Performance of Block Codes Using the Eigenstructure of the Code Correlation Matrix and Soft-Decision Decoding of BPSK
Abstract
A method is presented for obtaining the error
probability for block codes. The method is based on the eigenvalue-
eigenvector properties of the code correlation matrix. It is found that
under a unary transformation and for an additive white Gaussian
noise environment, the performance evaluation of a block code
becomes a one-dimensional problem in which only one eigenvalue
and its corresponding eigenvector are needed in the computation. The
obtained error rate results show remarkable agreement between
simulations and analysis.