sensor network applications. The physical layer of Zigbee, now definedunder IEEE 802.15.4 6, specifies two PHYs, one at 2.4 GHz, and the other at 900 MHz. The2.4 GHz PHY uses offset quaternary phase shift keying (QPSK) modulation with operation at a data rate of 250 kb/s, the European 868 MHz and North America 915 MHz industrial, scientific, and medical (ISM) bands use binary PSK (BPSK) modulation, and provide a data rate of 20 and 40 kb/s, respectively. Furthermore, Zigbeecan support a much larger number of nodes than other systems such as Bluetooth. Finally, low power wireless transceivers employing highly simplified signaling (amplitude modulation) have also been evaluated.7 While offering low power capability and rapid initial prototype progress for sensor networks, these simplified narrow band solutions are limited in performance and resistance to interference.ARCHITECTURE DESIGN SELECTIONS FOR INTEGRATED WIRELESS SENSOR SYSTEMS This section describes the architecture design considerations and approaches currently available that may be exploited in sensor network transceiver systems. It is important to note that most emphasis will lie on receiver architectures since with low system operating power and shortrange links, the typical high-complexity receiverenergy demand dominates over that of lowpower low-complexity transmitter systems. In addition, transmitter duty cycle may be low, whereas receiver duty cycle must necessarily be larger to permit acquisition of wireless sensornodes that arrive in the network in an unpredictable fashion. Thus, receiver power dissipation is typically dominant for wireless sensor network transceivers intended for short-rangelink operation.Operating Frequency Band Selection The wireless sensor network is expected to operate in one of the unlicensed ISM bands.Currently, the practical candidates for CMOS implementation are the 900 MHz, 2.4 GHz, and 5 GHz bands. In general, higher frequency allows smaller antenna structures at the same antenna gain, so compact node packaging is permitted. However, many considerations favor low-frequency operation, including reduced clock rate and oscillator phase noise level. Now, while the application of advanced CMOS processesassists in addressing these limitations, system fabrication cost also rises. Therefore,the wireless sensor network air interface discussed here operates at the lowest ISM band frequency of the 902928 MHz ISM band. This allows cost-effective CMOS processes (e.g., 0.35m and earlier technologies) to be used to implement very low-cost radio systems.Modulation Method and Data Rate Selection Stringent low power requirements dictate the choice of modulation methods. For example, in a wireless sensor network the peak current consumption may be determined by a power amplifier (PA). To minimize the peak current, constant envelope modulation schemes that allow high-efficiency nonlinear PAs are favored. Here, binary frequency shift keying (FSK) is chosen. Compared with other signaling schemes, FSK also has simpler modulation and demodulation circuitry, providing further benefit for low-power operation. A data rate target of 20 kb/s or lower is selected to provide operation that is optimized for compact data payloads and lower-power applications. The FSK tone frequency is then selected with a balance between the requirements of bandwidth efficiency favoring closely spaced channels and low tone frequency, and the role of flicker noise in direct conversion receiver architectures that influence performance and favor large tone frequency. Thus, for this architecture tone frequencies of 100 kHz (a high modulation index compared to that of conventional devices) are chosen. As is discussed further and illustrated with experimental results, this selection avoids the impact of CMOS flicker noise and DC offset, and still allows sufficient adjacent channel filtering without employing power-hungry high-order filters.Selection of Diversity Methods Multiple diversity methods are available for sensor network communications. In addition to frequency diversity, discussed earlier, diversity can also be achieved through a combination of spatial and time diversity techniques. Spatial diversity requires multiple antennas and corresponding multichannel transceivers, which increase power, size, and design complexity. Time diversity, in contrast, enables a low-complexity coding and interleaving method that can be implemented to prevent burst errors with only incremental additional complexity and cost. FHSS or DSSS techniques achieve frequency diversity by averaging over a wider bandwidth and will be applied to the systems described next. In summary, most existing wireless standards are tailored to achieve high spectral efficiency. Inevitably, power consumption and energy efficiency become secondary design considerations.In contrast, energy resources are the most valuable assets in wireless sensors, and successful deployment of a sensor network depends on low-power operation, and may also require advanced battery management and energy scavenging methods 8, 9. The following discussion of wireless system design and implementation for wireless sensors will focus on providing the required enabling spread spectrum operating capability, pe