Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter Communication System

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the AmBC.Novel Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.

LoRa Backscatter Network Efficient Data Transmission Using RF Source Range Control

Networks based on backscatter communication provide wireless data transmission in the absence of a power source.A backscatter device receives a radio frequency(RF)source and creates a backscattered signal that delivers data;this enables new services in battery-less domains with massive Internet-of-Things(IoT)devices.Connectivity is highly energy-efficient in the context of massive IoT applications.Outdoors,long-range(LoRa)backscattering facilitates large IoT services.A backscatter network guarantees timeslot-and contention-based transmission.Timeslot-based transmission ensures data transmission,but is not scalable to different numbers of transmission devices.If contention-based transmission is used,collisions are unavoidable.To reduce collisions and increase transmission efficiency,the number of devices transmitting data must be controlled.To control device activation,the RF source range can be modulated by adjusting the RF source power during LoRa backscatter.This reduces the number of transmitting devices,and thus collisions and retransmission,thereby improving transmission efficiency.We performed extensive simulations to evaluate the performance of our method.

Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

Non-Orthogonal Multiple Access(NOMA)has emerged as a novel air interface technology for massive connectivity in Sixth-Generation(6G)era.The recent integration of NOMA in Backscatter Communication(BC)has triggered significant research interest due to its applications in low-powered Internet of Things(IoT)networks.However,the link security aspect of these networks has not been well investigated.This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system.Our system model takes into account the simultaneous operation of NOMA IoT users and the Backscatter Node(BN)in the presence of multiple EavesDroppers(EDs).The EDs in the surrounding area can overhear the communication of Base Station(BS)and BN due to the wireless broadcast transmission.Thus,the chief aim is to enhance link security by optimizing the BN reflection coefficient and BS transmit power.To gauge the performance of the proposed scheme,we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes.Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without the BC and conventional orthogonal multiple access schemes in terms of system secrecy rate.

反向散射通信技术的研究与发展

反向散射通信作为物联网部署的重要技术手段,其主要思想是利用入射信号进行低功耗被动通信和能量收集,以期实现物联网节点的能源自持。为了加深对该技术的认识并推动相关领域的发展,对现有研究展开综述并对未来发展进行展望。首先,阐述了反向散射通信的基本原理及架构演进。其次,针对不同的通信架构,对已有工作进行了综述。在此基础上,给出了融主被动传输的互惠共生反向散射通信架构,并进行了初步的研究和仿真分析。最后,结合已有研究探讨了所提通信架构的未来研究方向。

基于用户窃听的MU-MISO反向散射通信系统鲁棒资源分配算法

针对反向散射通信系统信道估计不准、信息容易被窃听等问题,该文提出一种基于用户窃听的多用户-多输入单输出(MU-MISO)反向散射通信系统鲁棒资源分配算法,以提高系统传输鲁棒性与信息安全性。首先,考虑基站最大功率、时间分配、信道不确定性、能量收集和保密率等约束,建立一个MU-MISO的反向散射通信系统鲁棒资源分配问题。其次,基于非线性能量收集模型和有界球形信道不确定性模型,利用变量松弛法和S过程将原NP-hard问题转化为确定性问题,随后利用连续凸近似、半正定松弛与块坐标下降法将其转化为凸优化问题求解。仿真结果表明,与传统非鲁棒算法对比,所提算法具有较高的系统容量和较低的中断概率。

HR3C奥氏体耐热钢晶界蠕变损伤的电子背散射衍射分析

对不同条件下的HR3C奥氏体耐热钢蠕变试样进行性能测试和微观结构观察,研究奥氏体耐热不锈钢蠕变沿晶破坏行为和损伤特征。电子背散射衍射(EBSD)分析结果表明,不同蠕变速度下材料的晶粒尺寸基本不变,未产生择优取向,但高蠕变速度条件下部分孪晶界演变成一般晶界,而低蠕变速度下原始孪晶结构基本保持不变。EBSD分析结果清楚地反映了微观蠕变应变的不均匀性。沿晶微裂纹和蠕变空洞的产生和扩展是最显著的损伤特征,这些损伤现象与不同蠕变速度下的蠕变机制及晶界性质密切相关。

基于硬件损伤的认知反向散射通信网络鲁棒安全资源分配算法

为了提高反向散射通信网络频谱效率、传输鲁棒性及信息安全性,该文提出一种基于硬件损伤的认知反向散射通信网络鲁棒安全资源分配算法。首先,考虑认知反向散射用户的最小安全速率、传输时间、能量收集和反射系数等约束,基于有界信道不确定性和频谱感知误差模型,建立一个多变量耦合的吞吐量最大化非凸资源分配问题。其次,利用最坏准则、连续凸近似和交替优化方法,将原问题转换为凸优化问题,并提出一种基于迭代的鲁棒资源分配算法。仿真结果表明,与现有算法对比,所提算法具有较好的鲁棒性。

移动场景下反向散射混合多址算法研究

随着移动物联网的发展,在移动场景下实现高速、低功耗的信息传递具有重要研究价值。反向散射通信作为一种低功耗的通信技术可以解决功耗与能量供应问题。NOMA(非正交多址接入)是实现高频谱效率的技术,基于用户之间信道增益差进行配对通信,但是当用户信道增益差过小时,会产生强干扰进而严重影响性能,而采用OMA(正交多址接入)可以降低干扰。针对移动场景中因信道增益频繁变化而导致的性能降低以及能量供应问题,构建了移动场景下反向散射混合多址系统模型,提出反向散射设备在移动场景中使用NOMA或OMA的动态阈值,以最大化复用NOMA提升速率,剩余设备则采用OMA,并在此基础上提出最佳信道增益差配对算法。仿真结果表明,在移动场景中相较于传统方法,和速率、中断概率、复用用户数都有显著提高,在小型无人机、无人船等方面具有应用价值。

反向散射中基于载波索引的混合NOMA方案

基于功率域非正交多址的环境反向散射通信系统上行链路常通过距离差完成用户配对。无源反向散射系统的双重信道衰落,导致远端边缘设备无法满足通信所需功率或解码所需信干噪比(Signal-to-Interference-Noise Ratio,SINR)约束。为了解决上述问题,提出一种OFDM和具有索引调制(Index Modulation,IM)的OFDM混合的上行NOMA方案,该方案由标签调制方案和反射系数调节方案组成。OFDM-IM提供了更好的能量效率,可以使功率水平低的设备满足通信条件。反向散射设备(Backscatter Devices,BD)根据接收到的功率水平,灵活地选择OFDM或者OFDM-IM,并在功率域叠加;通过调节反射系数保证叠加信号的功率差,接收机利用功率电平来执行多用户检测。实验结果表明,该方能够有效地提高远端用户解码的成功率,并且解码用户数量的增加提高了系统容量。

基于Sentinel-1时序数据的山地冰川表面消融变化研究--以老虎沟12号冰川为例

冰川是影响气候变化的主要因素,合成孔径雷达(SAR)不仅具有较高空间分辨率和多极化等特点,而且对冰雪融化引起的介电常数变化较为敏感,已成为山地冰川表面消融变化监测的重要数据源。基于Sentinel-1时序数据,提出了一种综合应用多时相多极化SAR变化检测算法和Sigmoid函数的冰川表面消融监测方法。以祁连山老虎沟12号冰川为研究区,利用“中心线-圆”方法获得的冰川东、西支64个样区,通过各点2019-2020年124个时相的SAR后向散射系数变化特征确定了7个典型样区及2019和2020年冰川消融期;基于同轨道参考影像与多时相融雪影像对比,分别获得变化监测影像VV和VH极化后向散射系数,对其进行权重组合后提取湿雪像元;通过Sigmoid函数并结合湿雪平均海拔高度提取干雪,从而得到2年冰川消融期内16个时相的冰川表面干湿雪分布。利用2019年09月01日无人机数字正射影像(DOM)以及与Sentinel-1邻近日期5景Sentinel-2影像对提取结果进行精度验证,并结合冰川上气象站点气温和降水数据对误差结果进行深入分析。实验结果表明,该方法能够有效提取冰川表面干、湿雪分布,总体分类精度OA高达96%,Kappa系数高达0.84。老虎沟12号冰川消融期及覆盖各类型消融变化规律存在年际变化:2019年冰川的消融期为5月初至9月中下旬,2020年的消融期为6月中下旬至9月初;2019年从消融季开始,冰川表面干雪面积迅速减小,而湿雪与冰川冰面积在整个消融期均较大,但随着强降雪出现,干雪面积骤然上升,2020年冰川冰和湿雪面积变化明显,冰川冰面积持续增加,湿雪面积持续减小,而干雪面积在高海拔区趋于稳定。

实时输出视频的水下主动偏振成像

针对在水下主动偏振成像方法中,需要机械旋转相机前的检偏器获取正交偏振态图像,导致无法实时输出去后向散射视频的问题,提出了实时输出视频的水下主动偏振成像方法。首先,本方法将正交偏振切换位置从相机端更换到光源端,而相机端的检偏器偏振状态保持不变,并论证了此改变并不影响去后向散射的效果;然后,设计了阵列正交偏振光源,即光源由偏振态正交的两组LED灯珠交错排列组成,通过独立的驱动电路分别控制两组灯珠,输出偏振态正交的偏振光,从硬件上取消了偏振态切换的机械结构;第三,设计了同步控制装置,分别控制光源输出的偏振态和相机拍照,实现了正交偏振态图像数据的采集;最后,通过流水线式主动偏振图像处理方法,实现实时的视频输出。实验结果表明,本方法可以实时输出去后向散射视频,且在去后向散射性能上,与机械式主动偏振成像方法性能接近,两者去后向散射性能的背离度均低于4%,图像EME值增长倍数最大可达17.96。本方法具有结构简单、成本低、输出帧频不受影响以及相机选择性多等优点,能够广泛应用在水下成像领域。

空间引力波星载望远镜测试与评估技术研究进展

在空间引力波探测任务中,星载望远镜承担太空超长干涉光路双向光束准直的重要作用。空间引力波探测对星载望远镜提出了pm级光程稳定性和低于10^(-10)级后向杂散光水平的极高要求。超高水平指标要求超过了当前测试技术的精度极限,因此,针对星载望远镜发展测试与评估技术并开展系统超高精度测试是空间引力波探测计划成功的重要前提。本文在概述国内外在研的空间引力波探测星载望远镜研制情况的基础上,重点围绕星载望远镜的核心技术指标——光程稳定性和后向杂散光,介绍了在研望远镜的测试技术发展现状和已经取得的部分测试成果,以及各研究单位进一步的测试计划,为我国的空间引力波探测的星载望远镜测试与评估技术发展提供参考。

光子带隙光纤背向散射次波建模及实验验证

光子带隙光纤有着独特的结构形式、传输介质和导光机制,这使其具有传统光纤无法比拟的优点,是未来光纤陀螺的理想选择。但光子带隙光纤粗糙的纤芯内壁导致其产生强烈的背向散射次波,会使光子带隙光纤陀螺产生额外的非互易误差。为了定量分析光子带隙光纤背向散射次波强度大小,论文基于电偶极子辐射理论建立了一种简单的光子带隙光纤背向散射次波理论模型。通过聚焦离子束微纳加工法和原子力显微镜测量得到了准确的纤芯内壁表面形貌功率谱密度,进而计算得到HC-1550-02型光子带隙光纤背向散射系数理论值为2.61×10^(-9)/mm。通过光频域背向反射散射仪得到HC-1550-02型光子带隙光纤背向散射系数测量值为~1.82×10^(-9)/mm,初步验证了背向散射次波模型的正确性,为背向散射次波抑制技术研究奠定了基础。

基于多维度声学特征优选的多波束海底底质分类

海底表层底质分布信息的准确获取在构建海洋基础地理数据库中发挥着重要作用。目前,多波束是实现大范围海底底质分类的有效手段之一,基于多波束测深和反向散射强度数据所派生的声学特征被广泛应用于底质分类建模。然而,随着特征维度的增加,特征空间中存在的无关和冗余特征严重影响底质分类精度。为了定量评估声学特征对底质类别的表征能力,并消除无效特征对分类结果的干扰,本文提出了基于多维度声学特征优选的海底底质分类方法。首先,结合实际底质样本的物理属性对多维特征进行排序和优选,排除冗余和无关特征。其次,分别应用支持向量机、随机森林和深度信念网络构建海底底质监督分类模型。通过利用爱尔兰海南部多波束调查数据和实地取样信息进行试验,结果表明提出方法对海底底质的总体分类精度和Kappa系数分别最高达到了86.20%和0.834,相较于主成分分析和熵指标特征选择方法有明显提高,突出了该方法在海底底质探测及制图的应用潜力。

基于单向测量超声背散射系数的晶粒尺寸评价高效方法

镍基高温合金GH4742具有优异的机械性能,而晶粒尺寸是影响其性能的关键因素.基于物理模型的超声背散射法可以实现晶粒尺寸高效和准确的评价,但受限于复杂模型或多角度声束测量.因此,本文提出了一种只需单向测量的背散射系数法,且无需考虑测量系统等无关因素的影响.基于独立散射模型,推导了只与材料相关的背散射系数;利用空间相关函数描述了晶粒尺寸与背散射系数的关系;采用参考信号剔除干扰因素的影响,实现实验背散射系数的快速提取.制备三组不同晶粒尺寸的GH4742试块进行相控阵超声实验和平均晶粒尺寸评价,并与金相法结果进行对比.结果表明本文方法得到的晶粒度与金相法结果最大相对误差为–22.7%,最小相对误差为–3.7%.

Link Budget and Enhanced Communication Distance for Ambient Internet of Things

Backscatter communications will play an important role in connecting everything for beyond 5G(B5G)and 6G systems.One open challenge for backscatter communications is that the signals suffer a round-trip path loss so that the communication distance is short.In this paper,we first calculate the communication distance upper bounds for both uplink and downlink by measuring the tag sensitivity and reflection coefficient.It is found that the activation voltage of the envelope detection diode of the downlink tag is the main factor limiting the back-scatter communication distance.Based on this analysis,we then propose to implement a low-noise amplifier(LNA)module before the envelope detection at the tag to enhance the incident signal strength.Our experimental results on the hardware platform show that our method can increase the downlink communication range by nearly 20 m.

智能反射面增强的全双工环境反向散射通信系统波束成形算法

当前传统环境反向散射通信存在双重衰落、障碍物阻挡和网络容量有限的问题。智能反射面(RIS)作为6G的关键候选技术因能够主动改善信号传输质量、提升通信系统传输性能而备受关注。为此,该文将RIS与全双工技术引入到环境反向散射通信系统,研究了考虑硬件损伤与RIS离散相移的RIS增强全双工环境反向散射通信系统波束成形算法。首先,考虑反射节点最小能量收集与服务质量约束、功率站最大发射功率约束和RIS相移约束,建立了总发射功率最小的波束成形优化问题。然后,利用交替优化、半正定松弛、变量替换、半正定规划将原非凸问题转化成可求解的凸优化问题。最后,仿真结果表明,所提算法比传统波束成形方法平均功耗降低了7.8%。

基于多尺度纹理特征的海底底质样本增强方法

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