Soft-Decision Error Correction of NAND Flash Memory with a Turbo Product Code
Journal of Signal Processing Systems
Hybrid local search polynomial-expanded linear multiuser detector for DS/CDMA systems
International Journal of Wireless and Mobile Computing
Boolean functions over nano-fabrics: improving resilience through coding
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Efficient decoding of the (23, 12, 7) Golay code up to five errors
Information Sciences: an International Journal
Distributed turbo product codes with soft decode-and-forward and power allocation
International Journal of Wireless and Mobile Computing
An energy-efficient clustered distributed coding for large-scale wireless sensor networks
The Journal of Supercomputing
A minimal search soft decision list decoding algorithm for Reed-Solomon codes
International Journal of Information and Communication Technology
| Hi-index | 754.84 |
A class of decoding algorithms that utilizes channel measurement information, in addition to the conventional use of the algebraic properties of the code, is presented. The maximum number of errors that can, with high probability, be corrected is equal to one less thand, the minimum Hamming distance of the code. This two-fold increase over the error-correcting capability of a conventional binary decoder is achieved by using channel measurement (soft-decision) information to provide a measure of the relative reliability of each of the received binary digits. An upper bound on these decoding algorithms is derived, which is proportional to the probability of an error fordth order diversity, an expression that has been evaluated for a wide range of communication channels and modulation techniques. With the aid of a lower bound on these algorithms, which is also a lower bound on a correlation (maximum-likelihood) decoder, we show for both the Gaussian and Rayleigh fading channels, that as the signal-to-noise ratio (SNR) increases, the asymptotic behavior of these decoding algorithms cannot be improved. Computer simulations indicate that even for !ow SNR the performance of a correlation decoder can be approached by relatively simple decoding procedures. In addition, we study the effect on the performance of these decoding algorithms when a threshold is used to simplify the decoding process.