Sequence error probability lower bounds for joint detection and estimation

被引:1
|
作者
Anastasopoulos, A [1 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
关键词
correct decision feedback; generalized-likelihood ratio test; joint detection estimation; lower bounds; M-algorithm; per-survivor processing; sequence error probability; T-algorithm;
D O I
10.1109/TCOMM.2003.809718
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A commonly used lower bound on the probability of error of joint detection and estimation (JDE) algorithms is derived under the assumption that estimation is performed using the transmitted sequence, in a genie-aided fashion. Although it seems reasonable that this genie-aided receiver performs better than the original receiver, a proof of this fact is not available in the literature. In this letter, the validity of this bound is established for a general class of JDE algorithms, as well as for an important special case when the maximum-likelihood sequence detection criterion is used. The results are then extended to a well-known suboptimal JDE algorithm, namely, the T-algorithm. It is shown, however, that the technique used to prove this bound is not sufficient for establishing the validity of the bound for the M-algorithm and the per-survivor processing algorithm.
引用
收藏
页码:347 / 351
页数:5
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