Initial Commit
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Jordan Sherer
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subroutine osd174(llr,norder,decoded,niterations,cw)
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!
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! An ordered-statistics decoder based on ideas from:
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! "Soft-decision decoding of linear block codes based on ordered statistics,"
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! by Marc P. C. Fossorier and Shu Lin,
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! IEEE Trans Inf Theory, Vol 41, No 5, Sep 1995
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!
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include "ldpc_174_87_params.f90"
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integer*1 gen(K,N)
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integer*1 genmrb(K,N)
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integer*1 temp(K),m0(K),me(K)
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integer indices(N)
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integer*1 codeword(N),cw(N),hdec(N)
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integer*1 decoded(K)
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integer indx(N)
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real llr(N),rx(N),absrx(N)
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logical first
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data first/.true./
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save first,gen
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if( first ) then ! fill the generator matrix
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gen=0
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do i=1,M
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do j=1,22
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read(g(i)(j:j),"(Z1)") istr
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do jj=1, 4
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irow=(j-1)*4+jj
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if( irow .le. K ) then
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if( btest(istr,4-jj) ) gen(irow,i)=1
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endif
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enddo
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enddo
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enddo
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do irow=1,K
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gen(irow,M+irow)=1
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enddo
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first=.false.
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endif
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! re-order received vector to place systematic msg bits at the end
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rx=llr(colorder+1)
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! hard decode the received word
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hdec=0
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where(rx .ge. 0) hdec=1
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! use magnitude of received symbols as a measure of reliability.
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absrx=abs(rx)
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call indexx(absrx,N,indx)
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! re-order the columns of the generator matrix in order of increasing reliability.
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do i=1,N
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genmrb(1:K,N+1-i)=gen(1:K,indx(N+1-i))
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enddo
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! do gaussian elimination to create a generator matrix with the most reliable
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! received bits as the systematic bits. if it happens that the K most reliable
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! bits are not independent, then we dip into the bits just below the K best bits
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! to find K independent most reliable bits. the "indices" array tracks column
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! permutations caused by reliability sorting and gaussian elimination.
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do i=1,N
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indices(i)=indx(i)
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enddo
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do id=1,K ! diagonal element indices
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do ic=id,K+20 ! The 20 is ad hoc - beware
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icol=N-K+ic
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if( icol .gt. N ) icol=M+1-(icol-N)
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iflag=0
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if( genmrb(id,icol) .eq. 1 ) then
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iflag=1
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if( icol-M .ne. id ) then ! reorder column
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temp(1:K)=genmrb(1:K,M+id)
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genmrb(1:K,M+id)=genmrb(1:K,icol)
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genmrb(1:K,icol)=temp(1:K)
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itmp=indices(M+id)
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indices(M+id)=indices(icol)
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indices(icol)=itmp
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endif
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do ii=1,K
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if( ii .ne. id .and. genmrb(ii,N-K+id) .eq. 1 ) then
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genmrb(ii,1:N)=mod(genmrb(ii,1:N)+genmrb(id,1:N),2)
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endif
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enddo
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exit
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endif
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enddo
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enddo
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! use the hard decisions for the K MRB bits to define the order 0
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! message, m0. Encode m0 using the modified generator matrix to
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! find the order 0 codeword. Flip all combinations of N bits in m0
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! and re-encode to find the list of order N codewords. Test all such
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! codewords against the received word to decide which codeword is
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! most likely to be correct.
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m0=0
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where (rx(indices(M+1:N)).ge.0.0) m0=1
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nhardmin=N
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corrmax=-1.0e32
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j0=0
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j1=0
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j2=0
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j3=0
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if( norder.ge.4 ) j0=K
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if( norder.ge.3 ) j1=K
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if( norder.ge.2 ) j2=K
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if( norder.ge.1 ) j3=K
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nt=0
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do i1=0,j0
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do i2=i1,j1
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do i3=i2,j2
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do i4=i3,j3
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nt=nt+1
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me=m0
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if( i1 .ne. 0 ) me(i1)=1-me(i1)
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if( i2 .ne. 0 ) me(i2)=1-me(i2)
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if( i3 .ne. 0 ) me(i3)=1-me(i3)
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if( i4 .ne. 0 ) me(i4)=1-me(i4)
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! me is the m0 + error pattern. encode this message using genmrb to
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! produce a codeword. test the codeword against the received vector
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! and save it if it's the best that we've seen so far.
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do i=1,N
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nsum=sum(iand(me,genmrb(1:K,i)))
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codeword(i)=mod(nsum,2)
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enddo
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! undo the bit re-ordering to put the "real" message bits at the end
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codeword(indices)=codeword
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nhard=count(codeword .ne. hdec)
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! corr=sum(codeword*rx) ! to save time use nhard to pick best codeword
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if( nhard .lt. nhardmin ) then
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! if( corr .gt. corrmax ) then
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cw=codeword
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nhardmin=nhard
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! corrmax=corr
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i1min=i1
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i2min=i2
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i3min=i3
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i4min=i4
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if( nhardmin .le. 15 ) goto 200 ! early exit - tune for each code
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endif
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enddo
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enddo
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enddo
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enddo
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200 decoded=cw(M+1:N)
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niterations=nhardmin
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return
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end subroutine osd174
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