The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 09, 2002
Filed:
Apr. 21, 1999
Sreen A. Raghavan, La Jolla, CA (US);
Hari Thirumoorthy, San Diego, CA (US);
National Semiconductor Corporation, Santa Clara, CA (US);
Abstract
A Nearest Neighbors Look-Ahead Maximum Likelihood Estimation Sequence (LA-MLSE) algorithm for decoding data in a digital communications system forms the following three vectors to decode data: (1) a vector of the encoder input bit signals A=A{k, k+1, k+2}, (2) a vector of the noise-free encoder channel output signals Y=Y{A(k), A(k+1), A(k+2)}; and (3) a vector of the received signals R=R(A(k), A(k+1), A(k+2)). If the distance between the received signal R and at least one of the channel output vectors which are of the form Y{1, A(k+1), A(k+2)} is shorter than the distance between the received signal R and the Nearest Neighbor of the signal Y{1, A(k+1), A(k+2)}, then A(k) is decoded as 1. In an All Neighbors Look-Ahead MLSE algorithm, A(k) is decoded as 1 only if the distance between the received signal R and at least one of the channel output vectors which are of the form Y{1, A(k+1), A(k+2)} is shorter than all the distances between signal R and each of the channel output vectors which are of the form Y{0, A(k+1), A(k+2)}. In a Nearest Neighbor Adjusted Depth Look-Ahead MLSE algorithm, if the distance obtained using the first two time indices, i.e. k and k+1, is greater than a minimum distance, the time index k+2 is omitted from the calculations, thereby reducing the amount of computations necessary to estimate the value of the encoder input data.