Abstract:
A composite baseband signal includes a desired signal component modulated according to a first modulation scheme and an interfering signal component modulated according to a second modulation scheme. Information is recovered from the composite signal by applying a phase rotation associated with the second modulation scheme to the composite signal to generate a rotated signal. Based on the rotated signal, a channel model associated with the desired signal component and interference cancelling filter coefficients associated with the interfering signal component are generated. The rotated signal is filtered according to the interference cancelling filter coefficients to suppress the interfering signal component from the rotated signal. The filtered signal is equalized based on branch metrics derived from the channel model and symbol hypotheses rotated in accordance with a difference in phase rotations associated with the first and second modulations to recover information from the desired signal component.

Description:
BACKGROUND 
       [0001]    The present invention generally relates to interference suppression, and particularly relates to demodulating a desired signal while suppressing an interfering signal having a different modulation. 
         [0002]    Some wireless communication systems employ several modulation schemes for transmitting information. The modulation scheme used to communicate information over a particular channel depends on several factors such as the degree of channel interference and noise. Generally, a higher-capacity modulation scheme is used to convey information when noise and interference levels are relatively low. For example, Enhanced Data rates for GSM Evolution (EDGE) based systems utilize a modulation scheme such as 8PSK (or possibly an even higher-order modulation scheme such as 16-QAM or 32-QAM) when noise and interference levels are sufficiently low. However, GMSK is used to convey information when noise and interference levels are high. EDGE-based systems transmit information at the same symbol rate regardless of modulation type, but 8PSK provides a 3× data density improvement over GMSK because 8PSK encodes three bits of information per symbol compared to one bit for GMSK. 
         [0003]    The GMSK modulation transmits one bit per symbol interval. In a commonly used model for the GMSK signal in GSM/EDGE, the bit is modulated using +1 or −1 (or phases of 0 and 180 degrees), but the phase of the signal is progressively shifted by pi/2 for each symbol interval. In a similar fashion, the 8PSK modulation in GSM/EDGE uses one of eight phases (0, pi/4, pi/2, 3pi/4 and their negative counterparts) to encode three bits of information, while progressively applying a phase shift of 3pi/8 per symbol interval. The phase shift applied to each signal helps shape the signal characteristics to be more suitable for amplification purposes, whereas the different phase shifts applied to GMSK and 8PSK help in distinguishing the two signals for the purposes of blindly detecting the modulation used in a particular frame. 
         [0004]    While 8PSK modulation provides increased data density, GMSK modulated signals are less susceptible to error in high noise and interference environments because the phase and amplitude difference representing adjacent symbols is greater for GMSK than for 8PSK or QAM. Thus, EDGE communication systems tend to transmit information over highly disadvantaged channels using GMSK while 8PSK or QAM is used for less disadvantaged channels. 
         [0005]    Mobile terminals operating in an EDGE or similar environment are subject to noise and co-channel interference, i.e., interference arising from other communication channels in the same or different cell. EDGE-based systems conventionally employ a Single Antenna Interference Cancellation (SAIC) technique for suppressing co-channel interference when both the interfering signal and desired signal are modulated according to GMSK. However, in many instances, the interfering signal does not have the same modulations as the desired signal. SAIC is not effective at cancelling co-channel interference when the desired and interfering signals have different modulations. For example, SAIC is ineffective at suppressing an interfering GMSK-modulated signal when the desired signal is modulated according to 8PSK. Other interference suppression techniques account for modulation differences, but require a highly complex equalizer and calculation of pre-filter coefficients separate from channel response estimation. 
       SUMMARY 
       [0006]    According to the methods and apparatus taught herein, a composite baseband signal includes a desired signal component modulated according to a first modulation scheme and an interfering signal component modulated according to a second modulation scheme. When received, the signal is rotated in accordance with the rotation of the modulation of the interfering signal. The resultant signal is filtered and, depending on the filter coefficients, either the real or imaginary part of the filtered signal is extracted to suppress the interfering signal. Symbol estimates are then determined from the filtered signal by using an equalizer that uses postulates for the desired symbols that account for the difference in rotation between the modulation of the desired signal and the modulation of the interfering signal. 
         [0007]    According to one embodiment, information is recovered from the composite signal by applying a phase rotation associated with the second modulation scheme to the composite signal to generate a rotated signal. Based on the rotated signal, a channel model associated with the desired signal component and interference cancelling filter coefficients associated with the interfering signal component are generated. The rotated signal is filtered according to the interference cancelling filter coefficients to suppress the interfering signal component from the rotated signal. The filtered signal is equalized based on branch metrics derived from the channel model and symbol hypotheses rotated in accordance with a difference in phase rotations associated with the first and second modulations to recover information from the desired signal component. 
         [0008]    Of course, the present invention is not limited to the above features and advantages. Those skilled in the art will recognize additional features and advantages upon reading the following detailed description, and upon viewing the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0009]      FIG. 1  is a block diagram of an embodiment of a wireless terminal that suppresses interference based on the modulation scheme of the interfering signal. 
           [0010]      FIG. 2  illustrates an embodiment of processing logic for suppressing interference based on the modulation scheme of the interfering signal. 
           [0011]      FIG. 3  is a block diagram of another embodiment of a wireless terminal that suppresses interference based on the modulation scheme of the interfering signal. 
       
    
    
     DETAILED DESCRIPTION 
       [0012]      FIG. 1  illustrates an embodiment of a wireless terminal  100  such as a mobile phone or wireless communications base station including a front end processor  102 , baseband processor  104  and post processor  106 . The front end processor  102  filters and down-converts a received composite signal r(t) to yield a composite baseband signal r(n). The composite baseband signal r(n) includes a desired signal component s(n) modulated according to a first modulation scheme and an interfering signal component i(n) modulated according to a second modulation scheme. In one embodiment, the desired signal component s(n) is modulated according to 8PSK and the interfering signal i(n) is modulated according to GMSK. In other embodiments, the desired signal component s(n) is modulated according to an even higher-capacity modulation scheme such as 16-QAM or 32-QAM. Regardless, the baseband processor  104  applies a rotation to the signal r(n) in accordance with the modulation of the interferer. The baseband processor  104  then filters the resultant signal to suppress the interference and determines symbol estimates from the filtered signal. The post processor  106  performs various signal processing operations on the symbol estimates, such as error correction decoding. 
         [0013]    In more detail, the baseband processor  104  includes a signal rotator  108 . The rotator  108  applies a phase rotation associated with the modulation scheme of the interfering signal component i(n) to the composite baseband signal r(n) to generate a rotated signal t(n), e.g., as illustrated by Step  200  of  FIG. 2 . When the desired signal component s(n) has 8PSK modulations and the interfering signal component i(n) has GMSK modulations, the composite baseband signal is given by: 
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         [0000]    where h(k) represents the channel encountered by s(n), g(k) represents the channel encountered by i(n), and w(n) represents noise. Note that h(k) and g(k) include contributions from the radio channel and the transmit and receive filters used. 
         [0014]    The rotator  108  applies a progressive phase rotation of 
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         [0000]    to the composite baseband signal when the interfering signal component i(n) has GMSK modulations. The rotator output t(n) is thus given by: 
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         [0015]    Of course, a different phase rotation may be applied to the composite baseband signal when the interfering signal component i(n) has a modulation scheme other than GMSK. Regardless, the composite baseband signal r(n) is rotated such that the resulting signal t(n) has a first portion 
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         [0000]    corresponding to the desired signal component s(n) and a second portion 
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         [0000]    corresponding to the interfering signal component i(n). The second portion of the rotated signal consists of a real signal i(n) passed through a complex filter g(k). An aptly chosen complex interference cancelling filter  110  may be applied to the rotated baseband signal t(n) to project substantially all of the interference along the imaginary axis. Then, by taking the real part of the resultant signal z(n), suppression of the interfering signal component is achieved, e.g., as illustrated by Step  204  of  FIG. 2 . The filter output z(n) is given by: 
         [0000]        z ( n )= t ( n )* p ( n )  (5) 
         [0000]    where p(n) represents the filter coefficients, * denotes the convolution operation, and the real part of z(n) ideally has no contribution from the interfering signal component i(n). In another embodiment, the receiver  100  selects the interference cancelling filter p(n) so that the interference is projected along the real axis instead of the imaginary axis. According to this embodiment, the imaginary part of the filter output is then taken for further processing instead of the real part. 
         [0016]    Either way, the filter coefficients p(n) along with a channel response estimate d(n) associated with the desired signal component s(n) are generated by a coefficient estimator  112 , e.g., as illustrated by Step  202  of  FIG. 2 . Ideally, the filter coefficients p(n) and channel response d(n) are determined by taking either the real or imaginary part of the filter output z(n) using a signal extractor  114 . For example, the signal extractor  114  takes the real part of z(n) when the interference is projected along the imaginary axis as given by: 
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         [0000]    where x(n) is the extractor output, p(n) is complex, and d R (n) as well as d l (n) are real. Also, * denotes the convolution operation. The signal extractor  114  may be implemented separately from the interference cancelling filter  110  as shown in  FIG. 1 . In another embodiment, the signal extractor  114  is implemented as part of the filter  110  as shown by  FIG. 3 . Either way, the filter coefficients p(n) and channel response d(n) may be determined using known training sequences periodically transmitted to the wireless terminal  100 . 
         [0017]    In one embodiment, the training sequence information is used to jointly solve for the filter coefficients p(n) and the channel response coefficients d R (n) and d l (n), thus reducing receiver complexity. For EDGE-based systems, each received slot has a midamble of known symbols. The desired signal component s(n) is known over the midamble sequence and can be used to determine the best values of p(n), d R (n) and d l (n) as solutions that minimize the squared magnitude of the error e(n) as given by: 
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         [0000]    The time delay parameter τ in equation (7) is an appropriately selected delay value that models the delay added by the interference cancelling filter  110  and can be determined as part of the optimization process given by equation (7). The optimization process given by equation (7) can be solved directly or indirectly using an adaptation algorithm such as the LMS or RLS algorithm. 
         [0018]    Further, the number of taps in the resultant channel response d(n) can be chosen to optimize a subsequent equalization algorithm used to determine the values of the desired signal component s(n). Degenerate channel response values may be avoided by setting d R ( 0 ) to one. After the filter coefficients p(n) and channel response coefficients d R (n) and d l (n) are calculated, an equalization process is applied to the signal extractor output x(n) to determine the best estimate of the transmitted symbols associated with s(n). 
         [0019]    In one embodiment, the equalization process is trellis-based. According to this embodiment, an equalizer  116  hypothesizes transmitted symbol values for the desired signal component s(n) to define states on a trellis. The equalizer  116  evaluates the trellis states using a squared error branch metric given by: 
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                   8 
                   ) 
                 
               
             
           
         
       
     
         [0000]    where x(n) is the signal extractor output when the interference is projected along the imaginary axis and M corresponds to the length of the modified channel response vector d(n), e.g., as illustrated by Step  206  of  FIG. 2 . Thus, the equalizer  116  hypothesizes un-rotated symbol values for s(n) to determine trellis states, but hypothesizes rotated symbol values ŝ(n−k) using the difference in rotation present in the modulation scheme for the desired signal and that applied by rotator  108  to determine the best estimate of the transmitted symbols, i.e., the best trellis states. For example, the rotated symbol hypothesis values ŝ(n−k) have the phase rotation given by equation (4) when the interfering signal component i(n) has GMSK modulations. This way, the phase rotation performed by the rotator  108  for projecting the interfering signal i(n) away from the desired signal s(n) is undone by the equalizer  116  during the symbol estimation process. 
         [0020]    In one embodiment, the equalizer  116  is MLSE-based. In another embodiment, the equalizer  116  is DFSE-based. When the equalizer  116  is DFSE-based, the appropriate phase rotation, e.g., as indicated by equation (4) for GMSK interference and an 8PSK desired signal is applied to past decisions of the desired signal component s(n). Otherwise, the phase rotation performed by the rotator  108  is not undone during the symbol estimation process. Also, the modified channel response d(n) preferably has most of its energy concentrated in the first few taps when the equalizer  116  is DFSE-based. In one embodiment, this tap condition is accounted for when p(n), d R (n) and d l (n) are jointly calculated by the coefficient estimator  112  as given by equation (7). 
         [0021]    With the above range of variations and applications in mind, it should be understood that the present invention is not limited by the foregoing description, nor is it limited by the accompanying drawings. Instead, the present invention is limited only by the following claims, and their legal equivalents.