Title
Upper Bounds On the ML Decoding Error Probability of General Codes over AWGN Channels.
Abstract
In this paper, parameterized Gallager's first bounding technique (GFBT) is presented by introducing nested Gallager regions, to derive upper bounds on the ML decoding error probability of general codes over AWGN channels. The three well-known bounds, namely, the sphere bound (SB) of Herzberg and Poltyrev, the tangential bound (TB) of Berlekamp, and the tangential-sphere bound (TSB) of Poltyrev, are generalized to general codes without the properties of geometrical uniformity and equal energy. When applied to the binary linear codes, the three generalized bounds are reduced to the conventional ones. The new derivation also reveals that the SB of Herzberg and Poltyrev is equivalent to the SB of Kasami et al., which was rarely cited in the literatures.
Year
Venue
Field
2013
CoRR
Discrete mathematics,Combinatorics,Parameterized complexity,Decoding error probability,Communication channel,Binary linear codes,Additive white Gaussian noise,Mathematics,Bounding overwatch
DocType
Volume
Citations 
Journal
abs/1308.3303
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Qiutao Zhuang1443.56
Jia Liu24217.09
Xiao Ma37112.07