Abstract
We consider the performance of blind maximum likelihood sequence detection (MLSD) when the recursive least-squares (RLS) algorithm is used to update channel estimates. We employ asymptotic efficiency analysis to characterize the performance of the detector as the signal-to-noise ratio (SNR) approaches infinity. Asymptotic efficiency analysis allows us to quantify the loss in performance due to the presence of inter-symbol interference (ISI) and the lack of channel knowledge. We show that, under certain conditions, the asymptotic efficiency of the detector depends only on a single most-likely noise realization. Our results indicate that the performance of the RLS-based detector is strongly dependent on both the magnitude of the ISI and the number of data samples available.
Original language | English (US) |
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Pages (from-to) | 1667-1671 |
Number of pages | 5 |
Journal | Conference Record of the Asilomar Conference on Signals, Systems and Computers |
Volume | 2 |
State | Published - 2003 |
Event | Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 9 2003 → Nov 12 2003 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications