会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 31. 发明授权
    • Method and apparatus for puncturing data regions for signals to minimize data loss
    • 用于对数据区域进行穿孔的方法和装置,以最小化数据丢失
    • US09444589B2
    • 2016-09-13
    • US12897107
    • 2010-10-04
    • Kapil BhattadAmir FarajidanaJuan MontojoAlexei Yurievitch Gorokhov
    • Kapil BhattadAmir FarajidanaJuan MontojoAlexei Yurievitch Gorokhov
    • H04L5/00H04L1/00
    • H04L5/0007H04L1/0013H04L1/0068H04L5/0037H04L5/005H04L5/006H04L5/0064
    • Methods and apparatuses are provided that facilitate puncturing codeblocks in resource blocks for muting or transmitting signals of a disparate technology such that the puncturing similarly impacts the codeblocks. Codeblocks can be mapped in order across frequency in a given data symbol before moving to a next data symbol. In this regard, utilizing data resource elements substantially evenly spaced across frequency and across data symbols in a data resource block for transmitting signals of the disparate technology can substantially equalize impact of the puncturing to related codeblocks. In addition, resources can be allocated to legacy devices, devices with bandwidth, data rate, or quality of service requirements, devices of a certain rank or geometry, etc., based at least in part on the puncturing. Moreover, a modulation and coding scheme can be selected for generating codeblocks based at least in part on the puncturing and its effect on performance.
    • 提供了方便和设备,其便于在资源块中打孔代码块,用于对不同技术的信号进行静音或发送,从而使得穿孔类似地影响码块。 在移动到下一个数据符号之前,可以在给定数据符号中的频率上按顺序映射码块。 在这方面,利用数据资源块中的数据资源元素基本均匀地分布在数据资源块中,用于发送不同技术的信号的频率和跨数据符号,可以大大均衡穿孔对相关码块的影响。 此外,至少部分地基于穿孔,资源可以被分配给传统设备,具有带宽,数据速率或服务质量要求的设备,特定等级或几何的设备等。 此外,可以至少部分地基于打孔及其对性能的影响来选择调制和编码方案来生成代码块。
    • 37. 发明授权
    • Two-step joint demapping algorithm for LLR computation of MIMO signal based on sphere decoding
    • 基于球面解码的MIMO信号LLR计算的两步联合解映射算法
    • US08693588B2
    • 2014-04-08
    • US13171915
    • 2011-06-29
    • Michael L. McCloudDung Ngoc DoanAlexei Yurievitch Gorokhov
    • Michael L. McCloudDung Ngoc DoanAlexei Yurievitch Gorokhov
    • H03D1/04
    • H04L25/0328H04L25/03242H04L25/03305H04L25/067H04L27/38
    • Certain aspects of the present disclosure relate to a technique for two-step joint demapping based on sphere decoding for log-likelihood ratio (LLR) computation related to a received multiple-input multiple-output (MIMO) signal. The first step of the proposed algorithm comprises a linear minimum mean square error (LMMSE) based detection to form soft symbol estimates of symbols being transmitted. Then, the LMMSE-based soft symbol estimates can be utilized to form a set of constellation points of a stream interfering to a stream of interest. These candidate constellation points can be then subtracted (canceled) from the received signal to improve the LLR computations of the stream of interest. After the cancellation, the maximum ratio combining (MRC) can be applied to each individual stream to form more refined soft symbol estimates as well as an effective signal-to-noise ratio (SNR) estimate. The refined outputs of the MRC can be utilized to compute LLRs of transmitted bits based on the effective SNR and the refined soft symbol estimates associated with all the candidate constellation points from the set. The LLRs of transmitted bits may be employed by a channel decoder.
    • 本公开的某些方面涉及用于基于与接收的多输入多输出(MIMO)信号相关的对数似然比(LLR)计算的球体解码的两步联合解映射的技术。 所提出的算法的第一步包括基于线性最小均方误差(LMMSE)的检测,以形成被发送的符号的软符号估计。 然后,可以使用基于LMMSE的软符号估计来形成干扰感兴趣的流的流的一组星座点。 然后可以从接收的信号中减去(取消)这些候选星座点,以改善感兴趣的流的LLR计算。 在取消之后,最大比合并(MRC)可以应用于每个单独的流以形成更精细的软符号估计以及有效的信噪比(SNR)估计。 可以利用MRC的精细输出来基于与集合中的所有候选星座点相关联的有效SNR和精细的软符号估计来计算发送比特的LLR。 传输比特的LLR可以由信道解码器采用。
    • 39. 发明授权
    • Adaptive distributed frequency planning
    • 自适应分布式频率规划
    • US08355742B2
    • 2013-01-15
    • US13495774
    • 2012-06-13
    • Alexei Yurievitch GorokhovAvneesh AgrawalNaga BhushanTingfang Ji
    • Alexei Yurievitch GorokhovAvneesh AgrawalNaga BhushanTingfang Ji
    • H04B7/00
    • H04W16/04H04L1/0026
    • Systems and methodologies are described that facilitate employing distributed frequency planning and reuse factor optimization based upon forward link and/or reverse link interference management techniques. An optimal reuse factor for a base station can be determined based upon a metric that evaluates levels of service associated with neighboring base stations. Moreover, a subset of available resource sets can be selected for use by the base station; thus, a base station specific collection of resource sets can be formed through such selection. Further, mappings of each resource set to a set of physical resources can be disseminated in a network or portion thereof. According to another example, frequency hopping can be constrained to use of resources within a resource set (rather than across more than one resource set) as provided in a base station specific hopping pattern.
    • 描述了有助于采用基于前向链路和/或反向链路干扰管理技术的分布式频率规划和重用因子优化的系统和方法。 可以基于评估与相邻基站相关联的服务等级的度量来确定基站的最佳重用因子。 此外,可以选择可用资源集的子集供基站使用; 因此,可以通过这样的选择来形成基站特定资源集合。 此外,每个资源集合对一组物理资源的映射可以在网络或其一部分中传播。 根据另一示例,跳频可以被限制为使用资源集合(而不是跨越多于一个资源集合)的资源,如在基站特定跳频模式中所提供的。
    • 40. 发明申请
    • TWO-STEP JOINT DEMAPPING ALGORITHM FOR LLR COMPUTATION OF MIMO SIGNAL BASED ON SPHERE DECODING
    • 用于基于球面解码的MIMO信号的LLR计算的两步联合解算算法
    • US20120219097A1
    • 2012-08-30
    • US13171915
    • 2011-06-29
    • Michael L. McCloudDung Ngoc DoanAlexei Yurievitch Gorokhov
    • Michael L. McCloudDung Ngoc DoanAlexei Yurievitch Gorokhov
    • H03D1/00
    • H04L25/0328H04L25/03242H04L25/03305H04L25/067H04L27/38
    • Certain aspects of the present disclosure relate to a technique for two-step joint demapping based on sphere decoding for log-likelihood ratio (LLR) computation related to a received multiple-input multiple-output (MIMO) signal. The first step of the proposed algorithm comprises a linear minimum mean square error (LMMSE) based detection to form soft symbol estimates of symbols being transmitted. Then, the LMMSE-based soft symbol estimates can be utilized to form a set of constellation points of a stream interfering to a stream of interest. These candidate constellation points can be then subtracted (canceled) from the received signal to improve the LLR computations of the stream of interest. After the cancellation, the maximum ratio combining (MRC) can be applied to each individual stream to form more refined soft symbol estimates as well as an effective signal-to-noise ratio (SNR) estimate. The refined outputs of the MRC can be utilized to compute LLRs of transmitted bits based on the effective SNR and the refined soft symbol estimates associated with all the candidate constellation points from the set. The LLRs of transmitted bits may be employed by a channel decoder.
    • 本公开的某些方面涉及用于基于与接收的多输入多输出(MIMO)信号相关的对数似然比(LLR)计算的球体解码的两步联合解映射的技术。 所提出的算法的第一步包括基于线性最小均方误差(LMMSE)的检测,以形成被发送的符号的软符号估计。 然后,可以使用基于LMMSE的软符号估计来形成干扰感兴趣的流的流的一组星座点。 然后可以从接收的信号中减去(取消)这些候选星座点,以改善感兴趣的流的LLR计算。 在取消之后,最大比合并(MRC)可以应用于每个单独的流以形成更精细的软符号估计以及有效的信噪比(SNR)估计。 可以利用MRC的精细输出来基于与集合中的所有候选星座点相关联的有效SNR和精细的软符号估计来计算发送比特的LLR。 传输比特的LLR可以由信道解码器采用。