EFFICIENT COMPUTATION OF SOFT SCALING FACTORS FOR LINEAR MULTI-USER DETECTOR
    1.
    发明公开
    EFFICIENT COMPUTATION OF SOFT SCALING FACTORS FOR LINEAR MULTI-USER DETECTOR 审中-公开
    高效计算软件缩放因子用于对用户更加线性检测器

    公开(公告)号:EP2186209A2

    公开(公告)日:2010-05-19

    申请号:EP08794134.0

    申请日:2008-07-30

    IPC分类号: H04B1/707

    摘要: A symbol detector (30) converts initial symbol estimates of received symbols to soft estimates for decoding. The symbol detector (30) computes spreading waveform correlations between a spreading waveform for a symbol of interest and spreading waveforms for one or more interfering symbols. Interference rejection terms are computed by scaling the spreading waveform correlations by corresponding signal powers and compensating for noise. A soft scaling factor for the symbol of interest is computed from the interference rejection terms. The soft scaling factors are then applied to the initial symbol estimates to generate the soft estimates.

    METHODS AND APPARATUS FOR SYMBOL DETECTION VIA REDUCED COMPLEXITY SEQUENCE ESTIMATION PROCESSING
    2.
    发明授权
    METHODS AND APPARATUS FOR SYMBOL DETECTION VIA REDUCED COMPLEXITY SEQUENCE ESTIMATION PROCESSING 有权
    方法及检测用符号顺序的器件由一个估计降低了复杂性

    公开(公告)号:EP2243263B1

    公开(公告)日:2012-01-04

    申请号:EP09711576.0

    申请日:2009-02-18

    IPC分类号: H04L25/03

    CPC分类号: H04L25/03292

    摘要: Teachings presented herein offer the performance advantages of sequence estimation for received signal symbol detection, while simultaneously providing potentially significant reductions in computational overhead. Initial demodulation of a received signal (12) identifies a reduced number of candidate symbol values (24) for all or a subset of a sequence (14) of symbols (16) represented in the received signal (12). A sequence estimation process, e.g., an MLSE process, constrains its state spaces (62-1, 62-2, 62-3) to the reduced number of candidate symbols values (24), rather than considering all possible symbol values.

    A METHOD AND APPARATUS FOR DEMODULATION OF QAM SIGNAL USING SYMBOL-SPECIFIC AMPLITUDE REFERENCE ESTIMATION
    3.
    发明公开
    A METHOD AND APPARATUS FOR DEMODULATION OF QAM SIGNAL USING SYMBOL-SPECIFIC AMPLITUDE REFERENCE ESTIMATION 有权
    解调QAM的方法和设备信号使用符号,特定振幅参考估计

    公开(公告)号:EP2304879A1

    公开(公告)日:2011-04-06

    申请号:EP09766931.1

    申请日:2009-01-29

    IPC分类号: H04B1/707

    摘要: According to the teachings presented herein, 'spreading code' knowledge is used in forming amplitude references for QAM demodulation in a DS-CDMA receiver. Here, 'spreading code' broadly refers to spreading/channelization codes, scrambling codes, or the product of such codes. Further, these teachings apply to any linear DS-CDMA demodulator, such as Rake, Generalized Rake (G-Rake), or chip equalizer, and to nonlinear demodulators that employ linear filtering, such as decision feedback equalizers (DFEs). Advantageously, the determination of symbol-specific amplitude references relies on shared correlation estimates and/or shared combining weights that are common to two or more symbols of interest, thereby significantly reducing processing requirements as compared to the use of symbol-specific impairment correlation estimates.

    A METHOD AND APPARATUS FOR SYMBOL DETECTION VIA REDUCED COMPLEXITY SEQUENCE ESTIMATION PROCESSING
    4.
    发明公开
    A METHOD AND APPARATUS FOR SYMBOL DETECTION VIA REDUCED COMPLEXITY SEQUENCE ESTIMATION PROCESSING 有权
    方法及检测用符号顺序的器件由一个估计降低了复杂性

    公开(公告)号:EP2243263A1

    公开(公告)日:2010-10-27

    申请号:EP09711576.0

    申请日:2009-02-18

    IPC分类号: H04L25/03

    CPC分类号: H04L25/03292

    摘要: Teachings presented herein offer the performance advantages of sequence estimation for received signal symbol detection, while simultaneously providing potentially significant reductions in computational overhead. Initial demodulation of a received signal (12) identifies a reduced number of candidate symbol values (24) for all or a subset of a sequence (14) of symbols (16) represented in the received signal (12). A sequence estimation process, e.g., an MLSE process, constrains its state spaces (62-1, 62-2, 62-3) to the reduced number of candidate symbols values (24), rather than considering all possible symbol values.