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    • 1. 发明申请
    • SMOOTH TRANSITION BETWEEN PREDICTIVE AND MOBILE-ASSISTED SPECTRAL ALLOCATION
    • 预测和移动辅助频谱分配之间的平滑过渡
    • US20170055266A1
    • 2017-02-23
    • US15345901
    • 2016-11-08
    • EMPIRE TECHNOLOGY DEVELOPMENT LLC
    • Arvind Vijay Keerthi
    • H04W72/04H04B17/373H04L5/00
    • H04B17/373H04B17/318H04L5/0007H04L5/0032H04L5/006H04L5/0096
    • Technologies are generally described for providing a transition between predictive and mobile-assisted spectral allocation. In some examples, wireless devices may be enabled to determine adequacy of their allocated spectral path to meet their communication needs by analyzing signal-to-noise ratios (SNRs) of their assigned sub-carriers. If a wireless device determines a current sub-carrier to be inadequate based on the analysis, d may send information associated with preferred sub-carriers to a base station. The base station may determine one or more nearby good clusters based on a comparison of a sequence of received preferred sub-carriers and the spectral paths represented by the nearby duster centers, and select a re-allocated spectral path with shortest information distance to the sequence of preferred sub-carriers.
    • 通常描述技术用于提供预测和移动辅助频谱分配之间的转换。 在一些示例中,无线设备可以通过分析其分配的子载波的信噪比(SNR)来确定其分配的频谱路径的充分性以满足其通信需求。 如果无线设备基于分析确定当前子载波不足,则d可以向基站发送与优选子载波相关联的信息。 基站可以基于接收到的优选子载波的序列与由附近的除尘器中心表示的频谱路径的比较来确定一个或多个附近的良好群集,并且选择具有到该序列的最短信息距离的重新分配的频谱路径 的优选子载体。
    • 3. 发明授权
    • Predictive spectral allocation in mobile networks
    • 移动网络中的预测频谱分配
    • US09572165B2
    • 2017-02-14
    • US14833082
    • 2015-08-22
    • EMPIRE TECHNOLOGY DEVELOPMENT LLC
    • Arvind Vijay Keerthi
    • H04W72/04H04L5/00H04B17/373
    • H04W72/048H04B17/373H04L5/0007H04L5/006H04W72/042H04W72/044H04W72/0446H04W72/0453
    • Technologies are generally described for discerning patterns in the “goodness” or “badness” of time-frequency slots to allow predictive allocation of spectral resources that may be appropriate for a wireless user. According to some examples, information on device location, time slots, sub-carrier(s) allotted for each time slot, and quality indicators may be received from mobile devices. The time slots may be grouped by location to form analysis intervals. A time-frequency vector may then be identified for each analysis interval and a unit of geographic grid. A “goodness” indicator may be computed for each time-frequency vector. Clusters of time-frequency vectors may be categorized for each analysis interval and associated unit of geographic grid such that mobile devices can be assigned “good” clusters through sub-carrier allocation.
    • 通常描述技术用于在时间 - 频率时隙的“良好”或“不良”中识别模式,以允许可能适合于无线用户的频谱资源的预测分配。 根据一些示例,可以从移动设备接收关于每个时隙分配的设备位置,时隙,子载波的信息以及质量指示符。 时隙可以按位置分组以形成分析间隔。 然后可以针对每个分析间隔和地理网格的单位来识别时间 - 频率向量。 可以为每个时间 - 频率矢量计算“良好”指标。 可以针对每个分析间隔和相关联的地理网格单位对时间 - 频率向量的群进行分类,使得移动设备可以通过子载波分配被分配为“良好的”群集。
    • 4. 发明授权
    • Resolving spectral allocation conflicts in mobile networks
    • 解决移动网络中的频谱分配冲突
    • US09320052B2
    • 2016-04-19
    • US14354112
    • 2013-06-24
    • Empire Technology Development LLC
    • Arvind Vijay Keerthi
    • H04W72/12H04L5/00
    • H04W72/1226H04L5/00H04L5/0007H04L5/0037H04L5/006H04L5/0073
    • Technologies are generally described for reducing spectral allocation conflicts in wireless networks. In some examples, two (or more) wireless devices with intersecting spectral allocation may be identified, followed by determination of one or more time-frequency vectors of the spectral allocation for one of the wireless devices that have a first overlap with one or more time-frequency vectors of the spectral allocation of the other wireless device. For each determined time-frequency vector, an alternate time-frequency vector may be determined such that a second overlap between the alternate time-frequency vector and the time-frequency vectors of the other wireless device is lower than the first overlap. The alternate time-frequency vector may be transmitted to the wireless device to enable that device shift its communication to the alternate time-frequency vector for enhanced communication performance.
    • 通常描述了用于减少无线网络中的频谱分配冲突的技术。 在一些示例中,可以识别具有相交频谱分配的两个(或多个)无线设备,随后确定与一个或多个时间具有第一重叠的无线设备之一的频谱分配的一个或多个时间 - 频率向量 - 其他无线设备的频谱分配的频率向量。 对于每个确定的时间 - 频率向量,可以确定交替的时间 - 频率向量,使得另一无线设备的交替时间 - 频率向量与时间 - 频率向量之间的第二重叠低于第一重叠。 可以将替代时间 - 频率向量发送到无线设备,以使该设备将其通信转移到备选的时间 - 频率向量,以增强通信性能。
    • 7. 发明申请
    • RESOLVING SPECTRAL ALLOCATION CONFLICTS IN MOBILE NETWORKS
    • 在移动网络中解决光谱分配冲突
    • US20150271703A1
    • 2015-09-24
    • US14354112
    • 2013-06-24
    • Empire Technology Development LLC
    • Arvind Vijay Keerthi
    • H04W28/04H04W72/04
    • H04W72/1226H04L5/00H04L5/0007H04L5/0037H04L5/006H04L5/0073
    • Technologies are generally described for reducing spectral allocation conflicts in wireless networks. In some examples, two (or more) wireless devices with intersecting spectral allocation may be identified, followed by determination of one or more time-frequency vectors of the spectral allocation for one of the wireless devices that have a first overlap with one or more time-frequency vectors of the spectral allocation of the other wireless device. For each determined time-frequency vector, an alternate time-frequency vector may be determined such that a second overlap between the alternate time-frequency vector and the time-frequency vectors of the other wireless device is lower than the first overlap. The alternate time-frequency vector may be transmitted to the wireless device to enable that device shift its communication to the alternate time-frequency vector for enhanced communication performance.
    • 通常描述了用于减少无线网络中的频谱分配冲突的技术。 在一些示例中,可以识别具有相交频谱分配的两个(或多个)无线设备,随后确定与一个或多个时间具有第一重叠的无线设备之一的频谱分配的一个或多个时间 - 频率向量 - 其他无线设备的频谱分配的频率向量。 对于每个确定的时间 - 频率向量,可以确定交替的时间 - 频率向量,使得另一无线设备的交替时间 - 频率向量与时间 - 频率向量之间的第二重叠低于第一重叠。 可以将替代时间 - 频率向量发送到无线设备,以使该设备将其通信转移到备选的时间 - 频率向量,以增强通信性能。
    • 8. 发明申请
    • PREDICTIVE SPECTRAL ALLOCATION IN MOBILE NETWORKS
    • 移动网络中的预测频谱分配
    • US20140293955A1
    • 2014-10-02
    • US14123199
    • 2013-06-24
    • Empire Technology Development LLC
    • Arvind Vijay Keerthi
    • H04W72/04
    • H04W72/048H04B17/373H04L5/0007H04L5/006H04W72/042H04W72/044H04W72/0446H04W72/0453
    • Technologies are generally described for discerning patterns in the “goodness” or “badness” of time-frequency slots to allow predictive allocation of spectral resources that may be appropriate for a wireless user. According to some examples, information on device location, time slots, sub-carrier(s) allotted for each time slot, and quality indicators may be received from mobile devices. The time slots may be grouped by location to form analysis intervals. A time-frequency vector may then be identified for each analysis interval and a unit of geographic grid. A “goodness” indicator may be computed for each time-frequency vector. Clusters of time-frequency vectors may be categorized for each analysis interval and associated unit of geographic grid such that mobile devices can be assigned “good” clusters through sub-carrier allocation.
    • 通常描述技术用于在时间 - 频率时隙的“良好”或“不良”中识别模式,以允许可能适合于无线用户的频谱资源的预测分配。 根据一些示例,可以从移动设备接收关于每个时隙分配的设备位置,时隙,子载波的信息以及质量指示符。 时隙可以按位置分组以形成分析间隔。 然后可以针对每个分析间隔和地理网格的单位来识别时间 - 频率向量。 可以为每个时间 - 频率矢量计算“良好”指标。 可以针对每个分析间隔和相关联的地理网格单位对时间 - 频率向量的群进行分类,使得移动设备可以通过子载波分配被分配为“良好的”群集。
    • 10. 发明授权
    • Predictive spectral allocation in mobile networks
    • 移动网络中的预测频谱分配
    • US09204448B2
    • 2015-12-01
    • US14123199
    • 2013-06-24
    • Empire Technology Development LLC
    • Arvind Vijay Keerthi
    • H04W72/04
    • H04W72/048H04B17/373H04L5/0007H04L5/006H04W72/042H04W72/044H04W72/0446H04W72/0453
    • Technologies are generally described for discerning patterns in the “goodness” or “badness” of time-frequency slots to allow predictive allocation of spectral resources that may be appropriate for a wireless user. According to some examples, information on device location, time slots, sub-carrier(s) allotted for each time slot, and quality indicators may be received from mobile devices. The time slots may be grouped by location to form analysis intervals. A time-frequency vector may then be identified for each analysis interval and a unit of geographic grid. A “goodness” indicator may be computed for each time-frequency vector. Clusters of time-frequency vectors may be categorized for each analysis interval and associated unit of geographic grid such that mobile devices can be assigned “good” clusters through sub-carrier allocation.
    • 通常描述技术用于在时间 - 频率时隙的“良好”或“不良”中识别模式,以允许可能适合于无线用户的频谱资源的预测分配。 根据一些示例,可以从移动设备接收关于每个时隙分配的设备位置,时隙,子载波的信息以及质量指示符。 时隙可以按位置分组以形成分析间隔。 然后可以针对每个分析间隔和地理网格的单位来识别时间 - 频率向量。 可以为每个时间 - 频率矢量计算“良好”指标。 可以针对每个分析间隔和相关联的地理网格单位对时间 - 频率向量的群进行分类,使得移动设备可以通过子载波分配被分配为“良好的”群集。