Browsing by Author "Chou, CS"

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Performance of array signal processing algorithms for wideband digital wireless communication
(1999)
Chou, CS
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Lin, DW
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
We consider several array signal processing architectures equipped with different training approaches and evaluate their performance in high-speed digital wireless transmission by way of computer simulation. The array architectures considered are: space-only, delay-combine, and multi-stage space-time. The training approaches considered include max-SINR, LS (least-squares) with channel estimation, and LS without channel estimation. These arrays are simpler than the full space-time architecture at the cost of a lower error-rate performance.
Signal design and receiver dimensioning for space-time Viterbi equalisation
(2001-06-01)
Chou, CS
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Lin, DW
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電子工程學系及電子研究所
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電信研究中心
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Department of Electronics Engineering and Institute of Electronics
Space-time Viterbi equalisation for wireless communication has received much interest recently. The authors consider the associated signal and receiver design for improved transmission performance at high baud rates. Three techniques are proposed; two concern signal design and one concerns receiver design. First, special kinds of sequences called the min-norm training sequences are used for channel estimation. These sequences can minimise the mean-square estimation error in uncorrelated AWGN environments. Secondly, the authors consider using unequal power levels for the training signal and the data signal, with a higher power level for the former. They derive a mathematical expression for the optimal power ratio. Thirdly, a channel estimation method using reduced channel length is proposed. This method can reduce the channel estimation error in low SNR environments. Small-scale Monte Carlo simulations are conducted to investigate the performance gain of these techniques in wireless transmission. The results show varying degrees of advantage under different conditions.
Speaker-independent Mandarin polysyllabic word recognition
(1996)
Chang, HY
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Chen, B
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Chou, CS
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Liu, CM
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交大名義發表
In this paper we consider the design of speaker-independent Mandarin polysyllabic word recognition system from two viewpoints: the phonetical modeling and the recognition speeds. For phonetical modeling, we consider the accurate acoustic models that can increase the recognition rate. This paper experiments three phonetical models: context-independent INITIALs, right-context-dependent null-INITIALs models, and right-context-dependent INITIALs and null-INITIALs models. The recognition results show respectively on average recognition rate 99.1%, 93.7% and 83.6% for 500-words, 5000-words, and 25000-words tasks. While for top 3 words, the average rates 99.8%, 98.5% and 95.2% are achieved. On the basis of the recognition results, we consider the fast computing algorithms to increase computing speeds. Since that the tree-trellis search algorithm can retain the recognition rate of system and has the potential to greatly reduce the search time, this paper adopts the search algorithm as the basic framework and investigates some implementation techniques. The results show that the tree-trellis algorithm can provide a search time slightly dependent with word size.
Training sequence and memory length selection for space-time Viterbi equalization
(2000-12-01)
Chou, CS
;
Lin, DW
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
We consider signal and receiver design for space-time Viterbi equalization for wireless transmission, We propose a search method to find good training sequences, termed min-norm training sequences, for least-square channel estimation. Compared to either a maximum-length sequence ol a randomly generated training sequence, the training sequence obtained can drastically reduce the channel estimation error: We also derive a simple lower bound on the achievable channel estimation error of any training sequence. Knowledge of this lower bound helps the search for min-norm training sequences in that it facilitates a measure of the goodness of the best sequence examined so far, For operation under the situation with unknown channel response lengths, we propose a simple method to select the memory length (tap number) in the Viterbi equalizer based on the SNR of the received signal, The resulting equalization performance is found to he comparable with the case where a preset, fixed memory length is used. However, the proposed method often results in use of a smaller tap number, which translates into a reduction ill the computational complexity, Simulation results show that at symbol error rate below 10(-2) (SNR > 5 dB) the amount of complexity reduction is of the order of 5% to 25% on the average, for typical wireless channels.
Training techniques of space-time Viterbi equalizers for high speed mobile communication
(2000)
Chou, CS
;
Lin, DW
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
We consider space-time Viterbi equalization in nonspread-spectrum mobile communication at high data rates (over 1 Mbps). A specially designed sequence called the min-norm training sequence is used for channel estimation. The design is such that the mean-square estimation error is minimized in an AWGN environment. In addition, a channel estimation method using reduced channel length is proposed. The method can reduce the channel estimation error in low SNR environments. A Viterbi equalizer employing the proposed channel estimation method can perform better than employing least-squares channel estimation with nonreduced channel length.