Low Power Transceiver Design Parameters for Wireless Sensor Networks

Designing low power sensor networks has been the general goal of design engineers, scientist and end users. It is desired to have a wireless sensor network (WSN) that will run on little power (if possible, none at all) thereby saving cost, and the inconveniences of having to replace batteries in some difficult to access areas of usage. Previous researches on WSN energy models have focused less on the aggregate transceiver energy consumption models as compared to studies on other components of the node, hence a large portion of energy in a WSN still get depleted through data transmission. By studying the energy consumption map of the transceiver of a WSN node in different states and within state transitions, we propose in this paper the energy consumption model of the transceiver unit of a typical sensor node and the transceiver design parameters that significantly influences this energy consumption. The contribution of this paper is an innovative energy consumption model based on simple finite automata which reveals the relationship between the aggregate energy consumption and important power parameters that characterize the energy consumption map of the transceiver in a WSN;an ideal tool to design low power WSN.

A Novel Low-Complexity Low-Latency Power Efficient Collision Detection Algorithm for Wireless Sensor Networks

Collision detection mechanisms in Wireless Sensor Networks (WSNs) have largely been revolving around direct demodulation and decoding of received packets and deciding on a collision based on some form of a frame error detection mechanism, such as a CRC check. The obvious drawback of full detection of a received packet is the need to expend a significant amount of energy and processing complexity in order to fully decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a suite of novel, yet simple and power-efficient algorithms to detect a collision without the need for full-decoding of the received packet. Our novel algorithms aim at detecting collision through fast examination of the signal statistics of a short snippet of the received packet via a relatively small number of computations over a small number of received IQ samples. Hence, the proposed algorithms operate directly at the output of the receiver's analog-to-digital converter and eliminate the need to pass the signal through the entire. In addition, we present a complexity and power-saving comparison between our novel algorithms and conventional full-decoding (for select coding schemes) to demonstrate the significant power and complexity saving advantage of our algorithms.

A 2.4-GHz-Low-Power CMOS RF Transmitter for IEEE 802.15.4 Standard

This paper presents the experimental results of a low-power RF transmitter for 2.4-GHz-band IEEE 802.15.4 standard in 0.18-μm CMOS technology. In order to make an adaptive RF transmitter, several factors must be considered. The most important factors are performances, power consumption, output power, noise factor, and cost. The RF transmitter comprises a quadrature passive mixer, and a power amplifier. The proposed RF transmitter consumes only 10.8-mW under a supply voltage of 1.8-V.

M-ary FSK Modulation Using Short Packet without a Preamble and Error Detection Codes for Low Power Wireless Communication

Since power of a wireless sensor node is limited, low power communication technology has been required. M-ary frequency shift keying (MFSK) modulation with orthogonal signals is one of the methods to decrease the power. However, if the amount of transmitted data including such as an identification number (ID) of a node and measured data is small, a ratio of the data length to the total packet length, which means transmission efficiency, becomes quite low. Because a preamble and error check codes are generally added to a packet for synchronization between a transmitter and a receiver and for decrease in reception errors, respectively. In this research, we have developed a method with digital filters which eliminates the other signals from time series frequency spectra not to use a preamble and error check codes. Although estimated synchronization loss of the method was less than 1.6 dB, it was found that the loss of the method on error packet rate was almost 0 dB at more than 0.001 of packet error rate by a simulation made by BASIC. These results indicate a possibility to realize that a packet which consists of only two symbols can be received with no error if the transmitted data is less than 14 bits using 128-FSK.

Low Power Design of High Speed CMOS Pulse Stream Neuron Circuit

A new pulse stream neuron circuit is presented, which can be obtained in the digital CMOS process and combines both the merits of digital circuits and analog ones. The output is expressed by the frequency of the pulses with transfer characteristic, which is correspondent with the ideal sigmoid curve perfectly. Moreover, the pulse\|active strategy is introduced into the design of this CMOS pulse stream neuron circuit for the first time in order to reduce the power dissipation, which is applicable to the low\|power design of mixed\|signal circuits,too. A simple technical process and compact architecture make this circuit work at a higher speed and with lower power dissipation and smaller area.

Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

The Internet of Things(IoT)consists of interconnected smart devices communicating and collecting data.The Routing Protocol for Low-Power and Lossy Networks(RPL)is the standard protocol for Internet Protocol Version 6(IPv6)in the IoT.However,RPL is vulnerable to various attacks,including the sinkhole attack,which disrupts the network by manipulating routing information.This paper proposes the Unweighted Voting Method(UVM)for sinkhole node identification,utilizing three key behavioral indicators:DODAG Information Object(DIO)Transaction Frequency,Rank Harmony,and Power Consumption.These indicators have been carefully selected based on their contribution to sinkhole attack detection and other relevant features used in previous research.The UVM method employs an unweighted voting mechanism,where each voter or rule holds equal weight in detecting the presence of a sinkhole attack based on the proposed indicators.The effectiveness of the UVM method is evaluated using the COOJA simulator and compared with existing approaches.Notably,the proposed approach fulfills power consumption requirements for constrained nodes without increasing consumption due to the deployment design.In terms of detection accuracy,simulation results demonstrate a high detection rate ranging from 90%to 100%,with a low false-positive rate of 0%to 0.2%.Consequently,the proposed approach surpasses Ensemble Learning Intrusion Detection Systems by leveraging three indicators and three supporting rules.

基于边缘计算的智慧物联网农业病虫识别系统设计与实现

【目的】传统云计算存在实时性不够、带宽不足、能耗较大、不利于数据安全与隐私等问题,应用边缘计算能有效解决上述问题。【方法】通过基于边缘计算的智慧物联网农业病虫识别系统的开发与应用,测试目标应用的数字化、集成化、信息化、可视化和智能化,减少云计算的计算压力。【结果】智慧物联网农业病虫识别系统能实现节点或网关离线后自动重新登录的功能、系统数据采集与上报功能、服务器数据显示功能,从而减轻云计算中心的计算负担。【结论】研究结果将为使用边缘计算的系统提供有力的支撑,能保证整个系统的智能性、可靠性、安全性和经济性,并提高了计算能力和社会生产效率,为大规模推广边缘计算奠定了基础。

考虑太阳能辅助碳捕集技术的综合能源生产单元随机低碳调度策略

为解决综合能源生产单元(integrated energy production unit,IEPU)中燃煤机组碳捕集过程的高能耗问题,同时应对新能源不确定性对运行调度带来的挑战,该文提出一种考虑太阳能辅助碳捕集技术的IEPU随机低碳调度策略,旨在实现IEPU的多能协同与低碳运行。首先,对含太阳能辅助碳捕集热电联产单元(combined heat and power based on solar-assisted carbon capture,CHP-SACC)的能量流动与运行机理进行分析,并构建其运行模型;其次,考虑风电不确定性带来的影响,提出一种基于条件最小二乘生成对抗网络(conditional-least squares generative adversarial networks,C-LSGANs)的可再生能源场景生成方法来提高场景的生成质量;然后,考虑异质能流耦合约束、多元设备运行约束以及能量平衡约束等,以最大化系统运行收益期望为目标构建IEPU随机低碳调度模型;最后,在算例仿真中设置不同的运行策略验证所提低碳转型方案的有效性,并分析了能源价格、设备容量等因素对系统运行收益的影响。

融合大模型与图神经网络的电力设备缺陷诊断

电力系统中不同装置设备的缺陷评级和分析处理常受运维人员主观性影响,导致同一缺陷文本描述出现不同的严重程度评级。专业知识的差异也导致诊断分析差异和诊断效率不同。为提升缺陷诊断的准确性和效率,提出一种基于图神经网络的缺陷文本评级分类方法和大模型智能诊断分析助手。构建专业词典,使用自然语言处理算法规范化文本描述。通过统计方法,优化缺陷文本的语义表示。集成图注意力神经网络和RoBERTa模型对缺陷文本进行精确评级分类。基于大语言模型Qwen1.5-14B-Chat进行低秩适配(LoRA)微调训练得到电力设备诊断大模型Qwen-ElecDiag,结合检索增强生成技术开发设备缺陷诊断助手。此外,整理提供微调电力设备诊断大模型的指令数据集。对比实验结果表明,提出的基于图神经网络的缺陷评级分类方法在准确性上较最优基准模型BERT提升近8个百分点;诊断助手的电力知识以及缺陷诊断能力得到提升。通过提高缺陷评级的准确率并提供全面专业化诊断建议,不仅提高电力设备运维的智能化水平,也为其他垂直领域的智能运维提供新的解决方案。

基于智能电表数据的低压配电网拓扑与线路参数联合辨识

在低压配电网中,用户频繁地扩建和改接导致台账存在信息更新滞后、数据缺失等问题,难以获取当前运行状态下的拓扑及线路参数。针对无相角量测信息且含未知数量零注入功率“隐节点”的低压配电网,提出一种基于智能电表数据的低压配电网拓扑与线路参数联合辨识方法。基于低压配电网的电气特性以及辐射状网络的结构特点,推导出一种功率-电压比形式的线性逆潮流模型。通过线性回归求解得到阻抗距离矩阵,再利用无判定阈值形式的改进分组递归算法实现拓扑与线路参数的联合辨识。最后,在IEEE欧洲低压测试馈线和中国南京市某地区的实际低压配电网中对所提算法进行数值仿真,验证了所提算法的有效性。

分布式光伏并网对配电网的影响综述

随着绿色电力的大力发展和新型电力系统的建设,分布式光伏发电系统已经成为未来的重要能源形式之一。由于光伏渗透率的不断提高,分布式光伏电源并网会改变传统的配网潮流结构,对配电网的电能质量、安全保护以及规划等方面产生影响。首先概述了分布式光伏发电系统的发展现状,分析分布式光伏并网的特点以及工作原理。其次,对分布式光伏并网接入配网造成的影响及治理措施进行概述分析和总结。最后期望为分布式光伏电源接入高渗透率的可再生能源配电系统的快速发展提供参考。

基于自适应时间步脉冲神经网络的高效图像分类

脉冲神经网络(Spiking neural network,SNN)由于具有相对人工神经网络(Artifcial neural network,ANN)更低的计算能耗而受到广泛关注.然而,现有SNN大多基于同步计算模式且往往采用多时间步的方式来模拟动态的信息整合过程,因此带来了推理延迟增大和计算能耗增高等问题,使其在边缘智能设备上的高效运行大打折扣.针对这个问题,本文提出一种自适应时间步脉冲神经网络(Adaptive timestep improved spiking neural network,ATSNN)算法.该算法可以根据不同样本特征自适应选择合适的推理时间步,并通过设计一个时间依赖的新型损失函数来约束不同计算时间步的重要性.与此同时,针对上述ATSNN特点设计一款低能耗脉冲神经网络加速器,支持ATSNN算法在VGG和ResNet等成熟框架上的应用部署.在CIFAR10、CIFAR100、CIFAR10-DVS等标准数据集上软硬件实验结果显示,与当前固定时间步的SNN算法相比,ATSNN算法的精度基本不下降,并且推理延迟减少36.7%~58.7%,计算复杂度减少33.0%~57.0%.在硬件模拟器上的运行结果显示,ATSNN的计算能耗仅为GPU RTX 3090Ti的4.43%~7.88%.显示出脑启发神经形态软硬件的巨大优势.

基于6LoWPAN的物联网寻址策略研究

在6LoWPAN(IPv6 over Low-power Wireless Personal Area Network)的基础上,该文提出应用于物联网的寻址策略,实现基于IEEE 802.15.4协议的底层异构网络与互联网的实时通信。寻址策略包括IPv6地址自动配置和报头压缩。采用的分层地址自动配置策略,首先在底层网络内部允许节点使用16位短地址导出的链路本地地址进行数据分组传输,该链路本地地址需通过执行基于分簇的重复地址检测机制保证唯一性;其次,每个底层网络中的Sink节点通过上层IP路由器获取全球路由前缀,并与接口标识符相结合,形成Sink节点的全球地址,实现底层网络与互联网的数据交换。同时,通过在报头压缩编码中植入链路本地地址和全球地址控制位,提出了一种适用于物联网应用的报头压缩方案IIPHC(IoTs IPv6 Header Compression)。如果地址类型为链路本地地址,则采用简单灵活的IIPHC1方案,如果地址类型为全球地址,则采用相对复杂但有效的IIPHC2方案。仿真及测试结果表明,基于6LoWPAN的物联网寻址策略在网络开销、时延、吞吐量、能耗等性能方面存在一定的优越性。

计及激励型需求响应的低压配电网混合储能优化配置

分布式光伏高比例接入和再电气化与电能替代加剧了系统源、荷的波动性,传统低压配电网规划方法难以适应新型电力系统发展的要求。针对此问题,首先建立了计及激励型需求响应的低压配电网混合储能优化配置模型,然后,根据不同时间尺度下的储能设备和激励型需求侧响应资源的特点,提出运用改进的变分模态分解算法(variational mode decomposition,VMD)对净负荷曲线进行多尺度分解和组合重构,以系统总成本和有功功率波动值之和最小为目标,运用改进的鲸鱼优化算法对所提的优化配置模型进行求解。最后,通过算例验证所提方案的有效性。

考虑热动态的综合能源系统碳排放流建模与分析

在电力系统低碳转型背景下,传统的源侧碳排放控制难以满足碳排放责任公平分摊需求,亟需对多能源网络进行碳排放流(即碳流)追踪,明确源网荷碳排放责任。基于此,提出了热网准动态碳流模型,并对综合能源系统碳流进行建模与分析。介绍了热网静态碳流的管道计算模型;从热损耗和热延时两方面对热网管道的动态特性进行描述;在此基础上,引入热网管道储能变量刻画2种情况下热动态特性对管道和节点碳流分布的影响;进一步地,提出了热电联产机组的碳势计算方法和储能设备各时刻平均碳势的计算方法,并总结了电、热网络碳流联合分析方法;通过算例分析了静态和准动态热网模型下综合能源系统的碳流分布结果,并考虑了负荷热惯性及机组碳势对碳流分布的影响。

空地一体化网络服务连续性保障的低功耗通信与控制联合优化方法

空地一体化网络(AGIN)充分利用了空中基站(ABSs)灵活部署的特点,为热点地区提供了按需覆盖与高质量服务。然而,空中基站的高动态性使得网络的服务连续性难以保障。而且,空中基站能量受限,提升服务连续性和降低功耗通常又对应不同的飞行动作,因此,低功耗的服务连续性保障尤为困难。针对上述问题,该文基于联邦深度强化学习(FDRL)提出了一种面向低功耗服务连续性保障的通信与控制联合优化方法。所提方法通过联合优化空中基站的移动控制、用户关联和功率分配来保障网络服务的连续性。针对空中基站的高动态性,通过在所提方法中设计了环境状态经验池来利用信道的时空相关性,并在奖励函数中引入速率方差来保障网络服务连续性。考虑到不同飞行动作的功耗差异,所提方法通过优化空中基站的飞行动作来降低网络功耗。仿真结果说明,该文所提算法在满足用户速率需求和速率方差需求的前提下,能够减小网络功耗,并且所提联邦深度强化学习的性能接近中心式强化学习的性能。

含高比例分布式电源配电网分布式供电恢复方法

针对高比例分布式电源(DG)接入配电网,现有供电恢复方法未充分考虑DG故障穿越特性。文中提出了基于分布式控制的配电网多阶段供电恢复方法,以充分利用DG的电网支撑能力。分析了DG故障穿越特性及其电网支撑能力,并基于高比例DG接入后配电网不同运行方式,提出了负荷容量估算方法和DG分类处理策略。建立了分布式控制的供电恢复模型,并基于联络线路容量裕度指标提出多联络路径选择策略。最后,提出了适应高比例DG接入配电网的多阶段供电恢复方案。所提方法可以更好地发挥DG支撑作用,提高快速供电恢复能力。仿真算例验证了所提方法的有效性。

基于虚拟阻抗的低压配电网拓扑识别方法

当前拓扑识别技术难以反映潮流特性对拓扑识别的影响,基于配电网现有量测数据,通过分析节点间的电气距离,提出了虚拟阻抗的概念。将节点间具备电气意义的且与电气距离成正相关的连续变量定义为虚拟阻抗,并提出了一种基于虚拟阻抗的低压配电网拓扑识别方法。首先,构建以节点间虚拟阻抗为因变量的多元线性回归方程。然后,通过岭回归计算每一个单相电表与关口电表构成的回归方程的虚拟阻抗,根据计算结果快速判别出拓扑关系异常的电气设备。最后,建立基于导数动态时间弯曲(derivative dynamic time warping,DDTW)距离的校验模型,重新构建得到电气设备的正确拓扑关系,实现低压配电网拓扑关系的修正。以实际的低压配电网台区样本数据为依据,验证了所提方法的有效性。

LoRa信号干扰分析与性能研究

LoRa(Long Range radio)系统在当前不断发展的低功率广域网(LPWAN)中处于相对领先地位。它的MAC层采用的是基于ALOHA的接入协议。该接入机制虽然简单易实现,但同时也容易加剧冲突和碰撞的发生,降低整个系统的通信性能。因此,需要研究多个终端同时占用信道资源时的相互干扰情况,而LoRa信号的扩频因子(SF)将决定信号的通信覆盖范围。因此,分析了干扰信号的SF与发送信号的SF相同以及不同时,干扰信号对发送信号解调性能的影响。实验结果表明,相同SF信号间的干扰影响相对较大,而干扰信号使用的SF与发送信号不同时,干扰的影响相对较小。通过理论分析,获得了接收端正确解调时所要求的信干比(SIR)。可见,不同SF的LoRa信号可看作伪正交。

考虑供电能力提升的低压配电网柔性互联规划

构建具有可靠供电能力的低压配电网具有重要意义,然而低压配电网供电能力受到低压配电变压器负载、低压配电网新能源消纳能力以及低压配电网供电电压3大要素影响。因此,该文基于低压配电网柔性互联技术提出考虑供电能力提升的低压配电网柔性互联规划方法,通过抽取影响低压配电网供电能力的主要场景建立低压配电网柔性互联规划框架。另外,针对该文多主体规划运行模型的不确定性,采用信息间隙决策理论(information gap decision theory,IGDT)与基于Wasserstein距离的分布鲁棒方法进行精细化建模。最后,采用MATLAB和CPLEX求解器在IEEE 38节点配电网上进行算例分析。仿真结果表明,该规划方法在有效提升低压配电网供电能力的同时具有更好的经济性。