Efficient Spectrum(高效光谱)研究综述
Efficient Spectrum 高效光谱 - Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. [1] And in this work, spectroscopic ellipsometry is used to measure the absorption coefficient spectrum of the absorber layer CZTSSe with different sulfur-to-selenium ratio, and wxAMPS numerical simulation software is used to simulate various material properties and draw conclusions. [2] By taking a T-shaped rigid frame bridge as an example, the bilateral pounding model was abstracted, and the earthquake response spectra considering pounding at the bilateral beam ends were studied, including the maximum displacement spectrum, the acceleration dynamic coefficient spectrum, the pounding force response spectrum, and the response spectrum for the number of pounding events. [3] And the R 2 of the prediction model based on the refractive index spectrum is greater than that of the absorption coefficient spectrum. [4] Though the multicarrier technique orthogonal frequency division multiplexing (OFDM) is generous in 4G technology, it suffers with spectrum leakage, inefficient spectrum, and high PAPR. [5] A system configuration design is enabled by developing an analytical model that correlates the objective wave speed with the measurable reflection coefficient spectrum. [6] Moreover, when the peak region of the boundary's spectral irradiation is closer to the peaks of the absorption coefficient spectrum of the condensed phase, the accuracy of both separated and classical FSCK solutions decreases, though, the separated solution still provides better accuracy. [7] By analyzing the convergence of the reflection coefficient spectrum, the critical value of the truncated order of Legendre orthogonal polynomials is determined. [8] Spectrum scarcity and inefficient spectrum using, as well as lack of address, is an important problem in the consumption of resources on the network. [9] Assessment of the first transition point in the reflection coefficient spectrum has successfully predicted the rate of magnitude change caused by different layer thicknesses (e. [10] Simulation and experimental results show that this method can correctly reconstruct the extinction coefficient spectrum under reasonable iteration times. [11] Two peaks occur in the lift coefficient spectrum, with the low frequency corresponding to the vortex shedding frequency in the wake of the flow around the square cylinder and the high frequency corresponding to the traveling wave frequency. [12] A shift by 65 meV in the upper limit of the absorption coefficient spectrum due to a higher inter-band transition has been observed following the processes of post-annealing in air and in vacuum, whereas the process when carried out in a neutral environment the samples keep their band edge as prior to the treatment. [13] Besides, the estimation formulas of local wind pressure spectrum and overall pressure coefficient spectrum of super-large cooling tower under four-tower combination were proposed. [14]提出了智能电网中 ZigBee 认知无线电传感器网络的节能频谱感知算法的合适拓扑。 [1] 并且在本工作中，利用光谱椭偏仪测量了不同硫硒比的吸收层CZTSSe的吸收系数光谱，并利用wxAMPS数值模拟软件模拟了各种材料特性并得出结论。 [2] 以T型刚构桥为例，提取双边冲击模型，研究考虑双边梁端冲击的地震反应谱，包括最大位移谱、加速度动力系数谱、冲击力响应谱，以及冲击事件数量的响应谱。 [3] 并且基于折射率光谱的预测模型的R 2 大于吸收系数光谱的R 2 。 [4] 虽然多载波技术正交频分复用（OFDM）在4G技术中比较大方，但它存在频谱泄漏、频谱效率低和PAPR高的问题。 [5] 通过开发将目标波速与可测量反射系数谱相关联的分析模型，可以实现系统配置设计。 [6] 此外，当边界光谱辐照的峰值区域更接近凝聚相吸收系数光谱的峰值时，分离解和经典 FSCK 解的精度都会降低，但分离解仍然提供更好的精度。 [7] 通过分析反射系数谱的收敛性，确定勒让德正交多项式截断阶的临界值。 [8] 频谱稀缺和频谱使用效率低下，以及地址缺失，是网络资源消耗的一个重要问题。 [9] 对反射系数光谱中第一个过渡点的评估成功地预测了由不同层厚度（例如 [10] 仿真和实验结果表明，该方法可以在合理的迭代次数下正确重构消光系数谱。 [11] 升力系数谱中出现两个峰值，低频对应方柱周围流动的涡旋脱落频率，高频对应行波频率。 [12] 在空气和真空中的后退火过程之后，由于更高的带间跃迁，在吸收系数光谱的上限中观察到了 65meV 的偏移，而在中性环境中进行的过程中，样品保持他们的乐队边缘在治疗前。 [13] 此外，提出了四塔组合下超大型冷却塔局部风压谱和整体压力系数谱的估计公式。 [14]
cognitive radio network
Efficient spectrum sensing is essential for the successful application of the Dynamic Spectrum Assignment (DSA) technology in Cognitive Radio Networks (CRNs). [1] An accurate and efficient spectrum sensing technique is needed to find the spectrum white spaces in a wireless radio environment for cognitive radio networks. [2] Cognitive Radio Network (CRN) is a next generation of wireless communication technology for efficient spectrum utilization. [3] Overcrowded ISM band and inefficient spectrum utilization at a licensed band lead to the development of Cognitive Radio Network. [4] However, a large number of connected devices, as envisioned for the IoT, will create challenges in terms of spectrum scarcity and significant control overhead, which falls into the solution domain of cognitive radio networks (CRNs), since the cognitive radio technology has dynamic spectrum access capability and efficient spectrum utilization [2]. [5] Multi-parameter cognition in a cognitive radio network (CRN) provides a more thorough understanding of the radio environments, and could potentially lead to far more intelligent and efficient spectrum usage for a secondary user. [6] One of the biggest challenges in cognitive radio network (CRN) is efficient spectrum management. [7] Cognitive radio networks (CRNs) are currently a rich area of development because of the promise of solving spectrum access challenges such as spectrum management and efficient spectrum use. [8] Cognitive radio network practices dynamic spectrum access for efficient spectrum utilization. [9] Multi-parameter cognition in a cognitive radio network provides a potential avenue to more efficient spectrum usage. [10] The paper ‘‘Combined Pre-detection and Sleeping for Energy-efficient Spectrum Sensing in Cognitive Radio Networks’’ looks into how to gain additional transmission capacity from the licensed radio frequency spectrum, for massive data transmissions in edge networks, in an energy-efficient manner. [11]高效的频谱感知对于动态频谱分配 (DSA) 技术在认知无线电网络 (CRN) 中的成功应用至关重要。 [1] 需要一种准确有效的频谱感知技术来为认知无线电网络找到无线电环境中的频谱空白空间。 [2] nan [3] nan [4] nan [5] nan [6] nan [7] nan [8] nan [9] nan [10] nan [11]
medium access control
A self-scheduled multichannel-medium access control (SMC-MAC) protocol has been proposed in which the contention and sharing intervals are exploited for the efficient spectrum and energy utilisation. [1] For enabling WSN with cognitive capability to provision IOT requires efficient spectrum access and medium access control (MAC) design. [2] An efficient spectrum access and medium access control (MAC) design is required to enable wireless sensor network (WSN) with cognitive Internet of Things (IoT) that enables presence of sensor network with existing wireless infrastructure. [3]已经提出了一种自调度多通道介质访问控制 (SMC-MAC) 协议，其中利用争用和共享间隔来有效地利用频谱和能量。 [1] 为了使具有认知能力的 WSN 能够提供 IOT，需要有效的频谱访问和媒体访问控制 (MAC) 设计。 [2] 需要有效的频谱访问和介质访问控制 (MAC) 设计来启用具有认知物联网 (IoT) 的无线传感器网络 (WSN)，从而使传感器网络能够与现有的无线基础设施一起存在。 [3]
Energy Efficient Spectrum
This article introduces a novel energy efficient spectrum sensing method for multiple-input multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) systems in dynamic spectrum sharing (DSS) environments. [1] The energy efficient spectrum sensing employing a dedicated smart sensors and virtualized-operated networks for spectrum sensing is given focus in this paper. [2] The proposed fussy clustering protocol is compared with three different protocols: a basic energy efficient protocol, a spectrum aware protocol, and an energy efficient spectrum aware protocol which uses a weighting function. [3] An algorithm is proposed for energy efficient spectrum sharing. [4] The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. [5]nan [1] 本文重点介绍了采用专用智能传感器和虚拟化运营网络进行频谱感知的节能频谱感知。 [2] 将提出的模糊聚类协议与三种不同的协议进行比较：基本节能协议、频谱感知协议和使用加权函数的节能频谱感知协议。 [3] nan [4] nan [5]
Highly Efficient Spectrum 高效光谱
Conclusions falcon is a highly efficient spectrum clustering tool. [1] In smart spectrum, a database is constructed based on the measured data of the radio environment to manage the spectrum, thus realizing highly efficient spectrum utilization, and its usefulness has been confirmed in several systems. [2] CONCLUSIONS falcon is a highly efficient spectrum clustering tool. [3] In order to realize highly efficient spectrum sharing, it is important to accurately recognize the radio environment for the suitable communication parameter setting, and interpolation of the statistical information on the frequency axis can be used. [4]结论 falcon 是一种高效的频谱聚类工具。 [1] 在智能频谱中，基于无线电环境的实测数据构建数据库对频谱进行管理，从而实现频谱的高效利用，其实用性已在多个系统中得到证实。 [2] 结论 falcon 是一种高效的频谱聚类工具。 [3] nan [4]
Provide Efficient Spectrum
Non-orthogonal multiple access (NOMA) and cognitive radio (CR) are two promising technologies that provide efficient spectrum utilization, which is required for future wireless networks to support heterogeneous user requirements. [1] In this paper, we propose to combine cognitive radio (CR) with a biological mechanism called reaction–diffusion to provide efficient spectrum allocation for CIoT. [2] Cognitive radio (CR) technology can provide efficient spectrum utilization and maximize the throughput using dynamic spectrum access technique. [3]非正交多址 (NOMA) 和认知无线电 (CR) 是两种有前途的技术，可提供有效的频谱利用，这是未来无线网络支持异构用户需求所必需的。 [1] 在本文中，我们建议将认知无线电 (CR) 与称为反应扩散的生物机制相结合，为 CIoT 提供有效的频谱分配。 [2] 认知无线电 (CR) 技术可以提供有效的频谱利用，并使用动态频谱接入技术最大限度地提高吞吐量。 [3]
Realize Efficient Spectrum
In the LTE-LAA system, the optimal channel selection and subframe number adjustment are the keys to realize efficient spectrum utilization and fair system coexistence. [1] To realize efficient spectrum utilization in the fact of spectrum scarcity, cognitive radio (CR) is involved in smart grid and generates the cognitive radio enabled smart grid. [2]在LTE-LAA系统中，最优信道选择和子帧数调整是实现频谱高效利用和系统公平共存的关键。 [1] 为了在频谱稀缺的情况下实现频谱的高效利用，认知无线电（CR）参与到智能电网中，产生了认知无线电使能的智能电网。 [2]
An Efficient Spectrum
An efficient spectrum sensing ensures the improvement in throughput of cognitive radio as well as ensures the protection of licensed user from possible interference of unlicensed users. [1] An efficient spectrum access and medium access control (MAC) design is required to enable wireless sensor network (WSN) with cognitive Internet of Things (IoT) that enables presence of sensor network with existing wireless infrastructure. [2]有效的频谱感知可确保认知无线电的吞吐量提高，并确保授权用户免受未授权用户可能的干扰。 [1] 需要有效的频谱访问和介质访问控制 (MAC) 设计来启用具有认知物联网 (IoT) 的无线传感器网络 (WSN)，从而使传感器网络能够与现有的无线基础设施一起存在。 [2]
Achieve Efficient Spectrum
As a typical pattern recognition problem, specific emitter identification (SEI) is a crucial step to achieve efficient spectrum sensing. [1] Results demonstrate that a reasonable number of DCs with efficient content replicas in network design enables to achieve efficient spectrum usage for disaster-resilient cloud services provisioning. [2]作为典型的模式识别问题，特定发射器识别（SEI）是实现高效频谱感知的关键步骤。 [1] nan [2]
efficient spectrum utilization 高效的频谱利用
The two prime elements that govern future wireless communications are energy efficiency and efficient spectrum utilization. [1] Improper resource provisioning causes fragmentation in the network spectrum, which leads to inefficient spectrum utilization. [2] Recently, many technologies proved their potentials to invoke efficient spectrum utilization. [3] Cognitive Radio Networks (CRNs) promise efficient spectrum utilization by operating over the unused frequencies where Vehicular Ad-hoc Networks (VANETs) facilitate information exchanging among vehicles to avoid accidents, collisions, congestion, etc. [4] The growing number of mobile users is causing spectrum scarcity; and hence, an efficient spectrum utilization method is required. [5] Additionally, non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) are presented to achieve a promising multiplexing gain as well as to address the inefficient spectrum utilization incurred with OMA schemes. [6] Article history: Received: 29 November, 2020 Accepted: 21 January, 2021 Online: 05 February, 2021 Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. [7] In smart spectrum, a database is constructed based on the measured data of the radio environment to manage the spectrum, thus realizing highly efficient spectrum utilization, and its usefulness has been confirmed in several systems. [8] The limited coexistence capabilities of current Internet of Things (IoT) wireless standards produce inefficient spectrum utilization and mutual performance impairment. [9] The proposed SUFELF construction can discover a lot of applications in designs for S band, efficient spectrum utilization in cognitive radio networks (CRN). [10] The accuracy of the empirical propagation model plays a critical role in the optimal planning of the television white space (TVWS) network and contributes to efficient spectrum utilization. [11] In this context, efficient spectrum utilization is one of the key enablers to extract the residual network capacity. [12] The main goal of MC-DLMA is to find an optimal access policy to transmit on those pre-allocated channels and expedite more efficient spectrum utilization. [13] This sensor network designed embedding CR technology is termed as Cognitive Radio Sensor Networks (CRSN) which overcomes the limitations of conventional WSNs by providing dynamic access mechanisms to accomplish efficient spectrum utilization. [14] The massive increase in the utilization of mobile devices and communication networks has increased the requirement of massive connectivity and efficient spectrum utilization. [15] As an effort to calm down these adverse impacts, an underwater cognitive acoustic network-based spectrum decision strategy is proposed in this paper to aid in efficient spectrum utilization and allocation by multiple acoustic systems in the underwater environment. [16] Active radio access network (RAN) infrastructure sharing has emerged as a promising solution for efficient spectrum utilization, capital and operational cost savings, improved MVNO penetration rates and lower broadband retail prices in both emerging and developed markets. [17] The need for flexible radio systems that enable efficient spectrum utilization is becoming increasingly urgent to optimize the use of spectrum and telecommunication infrastructure支配未来无线通信的两个主要因素是能源效率和有效的频谱利用。 [1] 资源配置不当会导致网络频谱碎片化，从而导致频谱利用率低下。 [2] 最近，许多技术证明了它们在调用有效频谱方面的潜力。 [3] 认知无线电网络 (CRN) 通过在车辆自组网络 (VANET) 促进车辆之间的信息交换以避免事故、碰撞、拥堵等的未使用频率上运行来保证有效的频谱利用。 [4] 越来越多的移动用户导致频谱稀缺；因此，需要一种有效的频谱利用方法。 [5] 此外，提出了非正交多址 (NOMA) 和空分多址 (SDMA) 以实现有希望的多路复用增益以及解决 OMA 方案导致的低效频谱利用问题。 [6] 文章历史： 收到： 2020 年 11 月 29 日 接受： 2021 年 1 月 21 日 在线： 2021 年 2 月 5 日 调制类型分类是采用频谱共享场景（如动态频谱访问）所需的波形估计的一部分，可以更有效地利用频谱。 [7] 在智能频谱中，基于无线电环境的实测数据构建数据库对频谱进行管理，从而实现频谱的高效利用，其实用性已在多个系统中得到证实。 [8] 当前物联网 (IoT) 无线标准的有限共存能力导致频谱利用效率低下和相互性能损害。 [9] 所提出的 SUFELF 结构可以在 S 波段设计中发现许多应用，在认知无线电网络 (CRN) 中有效地利用频谱。 [10] 经验传播模型的准确性在电视空白空间 (TVWS) 网络的优化规划中起着至关重要的作用，并有助于有效地利用频谱。 [11] 在这种情况下，有效的频谱利用是提取剩余网络容量的关键因素之一。 [12] MC-DLMA 的主要目标是找到一个最佳接入策略以在这些预先分配的信道上传输并加快更有效的频谱利用。 [13] 这种设计嵌入CR技术的传感器网络被称为认知无线电传感器网络（CRSN），它通过提供动态接入机制来实现有效的频谱利用，克服了传统WSN的局限性。 [14] 移动设备和通信网络利用率的大幅提高，对海量连接和高效频谱利用提出了更高要求。 [15] 为了缓解这些不利影响，本文提出了一种基于水下认知声学网络的频谱决策策略，以帮助水下环境中多个声学系统有效地利用和分配频谱。 [16] 有源无线接入网络 (RAN) 基础设施共享已成为有效频谱利用、节省资本和运营成本、提高 MVNO 渗透率和降低新兴市场和发达市场的宽带零售价格的有前景的解决方案。 [17] nan [18] nan [19] 非正交多址 (NOMA) 和认知无线电 (CR) 是两种有前途的技术，可提供有效的频谱利用，这是未来无线网络支持异构用户需求所必需的。 [20] 在LTE-LAA系统中，最优信道选择和子帧数调整是实现频谱高效利用和系统公平共存的关键。 [21] nan [22] 为了在频谱稀缺的情况下实现频谱的高效利用，认知无线电（CR）参与到智能电网中，产生了认知无线电使能的智能电网。 [23] 这些包括抗选择性衰落、抗符号间干扰、抗载波间干扰、更有效的频谱利用和更简单的信道均衡。 [24] 另一方面，这些进步要求低功耗物联网的设计成本有限、能耗低、频谱利用率高。 [25] 由于传统电视广播技术的频谱利用率低下，现代无线通信技术的扩展导致频谱稀缺。 [26] 该策略导致有效的频谱利用。 [27] 它保证了高数据速率无线系统的有效频谱利用。 [28] 本文提出了一种在移动网络中有效利用频谱的解决方案。 [29] nan [30] 认知无线电 (CR) 技术可以提供有效的频谱利用，并使用动态频谱接入技术最大限度地提高吞吐量。 [31] 本文提出了一种改进的分组预留多址访问协议，用于分布式认知无线电自组织网络，利用机会/重叠频谱访问方法与主要用户（PU）共享频谱，以解决频谱稀缺和问题。频谱利用效率低下。 [32] 在本文中，我们讨论了一种基于并行多目标遗传算法 (PMOGA) 的方法，用于在认知无线电 (CR) 中有效利用频谱。 [33] 认知无线电被认为是一种有效利用频谱的有前途的技术。 [34] 基站（BS）应随时了解多载波系统中存在的所有用户的不同子载波的信道状况，以实现有效的频谱利用。 [35] 正交频分复用（OFDM）是一种多载波传输，具有很强的抗衰落、高效的频谱利用率和数据传输率。 [36] 本文提出在延迟关键和延迟容忍通信之间非正交共享可用资源，以满足超可靠低延迟通信 (URLLC) 的严格要求，并避免零星 URLLC 流量的基于授权 (GB) 访问的频谱利用效率低下。 [37] 认知无线电 (CR) 技术是有效利用频谱的一种有前途的解决方案，其中 CR 设备或二级用户 (SU) 可以机会性地利用许可信道中可用的空白空间。 [38] 低效的频谱利用迫使人们构建一种称为认知无线电 (CR) 系统的增强型通信范式，该系统通过从过去的经验中学习来动态适应环境。 [39] 有限的可用频谱和低效的频谱利用使得有必要采用动态频谱接入技术。 [40] 路由和频谱分配是 EON 中有效频谱利用的主要问题。 [41] 非正交多址 (NOMA) 和频谱共享 (SS) 是两种新兴的多址技术，用于在未来的无线通信标准中有效利用频谱。 [42] 这两种技术都用于有效地利用频谱，并确保频谱效率的显着提高。 [43] nan [44] nan [45] nan [46] 我们提出了一种频谱交易 (ST) 方案，用于在嵌入弹性光网络 (EON) 的虚拟光网络之间交易频谱，以实现有效的频谱利用和更好的客户服务质量。 [47] nan [48] nan [49] nan [50]
efficient spectrum sensing 高效的频谱传感
As a typical pattern recognition problem, specific emitter identification (SEI) is a crucial step to achieve efficient spectrum sensing. [1] In cognitive networks, efficient spectrum sensing is of great importance for communication of unlicensed secondary users (SU) without interfering with the communication of licensed primary users (PU). [2] Owing to the spectrum scarcity and energy constrained devices in wireless networks arises the demand for an efficient spectrum sensing technique which improves both sensing performance and energy efficiency for cognitive radio networks. [3] The energy detection (ED) of an unknown signal over Nakagami-m fading is considered for analytically modelling local probability of detection at individual SU, termed as efficient spectrum sensing (ESS). [4] To do that efficient spectrum sensing is one of the key jobs at the SUs part. [5] We aim to find an efficient spectrum sensing and leasing scheme for a CVNO in order to maximize its utility in the long run. [6] Effective implementation of CR networks strongly requires devolution of efficient spectrum sensing (SS) techniques. [7] An attempt has been made to implement a transmitter and receiver section for efficient spectrum sensing in cognitive radio environment. [8] This article introduces a novel energy efficient spectrum sensing method for multiple-input multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) systems in dynamic spectrum sharing (DSS) environments. [9] Finally, an energy-efficient spectrum sensing algorithm is proposed, requiring a lower number of cognitive users for a given error bound. [10] Despite the numerous techniques, the existing spectrum sensing techniques tend to fail in rendering an efficient spectrum sensing whenever a hidden terminal problem arises. [11] Despite the numerous spectrum sensing techniques, the existing techniques fail in providing an efficient spectrum sensing whenever a hidden terminal problem arises. [12] Efficient spectrum sensing is essential for the successful application of the Dynamic Spectrum Assignment (DSA) technology in Cognitive Radio Networks (CRNs). [13] An accurate and efficient spectrum sensing technique is needed to find the spectrum white spaces in a wireless radio environment for cognitive radio networks. [14] The energy efficient spectrum sensing employing a dedicated smart sensors and virtualized-operated networks for spectrum sensing is given focus in this paper. [15] Efficient spectrum sensing and sharing are the main functional components of the CR-based IoT. [16] This paper delivers an accurate approximation for adaptive threshold and optimal frame detection algorithms based on the robust multi-taper method aiming at an efficient spectrum sensing in cognitive radio systems. [17] A key challenge in DSA is to perform an efficient spectrum sensing and sharing mechanism. [18] Thus, an efficient spectrum sensing is a primary need of cognitive radio for detection of free channels and licensed users. [19] To achieve a power efficient spectrum sensing the geometry-based localization algorithm is proposed. [20] The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. [21] An efficient spectrum sensing ensures the improvement in throughput of cognitive radio as well as ensures the protection of licensed user from possible interference of unlicensed users. [22] Efficient spectrum sensing can improve the communication network throughput and reduce the possibility of frequency collision. [23] Collaborative sensing also known as cooperative spectrum sensing (CSS) is an efficient spectrum sensing technique to improve the sensing accuracy in cognitive radio (CR). [24] Utilization of directional antennas is a promising solution for efficient spectrum sensing and accurate source localization and tracking. [25] The proposed methods learn the historical spectrum sensing results and help the network to make an energy-efficient spectrum sensing decision. [26] In this paper, we propose an efficient spectrum sensing scheme by taking advantage of the cooperation of satellites and base stations. [27] Therefore, measuring the energy consumption is an important issue for efficient spectrum sensing. [28] The paper ‘‘Combined Pre-detection and Sleeping for Energy-efficient Spectrum Sensing in Cognitive Radio Networks’’ looks into how to gain additional transmission capacity from the licensed radio frequency spectrum, for massive data transmissions in edge networks, in an energy-efficient manner. [29]作为典型的模式识别问题，特定发射器识别（SEI）是实现高效频谱感知的关键步骤。 [1] 在认知网络中，有效的频谱感知对于非授权次要用户（SU）的通信非常重要，并且不会干扰授权主要用户（PU）的通信。 [2] 由于无线网络中的频谱稀缺和能量受限的设备，需要一种有效的频谱传感技术，以提高认知无线电网络的传感性能和能源效率。 [3] Nakagami-m 衰落上未知信号的能量检测 (ED) 被考虑用于对单个 SU 处的局部检测概率进行分析建模，称为有效频谱感测 (ESS)。 [4] 要做到这一点，高效的频谱感知是 SU 部分的关键工作之一。 [5] 我们的目标是为 CVNO 找到一种有效的频谱感知和租赁方案，以便从长远来看最大限度地发挥其效用。 [6] CR 网络的有效实施强烈需要下放有效的频谱感知 (SS) 技术。 [7] nan [8] nan [9] nan [10] 尽管技术众多，但现有的频谱感知技术往往无法在出现隐藏终端问题时提供有效的频谱感知。 [11] 尽管有许多频谱感测技术，但现有技术无法在出现隐藏终端问题时提供有效的频谱感测。 [12] 高效的频谱感知对于动态频谱分配 (DSA) 技术在认知无线电网络 (CRN) 中的成功应用至关重要。 [13] 需要一种准确有效的频谱感知技术来为认知无线电网络找到无线电环境中的频谱空白空间。 [14] 本文重点介绍了采用专用智能传感器和虚拟化运营网络进行频谱感知的节能频谱感知。 [15] 高效的频谱感知和共享是基于 CR 的物联网的主要功能组件。 [16] 本文基于针对认知无线电系统中高效频谱感知的鲁棒多锥度方法，提供了自适应阈值和最优帧检测算法的精确近似。 [17] DSA 的一个关键挑战是执行有效的频谱感知和共享机制。 [18] 因此，有效的频谱感知是认知无线电检测免费信道和许可用户的主要需求。 [19] nan [20] nan [21] 有效的频谱感知可确保认知无线电的吞吐量提高，并确保授权用户免受未授权用户可能的干扰。 [22] nan [23] nan [24] nan [25] nan [26] nan [27] nan [28] nan [29]
efficient spectrum sharing 高效的频谱共享
For a more efficient spectrum sharing performance, a deep learning power control strategy has been developed. [1] Therefore, it is urgent to design efficient spectrum sharing algorithms to support URLLC in 5G and the emerging 6G. [2] Simulations show that there are more than a certain percentage of users who use the TFT strategy, and if users are encouraged to change their sharing strategy on a regular basis, they can provide more efficient spectrum sharing than traditional centralized methods. [3] This paper proposes a zone-based approach referred to as zone-based GrEEn (ZBGrEEn) algorithm, for energy-efficient spectrum sharing (SS) networks. [4] An algorithm is proposed for energy efficient spectrum sharing. [5] In recent years, many researchers focus on a measurement-based spectrum database (SD) that utilizes the actual received power obtained by spectrum sensing as an enabler for an efficient spectrum sharing. [6] Cognitive radio is an efficient spectrum sharing mechanism to solve the contradiction between spectrum shortage and spectrum underutility, where secondary users (SUs) are allowed to access the spectrum licensed to primary users (PUs) in an opportunistic manner. [7] In order to realize highly efficient spectrum sharing, it is important to accurately recognize the radio environment for the suitable communication parameter setting, and interpolation of the statistical information on the frequency axis can be used. [8] For efficient spectrum sharing between noncooperating networks a fast spectrum scan must be implemented. [9] By achieving an efficient spectrum sharing among heterogeneous networks (HetNets), traffic offloading is a promising solution for boosting the capacity of traditional macro-cell networks. [10] Congestion in the RF spectrum is rapidly increasing, which has motivated the need for efficient spectrum sharing techniques. [11] Also, we propose the concept of digitized spectrum assets (DSA) in B-RAN for efficient spectrum sharing and management. [12] In fact, precisely predicting the energy level of the radio spectrum can provide richer information for applications such as characterizing the spectrum trending for earlier anomaly detection and estimating the channel quality for efficient spectrum sharing. [13]为了更有效的频谱共享性能，已经开发了深度学习功率控制策略。 [1] 因此，迫切需要设计高效的频谱共享算法来支持 5G 和新兴 6G 中的 URLLC。 [2] 仿真表明，有超过一定比例的用户使用 TFT 策略，如果鼓励用户定期改变共享策略，可以提供比传统集中式方法更有效的频谱共享。 [3] 本文提出了一种基于区域的方法，称为基于区域的 GrEEn (ZBGrEEn) 算法，用于节能频谱共享 (SS) 网络。 [4] nan [5] nan [6] nan [7] nan [8] nan [9] nan [10] nan [11] nan [12] nan [13]
efficient spectrum management 高效的频谱管理
Therefore, we propose a localized clustering scheme, which aims to provide better stability, scalability, efficient spectrum management, and reduce communication overhead. [1] However, more efficient spectrum management techniques are needed to reduce the congestion and interference caused by spectrum sharing. [2] Efficient spectrum management has always been an important issue due to the scarcity of satellite spectral resource, especially with the ever-increasing broadband demand. [3] As spectrum becomes crowded and spread over wide ranges, there is a growing need for efficient spectrum management techniques that need minimal, or even better, no human intervention. [4] Furthermore, we discuss an architecture for enabling efficient spectrum management and network virtualization in multi-operator 5G networks. [5] Accomplishing this demands efficient spectrum management combined with an optimized provisioning of hardware throughout the entire network life cycle. [6] More agile and efficient spectrum management is one of the key requirements for wireless communication industry. [7] One of the biggest challenges in cognitive radio network (CRN) is efficient spectrum management. [8] In such an environment of the future 5G networks and communication systems, devices such as sensors in this region of the spectrum will assume importance as it inherently provides large bandwidths, efficient spectrum management for deployment of pico-nets over small community areas. [9] Efficient spectrum management is an important issue in satellite communications due to the pervasive growth in wireless communications and the ever-increasing demand by bandwidth-hungry mobile applications. [10]因此，我们提出了一种局部聚类方案，旨在提供更好的稳定性、可扩展性、高效的频谱管理和减少通信开销。 [1] 然而，需要更有效的频谱管理技术来减少频谱共享造成的拥塞和干扰。 [2] 由于卫星频谱资源的稀缺，特别是随着宽带需求的不断增长，有效的频谱管理一直是一个重要的问题。 [3] 随着频谱变得拥挤并分布在很宽的范围内，对无需人工干预的有效频谱管理技术的需求日益增加，甚至更好。 [4] 此外，我们还讨论了在多运营商 5G 网络中实现高效频谱管理和网络虚拟化的架构。 [5] nan [6] 更灵活、更高效的频谱管理是无线通信行业的关键要求之一。 [7] nan [8] nan [9] nan [10]
efficient spectrum usage
Our results show that the proposed system may not perform well in terms of outage performance at the strong user during the cooperative transmission phase, but achieves higher ergodic sum capacity in whole communication process, and enhances efficient spectrum usage, compared with conventional CDRT and orthogonal multiple access systems. [1] The aim of DPS mechanism is to enable an efficient spectrum usage and enhance system capacity via the dynamic coordination of the transmission and the reception over different Base Stations (BSs). [2] Reliable and pristine PLL output frequency beat is of crucial importance for the efficient spectrum usage—and higher-order modulation schemes (at large bandwidths) are required to satisfy the end-users growing hunger for fast data throughput. [3] However, with the increase in the number of CubeSats, CubeSat-enabled communication systems, and many new use cases, new spectrum bands and a more efficient spectrum usage are needed. [4] This paper proposes spectrum sensor-aided DSA system based on a reinforcement learning (RL) algorithm that aims at efficient spectrum usage for IoT network over the incumbent network. [5] Multi-parameter cognition in a cognitive radio network (CRN) provides a more thorough understanding of the radio environments, and could potentially lead to far more intelligent and efficient spectrum usage for a secondary user. [6] Multi-parameter cognition in a cognitive radio network provides a potential avenue to more efficient spectrum usage. [7] Results demonstrate that a reasonable number of DCs with efficient content replicas in network design enables to achieve efficient spectrum usage for disaster-resilient cloud services provisioning. [8] This sharing of hardware effectively reduces cost/size and makes efficient spectrum usage. [9]我们的结果表明，与传统的CDRT和正交多路复用相比，所提出的系统在强用户的协同传输阶段的中断性能方面可能表现不佳，但在整个通信过程中实现了更高的遍历和容量，并提高了频谱利用率。访问系统。 [1] DPS 机制的目的是通过不同基站 (BS) 上的传输和接收的动态协调来实现有效的频谱使用并提高系统容量。 [2] 可靠且原始的 PLL 输出频率节拍对于有效频谱使用至关重要，并且需要更高阶的调制方案（在大带宽下）来满足最终用户对快速数据吞吐量日益增长的渴望。 [3] 然而，随着 CubeSat 数量的增加、支持 CubeSat 的通信系统以及许多新的用例，需要新的频段和更有效的频谱使用。 [4] 本文提出了基于强化学习 (RL) 算法的频谱传感器辅助 DSA 系统，旨在在现有网络上实现物联网网络的有效频谱使用。 [5] nan [6] nan [7] nan [8] nan [9]
efficient spectrum allocation 高效的频谱分配
Constrained by the achievable spectral resolution of single grating used in the WSS, the roll-off bandwidth of optical filter is challenging to improve for the purpose of precise and efficient spectrum allocation. [1] Due to blockchain's distributed storage and credibility, blockchain based dynamic spectrum sharing can achieve flexible, feasible and much more efficient spectrum allocation. [2] We describe some potential sources of inefficiency in spectrum auctions and some negative effects of inefficient spectrum allocation. [3] The proposed scheme acts as a decision support system (DSS), focusing on reducing the channel switching rate, hidden node interferences, and efficient spectrum allocation. [4] For the multi-incumbent scenario, the results show a tradeoff between efficient spectrum allocation and flexibility in spectrum access for our proposed algorithms. [5] To address this issue, this paper proposes an efficient spectrum allocation algorithm which is based on graph coloring technique and combined with analytic hierarchy process so as to meet the requirements of dynamic spectrum allocation to secondary terrestrial users with diversified QoS demands and yet without causing severe inference to primary satellite users. [6] In this paper, we propose to combine cognitive radio (CR) with a biological mechanism called reaction–diffusion to provide efficient spectrum allocation for CIoT. [7] The spectrum scarcity is not the real problem whereas inefficient spectrum allocation and its usage lead to the scarcity. [8] Several efficient spectrum allocation schemes have been proposed in the past which assume that the users are well behaved without any malicious behavior. [9]受限于 WSS 中使用的单光栅可实现的光谱分辨率，光学滤波器的滚降带宽难以提高，以实现精确高效的光谱分配。 [1] 由于区块链的分布式存储和可信性，基于区块链的动态频谱共享可以实现灵活、可行和更高效的频谱分配。 [2] nan [3] nan [4] 对于多现有场景，结果显示了我们提出的算法在有效频谱分配和频谱访问灵活性之间的权衡。 [5] 针对这一问题，本文提出了一种基于图着色技术并结合层次分析法的高效频谱分配算法，以满足地面二次用户的动态频谱分配需求，满足多样化的QoS需求，同时又不会造成严重的干扰。主要卫星用户。 [6] 在本文中，我们建议将认知无线电 (CR) 与称为反应扩散的生物机制相结合，为 CIoT 提供有效的频谱分配。 [7] 频谱稀缺不是真正的问题，而低效的频谱分配及其使用导致了稀缺。 [8] nan [9]
efficient spectrum acces
The proper estimation and detection of primary nodes are important for the energy-efficient spectrum access. [1] To accommodate the data traffic of these low power backscatter devices, an efficient spectrum access mechanism is required. [2] It gives rise to being difficult to effectively eliminate the spectrum interference and fulfill an efficient spectrum access mechanism using the congested frequency band. [3] For enabling WSN with cognitive capability to provision IOT requires efficient spectrum access and medium access control (MAC) design. [4] An efficient spectrum access and medium access control (MAC) design is required to enable wireless sensor network (WSN) with cognitive Internet of Things (IoT) that enables presence of sensor network with existing wireless infrastructure. [5] This article investigates the problem of efficient spectrum access for traffic demands of self-organizing cognitive small-cell networks, using the coalitional game approach. [6]主节点的正确估计和检测对于高能效频谱接入很重要。 [1] 为了适应这些低功率反向散射设备的数据流量，需要一种有效的频谱访问机制。 [2] 导致难以有效消除频谱干扰，难以利用拥塞频段实现高效的频谱接入机制。 [3] 为了使具有认知能力的 WSN 能够提供 IOT，需要有效的频谱访问和媒体访问控制 (MAC) 设计。 [4] 需要有效的频谱访问和介质访问控制 (MAC) 设计来启用具有认知物联网 (IoT) 的无线传感器网络 (WSN)，从而使传感器网络能够与现有的无线基础设施一起存在。 [5] nan [6]
efficient spectrum use 有效的频谱使用
A multichannel transceiver design with low hardware complexity, flexibility and efficient spectrum use intended for Impulse Radio (IR) Ultra-Wideband (UWB) apertures, is proposed in this paper. [1] On the other hand, these technologies allowed low-energy IoT architecture at low cost, low energy usage and efficient spectrum use. [2] Therefore, an intelligent system structure is required for efficient spectrum use. [3] Two innovations multiple access technologies for efficient spectrum use in future wireless communications standards, non-orthogonal multiple access (NOMA) and cognitive radio (CR). [4] Cognitive radio networks (CRNs) are currently a rich area of development because of the promise of solving spectrum access challenges such as spectrum management and efficient spectrum use. [5]本文提出了一种用于脉冲无线电 (IR) 超宽带 (UWB) 孔径的具有低硬件复杂性、灵活性和高效频谱使用的多通道收发器设计。 [1] 另一方面，这些技术以低成本、低能耗和高效频谱使用实现了低能耗物联网架构。 [2] 因此，高效的频谱使用需要智能的系统结构。 [3] nan [4] nan [5]
efficient spectrum splitting
The conjugate prism design and material matching design allow efficient spectrum splitting while introducing minimal beam deflection. [1] The conjugate micro-optics design delivers high-transmission, efficient spectrum splitting with minimum aberration, a low profile, and low-cost fabrication, thus allowing large-scale production of micro-concentrator photovoltaic modules. [2]共轭棱镜设计和材料匹配设计允许有效的光谱分裂，同时引入最小的光束偏转。 [1] 共轭微光学设计提供高透射率、高效光谱分离、最小像差、低剖面和低成本制造，从而允许大规模生产微聚光光伏模块。 [2]
efficient spectrum clustering 高效的频谱聚类
Conclusions falcon is a highly efficient spectrum clustering tool. [1] CONCLUSIONS falcon is a highly efficient spectrum clustering tool. [2]结论 falcon 是一种高效的频谱聚类工具。 [1] 结论 falcon 是一种高效的频谱聚类工具。 [2]