Title :
Blind sequence detection without channel estimation
Author_Institution :
Dept. of Electr. & Comput. Eng., State Univ. of New York, Binghamton, NY, USA
fDate :
7/1/2002 12:00:00 AM
Abstract :
This paper proposes a new blind sequence estimation method for single-input single-output (SISO) systems utilizing an optimal trellis search, which is performed by a channel-independent Viterbi algorithm (CIVA). In contrast to the traditional Viterbi algorithm that requires accurate channel estimation, CIVA does not require channel coefficients. Instead, the metrics are calculated from a bank of test vectors designed off-line. The proposed algorithm has outstanding performance under most of the channel conditions. Specifically, it does not suffer from ill-conditioned channels. In addition, it does not depend on channel correlation estimation and, therefore, has fast convergence. Simulations demonstrate its superior performance over even most training-based equalization algorithms
Keywords :
Viterbi detection; blind equalisers; convergence of numerical methods; maximum likelihood estimation; sequential estimation; SISO systems; blind equalization; blind sequence detection; channel conditions; channel-independent Viterbi algorithm; fast convergence; optimal trellis search; simulations; single-input single-output systems; test vectors; training-based equalization algorithms; Blind equalizers; Channel estimation; Convergence; Frequency estimation; Mobile communication; Packet radio networks; Radiofrequency identification; Statistics; Testing; Viterbi algorithm;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2002.1011213