Abstract:
A system for digitally equalizing a data channel with heavily ISI-induced signals received after passing a data communication channel using a combination of a linear equalizer and a nonlinear equalizer, which comprises an ADC, for sampling a received signal and converting it to a digital form; a Linear Equalizer for pre-processing said received signal, said Linear Equalizer is adapted to pre-process a first group consisting of echoes/channel taps of the induced ISI, which are not equalized by said nonlinear equalizer, by eliminating the echoes/channel taps of said first group; pre-process a second group consisting of the combination of the entire echoes/channel taps of the induced ISI, by eliminating the echoes/channel taps of said second group; and a nonlinear equalizer for receiving the signals preprocessed by said Linear Equalizer and for further processing said preprocessed signals and eliminating the echoes/channel taps of the induced ISI to be equalized by said nonlinear equalizer, thereby compensating for the entire ISI induced by said channel.

Description:
FIELD OF THE INVENTION 
     The present invention relates to the field of communication systems. More particularly, the invention relates to a method and system for providing enhanced equalization of a data channel with heavily ISI-induced signals, based on a combination of reduced complexity MLSE and linear equalizer. 
     BACKGROUND OF THE INVENTION 
     Digital modem links with reduced bandwidth include Inter Symbol Interference (ISI), which requires using a Linear Equalizer (LE) to invert the channel and reverse the Inter Symbol Interference (ISI) effect. However, a major drawback of using a Linear Equalizer is the effect of noise enhancement, which occurs due to the channel inversion. An alternative solution is to decode the received signal by using an MLSE (Maximum-Likelihood Sequence Estimation) equalizer (rather than a Linear Equalizer), which is non-linear and therefore, does not enhance the noise at the receiver&#39;s input. However, the implementation of an MLSE equalizer is more complex compared to an LE, since it requires longer memory to process many taps backwards. 
     It is therefore an object of the present invention to provide a method and system for the equalization of a data channel with heavily ISI-induced signals, using a nonlinear equalizer with reduced complexity. 
     It is another object of the present invention to provide a method and system for the equalization of a data channel with heavily ISI-induced signals, which does not enhance the noise at the receiver&#39;s input. 
     Other objects and advantages of the invention will become apparent as the description proceeds. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to a system for digitally equalizing a data channel with heavily ISI-induced signals received after passing a data communication channel using a combination of a linear equalizer and a nonlinear equalizer, which comprises:
         a) an ADC, for sampling a received signal and converting it to a digital form;   b) a Linear Equalizer for pre-processing the received signal, the Linear Equalizer is adapted to:
           b.1) pre-process a first group consisting of echoes/channel taps of the induced ISI, which are not equalized by the nonlinear equalizer, by eliminating the echoes/channel taps of the first group;   b.2) pre-process a second group consisting of the combination of the entire echoes/channel taps of the induced ISI, by eliminating the echoes/channel taps of the second group; and   
           c) a nonlinear equalizer (such as an RC-MLSE) for receiving the signals preprocessed by the Linear Equalizer and for further processing the preprocessed signals and eliminating the echoes/channel taps of the induced ISI to be equalized by the nonlinear equalizer, thereby compensating for the entire ISI induced by the channel.       

     The system may further comprise a linear feedback circuitry for continuously adapting the filter taps of the Linear Equalizer, including:
         a) a channel estimation block for receiving the received signal at one input and the decoded symbols from the output of the nonlinear equalizer at the other input, to estimate the channel&#39;s impulse response signal;   b) a FIR block for:
           b.1) receiving a signal which includes the channel taps that are covered by the nonlinear equalizer, from the channel estimation block;   b.2) receiving the decoded symbols from the output of the nonlinear equalizer;   b.3) constructing an output signal at its output;   
           c) an adder for generating an error signal being the difference between the signals at the output of the Linear Equalizer and the output of the FIR block; and   d) a tap adaptation block for minimizing the error signal, such that the input to the nonlinear equalizer includes only taps which are covered by the nonlinear equalizer.       

     The system may be adapted to equalize received signals with high order modulations, including:
     PAM-2;   PAM-4;   PAM-8;   PAM-16;   Optical Dual Binary (ODB) modulation;   Quadrature Phase Shift Keying (QPSK);   QAM-8;   QAM-16.   

     The system may be also adapted to perform digital equalization of data channels in data networks, including:
     data center intra-connection;   data center interconnection;   metropolitan point-to-point connections;   metropolitan Wavelength-Division Multiplexing (WDM).   

     The present invention is also directed to a method for digitally equalizing a data channel with heavily ISI-induced signals received after passing a data communication channel, comprising:
         a) sampling a received signal and converting it to a digital form;   b) pre-processing the received signal by a Linear Equalizer, which is adapted to:
           b.1) pre-process a first group consisting of echoes/channel taps of the induced ISI, which are not equalized by the nonlinear equalizer, by eliminating the echoes/channel taps of the first group;   
           c) b.2) pre-process a second group consisting of the combination of the entire echoes/channel taps of the induced ISI, by eliminating the echoes/channel taps of the second group; and   d) receiving the signals preprocessed by the Linear Equalizer by a nonlinear equalizer; and   e) compensating for the entire ISI induced by the channel by further processing, by the nonlinear equalizer, the preprocessed signals and eliminating the echoes/channel taps of the induced ISI to be equalized by the nonlinear equalizer.       

    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above and other characteristics and advantages of the invention will be better understood through the following illustrative and non-limitative detailed description of preferred embodiments thereof, with reference to the appended drawings, wherein: 
         FIG. 1  (prior art) illustrates an example of the impulse response of a typical data channel with reduced bandwidth; 
         FIG. 2  illustrates a block diagram of the equalization system proposed by the present invention; 
         FIG. 3  illustrates the impulse response of a data channel with reduced bandwidth after performing a decoding process, based on a combined processing using a Linear Equalizer and a reduced complexity MLSE (RC-MLSE), as proposed by the present invention; 
         FIG. 4  is a block diagram of the equalization system of  FIG. 2 , with continuous adaptation capability of filter taps of the Linear Equalizer, according to the present invention; and 
         FIG. 5  illustrates comparison results of the Symbol Error Rate (SER) between a receiver scheme which includes an RC-MLSE receiver only and a receiver scheme which includes a combination of an LE and an RC-MLSE. 
     
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
     The present invention suggests a digital equalization mechanism, which is combined with a Maximum Likelihood Sequence Estimator (MLSE) in digital communication links. The proposed equalization mechanism includes a receiver, which uses a combination of an LE and a Reduced Complexity MLSE (RC-MLSE) to implement a receiver with low implementation complexity and lower noise enhancement. The advantage is that an RC-MLSE requires less computations and less power and is more simple to implement than a regular MLSE. 
     The Relation Between Reduced Bandwidth and ISI 
     Generally, channels with reduced bandwidth introduce ISI. If the transmitted signal is given by:
 
 y ( t )=Σ k α k ·δ( t−k·T   sym )  [Eq. 1]
 
where
     a k —The transmitted symbol   k—The symbol index   δ—The Dirac delta-function   t—The continuous time   T sym —The baud interval (Sec)   

     Then the received signal (before sampling) could be written as:
 
 r ( t )= y ( t )* h ( t )+ w ( t )[Eq.2]
     w(t)—The additive noise   h(t)—The overall impulse response from transmitter (before DAC) to receiver (after ADC)
 
 r ( t )=Σ k ·α k   ·h ( t−k·T   sym )+ w ( t )  [Eq. 8]
   

     Assuming perfect timing reconstruction, the sampling instances will be:
 
 t=n·T   sym  
 
     Under these conditions, the sampled version of the received signal could be written as: 
                       r   n     =     r   ⁡     (     t   =     n   ·     T   sym         )         ⁢     
     ⁢       r   n     =         ∑   k     ⁢       a   k     ·     h   ⁡     (       n   ·     T   sym       -     k   ·     T   sym         )           +     w   ⁡     (     n   ·     T   sym       )           ⁢     
     ⁢       r   n     =         ∑   k     ⁢       a   k     ·     h   ⁡     (       (     n   -   k     )     ·     T   sym       )           +     w   ⁡     (     n   ·     T   sym       )           ⁢     
     ⁢       r   n     =         a   n     ·     h   ⁡     (   0   )         +       ∑     k   ≠   n       ⁢       a   k     ·     h   ⁡     (       (     n   -   k     )     ·     T   sym       )           +     w   n                 [     Eq   .           ⁢   4     ]               
where,
 
     a n ·h(0) is the desired part of the signal 
     Σ k≠n α k ·h((n−k)·T sym ) is the inter symbol interference (ISI) term 
     w n  is the additive noise. 
       FIG. 1  shows an example of the response of a typical reduced bandwidth channel. In this case, the channel includes four effective echoes (unwanted signals)  11 - 14  (in this example, for Unit Intervals (UIs) =−2, −1, 1, 2, where the UI is the symbol duration time), while the rest are zero and therefore, do not add anything to the received signal. The envelop  15  represents the analog channel impulse response. 
     A Linear Equalizer based on the Minimum Mean Squared Error (MMSE) criteria tries to minimize the error caused by both the residual ISI and by the (enhanced) noise. On the other hand, an MLSE decoder does not try to invert the channel (i.e., to zero the ISI) but rather, it uses the echoes as a wanted signal for decoding the transmitted symbol sequence (the echoes are ‘wanted signals’ for consecutive symbols). An MLSE decoder that uses the echoes as wanted signals is required to implement decoding functionality which is proportional to:
 
 C∝M   (N     ISI     +1)   [Eq. 5]
 
where M is the symbol modulation order (i.e., for PAM-4, M=4 etc.) and N ISI  is the number of echoes used for sequence decoding.
 
     If an RC-MLSE decoder implementation uses N ISI  which is smaller than the channel unwanted ISI (to save implementation complexity), then the residual ISI will reduce the performance of the decoding algorithm. 
     For the example of  FIG. 1 , the channel ISI is represented by 5 echoes (including the wanted signal  10  and un-wanted ISI  11 - 14 ). If the RC-MLSE decoder implementation uses only N ISI =2, then only two unwanted echoes and the wanted echo will be used in the RC-MLSE decoding algorithm, while the other (remaining) two unwanted echo&#39;s will reduce the decoding performance since they are not taken into the decoding considerations. 
       FIG. 2  illustrates a block diagram of the equalization system proposed by the present invention, in which the receiver  20  includes an ADC  21  for sampling the received signal x(t) and a combination of an LE  23 , followed by a Reduced Complexity MLSE (RC-MLSE)  23  to implement the receiver  20  with low complexity and lower noise enhancement. 
     The decoding process is based on the following combined processing: At the first step, the echoes/channel taps of the induced ISI are reduced by using a Linear Equalizer  22 , in order not to be covered by the reduced complexity MLSE (RC-MLSE)  23 . At the next step, the signal at the linear equalizer&#39;s output is decoded (using standard decoding) by the RC-MLSE  23 . This decoding process is described in  FIG. 3  (in time domain). 
     In the example of  FIG. 3 , it is assumed that the number of echoes handled by the RC-MLSE is N ISI =2 (the wanted signal  10  and its two neighboring echoes  12 - 13 ). The envelop  15  represents the analog channel impulse response. Taps (echoes)  11  and  14  represent the taps which are equalized by the linear equalizer  22 . Taps echoes)  10 ,  12  and  13  represent the (N ISI +1) taps which are used by the RC-MLSE  23  to decode the symbol sequence. The Linear Equalizer  22  is used to preprocess the less effective taps (echoes)  11  and  14  by eliminating them and redistributing their energy among the remaining taps  10 ,  12  and  13  (which are the most substantial), to be processed by the RC-MLSE  23 . Despite the fact that the channel is non-linear, the LE  22  assumes linearity of the channel and therefore, performs only linear operations which are less complex (that the operations of the RC-MLSE  23  which are nonlinear). The redistribution scheme is based on the number of taps that RC-MLSE  23  will be required to further process. For example, if the level of the less effective taps (echoes) is below the noise level, the LE  23  will be adapted to totally eliminate them (without redistributing their energy among the remaining taps), such that only taps with energy level which is above the noise level will be redistributed. By doing so, the LE  22  effectively modifies (reshapes) the impulse response of the channel, to include only three taps ( 10 ,  12  and  13 ), thereby “shortening” the channel and saving from the processing effort that will be required from the RC-MLSE  23 . 
     According to the present invention, the filter taps of Linear Equalizer are continuously adapted by constructing an error signal for the LE tap adaptation. 
       FIG. 4  is a block diagram of the equalization system (of  FIG. 2 ) with continuous adaptation capability of filter taps of Linear Equalizer  22  using a linear feedback circuitry  44 , as proposed by the present invention. 
     The received signal r n  an after sampling (at point  1 ) could be written as:
 
 r   n =Σ k   a   k   ·h   (n−k)   +w   n   [Eq. 6]
 
     The channel estimation block  41  receives the received signal r n  (point  1 ) at one input and the decoded symbols from the output of the RC-MLSE  23  (point  3 ) at the other input, to estimate the channel&#39;s impulse response signal h[n]. 
     The channel estimation block  41  provides to the FIR block  42  a signal (point  4 ) which includes the channel taps that are covered by the RC-MLSE  23 : h k (k∈MLSE Taps). The FIR block  42  also receives the decoded symbols from the output of the RC-MLSE  23  (point  3 ) and from the output of the channel estimation block  41  (point  4 ), constructs the signal at the output of the FIR block  42  (point  5 ) which is given by:
 
 x 5 n =ρ k∈MLSETaps   a   k   ·h   (n−k)   [Eq. 7]
 
     The signal at point  6 , which is the difference between the signals at the output of Linear Equalizer  22  (point  2 ) and the output of the FIR block  42  (point  5 ), represents the error signal x6 n  (at point  6 ):
 
 x 6 n   =x 2 n   −x 5 n   [Eq. 8]
 
     The tap adaptation block  43  receives the error signal at point  6  and minimizes it. When this will happen (while neglecting the noise and assuming the minimal value is zero), the signal at point  2  will be equal to the signal at point  5  so the signal at point  2  could be written as:
 
 x 2 n =Σ k∈MLSETaps   a   k   ·h   (n−k)   +{tilde over (w)}   n   [Eq. 9]
 
     In such a case (steady state), the input to the RC-MLSE  23  includes only taps which are covered by the RC-MLSE  23 . 
     In practice, FIR block  42  is fed by the channel estimation block  41 , which represents the linear model (assumption) of the channel. Therefore, FIR block  42  will have a reshaped impulse response, which generates the error signal (at point  6 ), according to which the tap adaptation block  43  updates the taps of the LE  22 . 
     The implementation of the linear feedback circuitry  44  of  FIG. 4  actually uses only linear (and relatively simple) operations, in order to simplify the implementation 
       FIG. 5  illustrates a comparison between a receiver scheme which includes an RC-MLSE receiver  23  only and a receiver scheme which includes a combination of an LE  22  and an RC-MLSE  23 . 
     In this example, the channel impulse response was: 
     h=[0.00011351 0.021874 0.23321 0.46527 0.25063 0.030095 −0.0014694]; 
     Graph  51  represents the Symbol Error Rate (SER) for a hard slicer decoder over an Additive white Gaussian noise (AWGN) channel with no ISI. Graph  52  represents receiver performance over the ISI channel, which uses only a nonlinear equalization of the RC-MLSE  23  (N ISI =2). Graph  53  represents the receiver performance over the ISI channel, using the combination of an LE  22  and an RC-MLSE  23 . It can be seen that the SER obtained by using the proposed combination of an LE  22  for linear preprocessing and an RC-MLSE  23  for nonlinear processing provides a reasonable SER, with much less implementation complexity. 
     The above examples and description have of course been provided only for the purpose of illustration, and are not intended to limit the invention in any way. As will be appreciated by the skilled person, the invention can be carried out in a great variety of ways, employing more than one technique from those described above, other than used in the description, all without exceeding the scope of the invention.