Abstract:
Systems and methods are disclosed for dynamic channel estimation in a digital receiver by performing a dynamic equalization on an incoming signal to compensate for channel distortion; independently estimating one or more channel parameters for the dynamic equalization, wherein the one or more channel parameters track channel change; determining a convolution of the channel parameters and updating the parameters for the dynamic equalization for subsequent processing of incoming signal; and providing an equalized output from the digital receiver.

Description:
BACKGROUND 
       [0001]    The present invention is related to a communication system with digital receiver channel equalization. 
         [0002]    In a digital receiver, dynamic equalization is usually needed to compensate for time-variant channel distortion and eliminate inter-symbol-interference (ISI).  FIG. 1  gives the typical DSP (digital signal processing) elements and procedure. Signal x is input to receiver system  100  and is first fed to pre-processing block  102  which, for example, can be perform sampling rate conversion and fixed channel-effect compensation/pre-equalization, among others. Signal y from block  102 &#39;s output is coupled to dynamic channel equalization  104  which usually uses FIR (Finite Impulse Response) filter. In combination, blocks  102  and  104  form block  110  that performs digital receiver channel equalization. 
         [0003]    Block  104 &#39;s input and output signals (y and z) are also connected to channel estimation block  106  to track for channel changes and update channel parameters for block  104 . Such parameters can be FIR filter coefficients, in case FIR filter is applied in channel equalization block  104 . Channel equalization block  104  then takes the updated parameters to equalize its next input signal. Signal output from  104  is passed to post-processing block  108 . 
         [0004]    However, in some cases due to combined processing, for example pre-processing  102  and channel equalization  104  are merged to processing block  110 , such input signal to channel estimation block  106  will not be available. One example is when dynamic equalization combined with pre-processing in frequency-domain where FFT (Fast Fourier Transform) is applied to the input signal, while channel estimation is still performed in time domain. In such case there must be alternative ways to re-generate the expected input signal. 
         [0005]    Conventional systems may re-generate the expected input by applying de-convolution to the output signal z. Convolution is the DSP operation for two functions f(n) and g(n), producing a third function defined as: 
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         [0006]    For example, f can be input signal, and g can be a FIR filter function. De-convolution can be done using a reverse of estimated channel parameter (i.e., reverse of FIR filter) to do convolution with signal output, which is: 
         [0000]      ( f ( n )* g ( n ))* g   −1 ( n )= f ( n ) 
         [0007]    However, it can be difficult to get the reverse of channel parameters for the above solution. The added complexity in calculating de-convolution may require more powerful hardware which is power hunger. Further, additional errors may be caused when simplifying assumptions or engineering approximations are used. 
       SUMMARY 
       [0008]    Systems and methods are disclosed for dynamic channel estimation in a digital receiver by performing a dynamic equalization on an incoming signal to compensate for channel distortion; independently estimating one or more channel parameters for the dynamic equalization, wherein the one or more channel parameters track channel change; determining a convolution of the channel parameters and updating the parameters for the dynamic equalization for subsequent processing of incoming signal; and providing an equalized output from the digital receiver. 
         [0009]    Implementations of the above aspect may include one or more of the following. The channel parameters can be converted to a rate or a format that matches the dynamic equalization rate or format. The system includes performing sub-level channel estimation. The sub-level channel estimation can use an open loop with the incoming signal. The sub-level equalization uses the dynamic equalization. The channel estimation uses a portion of output signals from the dynamic equalization. The parameter updating comprises combining a pre-existing parameter with newly estimated channel parameters. The combining includes applying a convolution to the pre-existing and new parameters. The convolution outputs can be kept to a predetermined length using truncation such as dropping zero outputs in the truncation. The dynamic equalization and the channel estimation can be done using separate paths. Rate conversion can be applied to the dynamic equalization prior to estimating the channels. The rate conversion can be applied to updated channel parameters prior to the dynamic equalization. The rate conversion can be applied to newly estimated parameters prior to combining with pre-existing parameters. The dynamic equalization is in a frequency domain and the estimating of channel parameters are in a time domain. The conversion of newly estimated parameters to frequency domain can be done prior to combining with pre-existing parameters. The newly estimated parameters and pre-existing parameters can be combined by one-by-one multiplication. The newly estimated parameters can be combined with pre-existing parameters and the combined parameters can be converted to a frequency domain. The dynamic equalization and the estimating of channel parameters can be all done in a frequency domain. One implementation takes dynamic channel equalization block output z as input and applies dynamic equalization solutions such as Constant Modulus Algorithm (CMA) to estimate channel parameters, where channel means all the paths from transmitter output to signal z. The estimated parameters are further processed using convolution with those used in achieving signal z, to have updated parameters as those applied to the dynamic channel equalization block. 
         [0010]    Advantages of the preferred embodiments may include one or more of the following. The system reduces processing complexity which further results in lower cost. The system can provide a solution without knowing the input for the channel estimation block. By treating the signal path from transmitter output all the way to dynamic equalizer&#39;s output as an extended channel, the system can apply channel estimation to this “extended channel” output, which is actually the equalized signal, and uses the estimated channel parameter to update the old one that result in the current output signals. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]      FIG. 1  gives the typical DSP (digital signal processing) receiver system. 
           [0012]      FIG. 2  shows a block diagram of one embodiment of the present invention. 
           [0013]      FIG. 3  shows an exemplary illustration of rate conversion when placed after the actual convolution block. 
           [0014]      FIG. 4  shows an exemplary illustration of rate conversion when placed after the actual before actual convolution block. 
           [0015]      FIG. 5  shows an exemplary flow chart for performing digital receiver channel equalization. 
           [0016]      FIG. 6  shows an example application that includes frequency-domain CD and PMD compensation with time-domain coefficient update. 
       
    
    
     DESCRIPTION 
       [0017]      FIG. 2  shows a block diagram of one embodiment of the present invention. Input signal x is first processed by pre-processing block  202 , which is further coupled to channel equalization block  204 . In one embodiment, channel equalization block  204  is a FIR filter which takes coefficients from extended channel estimation block  210 . Block  210 &#39;s extended channel estimation operation is done by sub-level channel estimation block  214  and FIR coefficient convolution block  216  with a delay block  215 . Sub-level equalization block  212  may also be included if closed-loop channel estimation algorithm is applied. 
         [0018]    Turning now to sub-level channel estimation block  214 , various blind equalization processes can be used, such as CMA (Constant Modulus Algorithm), SWA (Shalvi-Weinstein), training-based processes such as LMS (Least Mean Square), or other suitable techniques can be used. In one embodiment, sub-level channel estimation block  214  can be open-loop processing only, which means it only takes input to calculate the channel parameters (based on signal z). In another embodiment, there is also a sub-level equalization block  212 , whose output is fed into  214  for error calculation and channel parameters update, so that  212  and  214  make a closed-loop for parameter update. 
         [0019]    As to sub-level equalization block  212 , in one embodiment, sub-level equalization block  212  has substantially identical architecture/algorithm as that in dynamic channel equalization block  204 . In another embodiment, dynamic channel equalization block  204  processes in frequency domain which is equivalent to that of time-domain processing in sub-level equalization block  212 . In a further embodiment, the processing of  204  and  212  may be different, in case there is fixed mapping relationship which can be reflected from parameter conversion done in coefficient convolution block  216 . Sub-level equalization block  212  and sub-level channel estimation block  214  may only process a portion of signals from  204 &#39;s output (signal z). 
         [0020]    Referring to coefficient convolution block  216 , block  216  combines the updated parameters from  214  with those used in dynamic channel equalization block  204  to generate new parameters for block  204 . For example, if block  204  and block  212  are both FIR filters, direct convolution operation to the two parameter groups may be applied to generate updated parameters. In implementation complexity, the coefficient length is expected to be constant; however the convolution processing usually results in longer output. So convolution results should be truncated to the expected number. 
         [0021]    In one embodiment, the sampling rate used in block  204  and block  212  may be different. In that case signal output from block  204  might be resampled before feeding into block  212  and block  214 ; also the parameters output from block  214  may be resampled before running convolution with those used in block  204 . Parameters resampling may also be done after convolution block  216 , before feeding into block  204 . 
         [0022]    By treating the signal path from transmitter output all the way to dynamic equalizer&#39;s output as an extended channel, the system of  FIG. 2  can apply channel estimation to this “extended channel” output, which is actually the equalized signal, and uses the estimated channel parameter to update the old one that result in the current output signals. 
         [0023]    One example is given in  FIG. 3 , where block  300  shows the updated parameters processing path. Following actual convolution block  302 , a rate conversion matches the difference between sub-level channel estimation block  214  and dynamic channel estimation block  204 . 
         [0024]    In an alternative embodiment shown in  FIG. 4 , the rate conversion is placed right at input from sub-level channel estimation block  214 . “Delay” block  304  saves the previous parameters for combining with new input. 
         [0025]    In  FIG. 3  and  FIG. 4 , block  308  represents “other conversion”, which for example, can be time-domain to frequency-domain conversion. In one embodiment, if dynamic channel equalization  204  processes in frequency domain and the result parameter from block  214  is in time domain, then coefficient convolution outputs need to be converted to frequency domain before feeding into block  204 . If the output from  204  is still in frequency domain while  214  takes time-domain input signals only, then corresponding frequency-to-time domain signal conversion is also needed for  214  and  212 &#39;s input. Similarly, if both the processing in  204  and the results from  214  are in frequency domain, then the operation in  216  can be direct multiplication of old coefficients and  214 &#39;s output coefficients. Again rate conversion will be needed if there is mismatch between  214 &#39;s output and those used by dynamic channel estimation block  204 . 
         [0026]    Referring now to convolution and truncation, this process uses FIR filter for dynamic channel equalization block  204  as an example, though it is also be applicable to other cases. As mentioned above, if block  216  performs a time-domain convolution, the non-zero results will be more than those needed in block  204 . The system would need to truncate the number of resulting taps, which picks some of the non-zero results while drop the others. It is achieved by using unit vector I (the convolution of I and any function g(n) is still g(n−k), where k is determined by I) as old parameters, to drop the always-zero outputs no matter what the input is. For example, in case of a 13-tap FIR filter in blocks  204  and  214 , when 
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         [0000]    the truncated convolution can be: y(n)=Σ i=0   12 h(n). x(n+i−12), n=0 to 12, n=0 to 12, where y(n) is truncated convolution output, h(n) as old coefficients and x(n) as new input, or vice versa. 
         [0027]    In case initially the channel parameter is unknown, in one embodiment, the coefficient to be applied to dynamic channel equalizer  204  is set to unit vector I, which is used when deciding which convolution results are to be dropped. 
         [0028]      FIG. 5  shows an exemplary flow chart for performing digital receiver channel equalization. The process includes signals equalization operations  510  and channel estimation operations  520 . After system initialization, signals equalization  510  takes signal input ( 512 ) and equalizes the signal using provided parameters ( 514 ) where after system initialization, the parameters are initialized using provided pre-configured value; while during normal operation where inputs from channel estimation processing  520  are available, the process uses parameters from  520 . This procedure is executed repeatedly. 
         [0029]    In the channel estimation operation  520 , the process first waits for available input ( 522 ) which is generated in  514 . If necessary, rate conversion and/or processing domain conversion (frequency domain to time domain or vice versa) are also done ( 524 ). Then in  526  the process runs channel estimation for parameters update. In  528  the process applies rate conversion and/or processing domain conversion to the parameters output from  526  where necessary. The parameters are combined with saved parameter ( 530 ), which in one embodiment includes convolution and truncation. The outputs from  530  provide update to  514 , and are also saved for next usage ( 532 ). Again rate conversion and/or domain conversion are applied to the parameters if necessary before feeding into  514  ( 534 ). 
         [0030]      FIG. 6  shows an example application that includes frequency-domain CD and PMD compensation with time-domain coefficient update. In this example application, an optical digital receiver uses frequency domain equalization for both chromatic dispersion (CD) and polarization mode dispersion (PMD), together with time-domain channel estimation. Block  610  acts as frequency-domain equalization, which first converts input signal to frequency domain by FFT block  602 , and then applies CD and PMD compensation coefficients to frequency signal in block  604 . After that the signals are converted back to time domain by IFFT block  606 . Outputs from  610  are provided to block  608  for further processing, such as signals rate conversion and phase/frequency offset compensation. Depending on the processing speed of channel estimation block  620 , part of the output samples from block  610  are also provided to block  620  to estimate channel parameters which will provide update to CD and PMD compensation block  604 . Assume signal input to block  610  has sampling rate different from that used in sub-level channel estimation block  624 , then inside block  620 , the output signals from block  610  are first resampled by resampler block  622  to match the rate in block  624 . Sub-level channel estimation block  624  then applies estimation algorithm to track channel changes. The result from block  624  is fed into convolution block  626 , which outputs the convolution of block  624 &#39;s output and old result from block  626 . The outputs from block  626  are updated parameters which will be converted by resampler block  628  to match the rate used in block  610 . FFT block  630  follows block  628  to convert the updated parameters to frequency domain will is fed into CD and PMD compensation block  604 . 
         [0031]    By way of example, a digital receiver is discussed next. The digital receiver is essentially a computer with transceivers that can be wired or wireless. The computer preferably includes a processor, random access memory (RAM), a program memory (preferably a writable read-only memory (ROM) such as a flash ROM) and an input/output (I/O) controller coupled by a CPU bus. The computer may optionally include a hard drive controller which is coupled to a hard disk and CPU bus. Hard disk may be used for storing application programs, such as the present invention, and data. Alternatively, application programs may be stored in RAM or ROM. I/O controller is coupled by means of an I/O bus to an I/O interface. I/O interface receives and transmits data in analog or digital form over communication links such as a serial link, local area network, wireless link, and parallel link. Optionally, a display, a keyboard and a pointing device (mouse) may also be connected to I/O bus. Alternatively, separate connections (separate buses) may be used for I/O interface, display, keyboard and pointing device. Programmable processing system may be preprogrammed or it may be programmed (and reprogrammed) by downloading a program from another source (e.g., a floppy disk, CD-ROM, or another computer). 
         [0032]    Each computer program is tangibly stored in a machine-readable storage media or device (e.g., program memory or magnetic disk) readable by a general or special purpose programmable computer, for configuring and controlling operation of a computer when the storage media or device is read by the computer to perform the procedures described herein. The inventive system may also be considered to be embodied in a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform the functions described herein. 
         [0033]    The invention has been described herein in considerable detail in order to comply with the patent Statutes and to provide those skilled in the art with the information needed to apply the novel principles and to construct and use such specialized components as are required. However, it is to be understood that the invention can be carried out by specifically different equipment and devices, and that various modifications, both as to the equipment details and operating procedures, can be accomplished without departing from the scope of the invention itself. 
         [0034]    By treating the signal path from transmitter output all the way to dynamic equalizer&#39;s output as an extended channel, the system can apply channel estimation to this “extended channel” output, which is actually the equalized signal, and uses the estimated channel parameter to update the old one that result in the current output signals.