Page 48 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 6 – Wireless communication systems in beyond 5G era
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ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 6



          The PSG input column vector at the    t h  iteration is
          de ined as follows:                                                 D
                                   (  )                                                                     
                        ⎡    n (   −    ∶   )  ⎤                                                      Norm.
                        ⎢      0     0       ⎥                           −1
                    i =  ⎢  r (   −    ∶    − 1)  ⎥ ,  (9)
                       
                                   1
                             0
                        ⎢         …          ⎥                                      
                        ⎣ r   −1 (   −    ∶    − 1) ⎦
                                      
                                                                              Fig. 2 – Structure of the PSG.
                          th
          where   (  ) is the    systematic symbol, n (   −    ∶   )
                                                     0
                                              0
          is a column vector of length    + 1 which contains noise  Functions    and    will be parameterized using DNNs.
                                   0
          samples from the sequence n of (1), r (   −    ∶    − 1)  The structure of Fig. 2 corresponds to a recurrent ar‑
                                                   
                                             
                                   0
          (   = 0, … ,    − 1) is a column vector of length    which  chitecture, and therefore, we will consider the following
                                                     
          contains noise samples from the sequence r of forward‑  three recurrent architectures to model it: RNNs, GRUs
                                                 
                                           th
          channel noise samples that corrupt the    symbol of each  and LSTMs.
          parity symbol sequence, that is:
                                                               2.3.1  RNN
                       r ≜ (   (  ), … ,      −1 (  )),  (10)
                             0
                          
                                                               When modeled with an RNN, the function   (⋅) in (13) is
                                        th
          where    (  ) (   = 0, … ,    −1) is the    sample of v in (5)  de ined as follows:
                                                      
                  
          and    , … ,    are arbitrary positive integers (   can be 0),
                      
              0
                                                0
          hereafter called the encoder input extensions. We note that    (i , h   −1 ) = tanh(Wh   −1  + Yi + b),  (14)
                                                                            
                                                                                                    
          the Deepcode [1] encoder can be recovered as a special
                                                                                                            0
          case by setting    = 0 and    = … =        = 1, which  where W is a state‑transition matrix of size    ×    , Y
                                                                                                       0
                                   1
                        0
                                                                                           0
          means that, in each iteration, only a single noise sample  is an input‑state matrix of size    ×    (   is the length of
                                                                        
                                                                                                    0
          for each systematic or parity check symbol is used. The  vector i ), and b is a bias vector of length    . W, Y and b
          buffers in the DEF encoder contain the systematic sym‑  are obtained by NN training.
          bol sequence x and the corresponding forward‑noise se‑
          quence n of (1). Those sequences are generated during  2.3.2  GRU
                 0
          the  irst encoding phase and used by the PSG in the second  With a GRU, the function   (⋅) of (13) is de ined as follows:
          phase.
                                                                     (i , h   −1 ) =     (i , h   −1 ) ∘ (1 −   (i , h   −1 ))
                                                                                                      
                                                                                   0
                                                                                       
                                                                        
          2.3 Parity Symbol Generator (PSG)                                   + h    −1  ∘   (i , h   −1 ).  (15)
                                                                                            
          The core functionality of the DEF encoder is the compu‑  The function    (⋅) in (15) is de ined as follows:
          tation of the parity check symbols, which is performed by         0
          the block denoted (PSG) (see Fig. 1). PSG computes the     (i , h   −1 ) =  tanh((W h  + b ) ∘   (i , h   −1 )
                                                                                             −1
                                                                   0
                                                                       
                                                                                                 ℎ
                                                                                                         
                                                 th
           th
             parity symbol sequence p based on the    modula‑                + Y i + b ).                   (16)
                                     
          tion symbol    and a subset of the past forward‑channel                          
                       
          outputs.                                             The functions   (⋅) in (15) and   (⋅) in (16) are de ined as
                                                th
          Fig. 2 shows the structure of the PSG. In the    encoding  follows:
                                    th
          iteration, the PSG generates a    parity symbol sequence
          p which consists of    real parity symbols obtained as fol‑    (i , h   −1 ) =    (W h  + Y i + b )  (17)
                                                                                                         
                                                                                                      
                                                                                              −1
                                                                           
             
          lows:                                                         (i , h   −1 ) =    (W h  + Y i + b )  (18)
                                                                                                      
                                                                                              −1
                                                                           
                                                                                                         
                         p = Norm(  (h )),            (11)
                                         
                             
                                                                                   )
                                                               where   (  ) ≜ (1 +    −   −1  denotes the sigmoid function.
          where h , a real vector of arbitrary length    , denotes the  In equations (15)‑(18), matrices W , W , W , Y , Y , Y
                  
                                              0
                                                                                                           
                                                                                                              
                                                                                                
                                                                                                    
                                                                                                        
          PSG state at time instant   , while function   (⋅) consists of a  and vectors b , b , b , b are obtained by NN training.    
          lineartransformationappliedtothePSGstateh obtained               ℎ            
                                                   
          as follows:                                          2.3.3  LSTM
                            (h ) = Ah + c,            (12)
                                      
                               
          where A has size    ×    and c has length   . The above  As for LSTM, the function   (⋅) of (13) is de ined as follows:
                              0
          matrices W, Y, A and vectors b, c are obtained by NN train‑    (i , h  ) =     (i , h  ) ∘ tanh(s )  (19)
          ing. The Norm(⋅) function normalizes the PSG output so               −1     1        −1        
          that each parity symbol has zero mean and unit variance.  where s is the cell state at time instant   . The cell state
                                                                        
          The PSG state h is recursively computed as           provides long‑term memory capability to the LSTM NN,
                         
                          h =   (i , h   −1 ),        (13)     whereas the state h provides short‑term memory capa‑
                                                                                  
                              
                                    
                                                               bility. The cell state is recursively computed as follows:
          where function   (⋅) will be discussed below, and i is de‑
                                                      
           ined in (9). As for the initialization, we set h as the all‑  s     =     (i , h   −1 ) ∘ s   −1
                                                                                     
                                                                                 2
                                                0
          zero vector.                                                       +     (i , h   −1 ) ∘    (i , h   −1 ).  (20)
                                                                                                 
                                                                                     
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          36                                 © International Telecommunication Union, 2021
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