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    • 3. 发明申请
    • Reduced-latency soft-in/soft-out module
    • 降低延迟软启/退出模块
    • US20020021770A1
    • 2002-02-21
    • US09848778
    • 2001-05-03
    • Peter A. BeerelKeith M. ChuggGeorgios D. DimouPhunsak Thiennviboon
    • H03D001/00H04L027/06
    • H03M13/3905H03M13/2957H03M13/3966H03M13/6572
    • Decoding an encoded signal (for example, a turbo encoded signal, a block encoded signal or the like) is performed by demodulating the received encoded signal to produce soft information, and iteratively processing the soft information with one or more soft-in/soft-output (SISO) modules. At least one of the SISO modules uses a tree structure to compute forward and backward state metrics. More generally, iterative detection is performed by receiving an input signal corresponding to one or more outputs of a module whose soft-inverse can be computed by running the forward-backward algorithm on a trellis representation of the module, and determining the soft inverse of the module by computing forward and backward state metrics of the received input signal using a tree structure.
    • 通过解调接收到的编码信号以产生软信息来对编码信号(例如,turbo编码信号,块编码信号等)进行解码,并且利用一个或多个软/软编码信号迭代地处理软信息, 输出(SISO)模块。 至少有一个SISO模块使用树结构来计算前向和后向状态度量。 更一般地,通过接收与模块的一个或多个输出相对应的输入信号来执行迭代检测,该模块的软反转可以通过在模块的网格表示上运行前向后向算法来计算,并且确定 模块,通过使用树结构计算所接收的输入信号的前向和后向状态度量。
    • 5. 发明授权
    • Method of and apparatus for implementing fast orthogonal transforms of variable size
    • 用于实现可变大小的快速正交变换的方法和装置
    • US07870176B2
    • 2011-01-11
    • US11176149
    • 2005-07-07
    • Doron SolomonGilad Garon
    • Doron SolomonGilad Garon
    • G06F17/14
    • H03M13/4169G06F17/142H03M13/1105H03M13/2957H03M13/39H03M13/3966H03M13/41H03M13/4107H03M13/4146H03M13/6508H03M13/6511H03M13/6513H03M13/6516H03M13/6561
    • A reconfigurable architecture for and method of performing a fast orthogonal transform of vectors in multiple stages, the size of a vector being N, wherein N can vary and the number of stages is a function of N, the architecture comprising: a computational unit configured and arranged so as to include one or more butterfly units; a block including one or more multipliers coupled to the output of the computational unit, configured and arranged so as to perform all of the butterfly computations for at least one stage of the transform; a storage unit configured and arranged so as to store the intermediate results of the butterfly computations and predetermined coefficients for use by the computational unit for performing each butterfly computation, the storage unit including memory and multiplexing architecture; the storage unit including memory and multiplexing architecture; a multiplexer unit configured and arranged so as to time multiplex all of the butterfly computations of the transform using said computation unit for the one stage so that only one computation unit is required for the stage; and a controller configured and arranged so as to provide coefficients to the computational unit, and control the sizes of memory and multiplexing architecture in the storage unit; wherein the multipliers' coefficients, the coefficients of the computational unit, the sizes of memories, and multiplexing architecture, for each stage are modified as a function of the value of N. The architecture can be implemented as an integrated chip, and used in communication devices.
    • 一种用于执行多级向量的快速正交变换的可重构架构和方法,所述向量的大小为N,其中N可以变化,并且级数是N的函数,所述架构包括:计算单元,其被配置和 布置成包括一个或多个蝴蝶单元; 包括耦合到所述计算单元的输出的一个或多个乘法器的块,被配置和布置成为所述变换的至少一个阶段执行所有蝴蝶计算; 存储单元,被配置和布置为存储蝶形计算的中间结果和预定系数,供计算单元用于执行每个蝶式运算,该存储单元包括存储器和复用结构; 所述存储单元包括存储器和复用架构; 多路复用器单元,其被配置和布置为使用所述一级的所述计算单元对所述变换的所有蝶式计算进行时间复用,使得仅需要一个计算单元用于所述级; 以及控制器,其被配置和布置为向所述计算单元提供系数,并且控制所述存储单元中的存储器和复用架构的大小; 其中每个级的乘法器系数,计算单元的系数,存储器的大小和复用架构被修改为N的值的函数。架构可以被实现为集成芯片,并且用于通信 设备。
    • 7. 发明授权
    • Reduced-latency soft-in/soft-out module
    • 降低延迟软启/退出模块
    • US07197691B2
    • 2007-03-27
    • US10875979
    • 2004-06-24
    • Peter A. BeerelKeith M. ChuggGeorgios D. DimouPhunsak Thiennviboon
    • Peter A. BeerelKeith M. ChuggGeorgios D. DimouPhunsak Thiennviboon
    • H03M13/03
    • H03M13/3905H03M13/2957H03M13/3966H03M13/6572
    • Decoding an encoded signal (for example, a turbo encoded signal, a block encoded signal or the like) is performed by demodulating the received encoded signal to produce soft information, and iteratively processing the soft information with one or more soft-in/soft-output (SISO) modules. At least one of the SISO modules uses a tree structure to compute forward and backward state metrics. More generally, iterative detection is performed by receiving an input signal corresponding to one or more outputs of a module whose soft-inverse can be computed by running the forward-backward algorithm on a trellis representation of the module, and determining the soft inverse of the module by computing forward and backward state metrics of the received input signal using a tree structure.
    • 通过解调接收到的编码信号以产生软信息来对编码信号(例如,turbo编码信号,块编码信号等)进行解码,并且利用一个或多个软/软编码信号迭代地处理软信息, 输出(SISO)模块。 至少有一个SISO模块使用树结构来计算前向和后向状态度量。 更一般地,通过接收与模块的一个或多个输出相对应的输入信号来执行迭代检测,该模块的软反转可以通过在模块的网格表示上运行前向后向算法来计算,并且确定 模块,通过使用树结构计算所接收的输入信号的前向和后向状态度量。
    • 9. 发明授权
    • Maximum likelihood detector and/or decoder
    • 最大似然检测器和/或解码器
    • US07263652B2
    • 2007-08-28
    • US10867216
    • 2004-06-14
    • Oleg ZaboronskiAndrei Vityaev
    • Oleg ZaboronskiAndrei Vityaev
    • H03M13/03
    • H03M13/6572H03M13/395H03M13/3966H03M13/3972H03M13/41H03M13/4107
    • A maximum likelihood detector receiving a data stream corresponding to ideal values which may include noise, and outputting information specifying a sequence of states of maximum likelihood selected from possible states corresponding to the data stream according to weighting value selections made by the processors, the ideal values being determined by the possible states, including: a pre-processor to obtain first weighting values; processors in a hierarchy, each processor in a select level of the hierarchy is programmed to use, respectively, a plurality of the weighting values to calculate subsequent weighting values indicating respective likelihoods that a section of the data stream values corresponds to each of a plurality of possible state sequences, for each possible initial state and each possible final state, to select further weighting value of highest likelihood corresponding to a state sequence from the initial state to the final state.
    • 接收对应于可能包括噪声的理想值的数据流的最大似然检测器,并且根据由处理器进行的加权值选择,输出指定从对应于数据流的可能状态中选择的最大似然状态序列的信息,理想值 由可能的状态确定,包括:获得第一加权值的预处理器; 层级中的处理器,层次结构的选择级别中的每个处理器被编程为分别使用多个加权值来计算指示相应似然性的后续加权值,即数据流值的一部分对应于多个 对于每个可能的初始状态和每个可能的最终状态,可能的状态序列选择对应于从初始状态到最终状态的状态序列的最高似然度的进一步权重值。
    • 10. 发明申请
    • Maximum likelihood detector and/or decoder
    • 最大似然检测器和/或解码器
    • US20050044474A1
    • 2005-02-24
    • US10867216
    • 2004-06-14
    • Oleg ZaboronskiAndrei Vityaev
    • Oleg ZaboronskiAndrei Vityaev
    • H03M13/41H03M13/03
    • H03M13/6572H03M13/395H03M13/3966H03M13/3972H03M13/41H03M13/4107
    • A maximum likelihood detector receiving a data stream corresponding to ideal values which may include noise, and outputting information specifying a sequence of states of maximum likelihood selected from possible states corresponding to the data stream according to weighting value selections made by the processors, the ideal values being determined by the possible states, including: a pre-processor to obtain first weighting values; processors in a hierarchy, each processor in a select level of the hierarchy is programmed to use, respectively, a plurality of the weighting values to calculate subsequent weighting values indicating respective likelihoods that a section of the data stream values corresponds to each of a plurality of possible state sequences, for each possible initial state and each possible final state, to select further weighting value of highest likelihood corresponding to a state sequence from the initial state to the final state.
    • 接收对应于可能包括噪声的理想值的数据流的最大似然检测器,并且根据由处理器进行的加权值选择,输出指定从对应于数据流的可能状态中选择的最大似然状态序列的信息,理想值 由可能的状态确定,包括:获得第一加权值的预处理器; 层级中的处理器,层次结构的选择级别中的每个处理器被编程为分别使用多个加权值来计算指示相应似然性的后续加权值,即数据流值的一部分对应于多个 对于每个可能的初始状态和每个可能的最终状态,可能的状态序列选择对应于从初始状态到最终状态的状态序列的最高似然度的进一步权重值。