Back to Search
Start Over
Generalized Nearest Neighbor Decoding.
- Source :
-
IEEE Transactions on Information Theory . Sep2022, Vol. 68 Issue 9, p5852-5865. 14p. - Publication Year :
- 2022
-
Abstract
- It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minimum Euclidean distance between a codeword and the received channel output vector, is the maximum likelihood solution and hence capacity-achieving. Nearest neighbor decoding remains a convenient and yet mismatched solution for general channels, and the key message of this paper is that the performance of nearest neighbor decoding can be improved by generalizing its decoding metric to incorporate channel state dependent output processing and codeword scaling. Using generalized mutual information, which is a lower bound to the mismatched capacity under independent and identically distributed codebook ensemble, as the performance measure, this paper establishes the optimal generalized nearest neighbor decoding rule, under Gaussian channel input. Several restricted forms of the generalized nearest neighbor decoding rule are also derived and compared with existing solutions. The results are illustrated through several case studies for fading channels with imperfect receiver channel state information and for channels with quantization effects. [ABSTRACT FROM AUTHOR]
- Subjects :
- *GAUSSIAN channels
*EUCLIDEAN distance
*CHANNEL estimation
Subjects
Details
- Language :
- English
- ISSN :
- 00189448
- Volume :
- 68
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Information Theory
- Publication Type :
- Academic Journal
- Accession number :
- 158603995
- Full Text :
- https://doi.org/10.1109/TIT.2022.3172701