A FAST ACSU ARCHITECTURE FOR VITERBI DECODER USING T-ALGORITHM PDF
In this paper, we propose an efficient architecture based on pre-computation for Viterbi decoders incorporating T-algorithm. Through optimization at both. A Fast ACSU Architecture for Viterbi Decoder Using T-Algorithm. Jinjin He, Huaping Liu, Senior Member, IEEE, and Zhongfeng Wang*, Senior Member, IEEE. High performance ACS for Viterbi decoder using pipeline T-Algorithm .. Z. Wang, A fast ACSU architecture for Viterbi decoder using T-Algorithm, in: Proc.
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A total of received gor 12 bits are simulated. Then, Bs are fed into the ACSU that recursively compute the path metrics Ps and outputs decision bits for each possible state transition.
We again need to analyze the trellis transition of the original code. For clarity, we only provide the main conclusion here. For VD in-corporated with T- algorithm, no state is guaranteed to be active at all clock cycles.
As a result, the de-coding speed of the low-power VD is greatly improved. It is well known that viterbi decoder is dominant module for finding the overall power consumption for the TCM decoders. A systematic way to determine the optimal precomputation steps is shown, where the minimum number of steps for critical path to achieve the theoretical iteration bound is calculated and the computational complexity overhead due to precomputation is evaluated.
Low power Viterbi decoder for Trellis coded Modulation using T-algorithm
Therefore, it is worth to discuss the optimal number of precomputation steps. Also, we assume that each remaining metric would ror a computational overhead of one addition decodwr.
When applied to high rate convolutional codes, the relaxed adaptive VD suffers a severe degradation of bit- error-rate BER performance due to the inherent drifting error between the estimated optimal path metric and the accurate one. After that, the decision bits are stored in and retrieved from the SMU in order to decode the source bits along the final survivor path.
Viterbi Convolutional Encoding and Viterbi Decoding.
Also, any kinds of low-power scheme would introduce extra hardware like the purge unit shown in Fig. Javeed is pursuing his master of technology in VLSI systems in Bomma institute of technology and scienceJawaharlal Nehru technological university, India. Theoretically, when we continuously decompose Ps n-1Ps n-2 ,……, the precomputation scheme can be extended to Q steps. User Username Password Remember me.
Thus we next focus on the power comparison between the full trellis VD and the proposed scheme. So, the computational over head and decoding latency due to predecoding and re encoding viterib the TCM signal become. The precomputation architecture that incorporates T-algorithm efficiently reduces the power consumption of VDs without reducing the decoding speed appreciably.
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Therefore, a straight forward implementation of T- Algorithm will dramatically reduce archotecture decoding speed. Design of high speed low power viterbi decoder for TCM system J. However, searching for the optimal path metric in the feedback loop still reduces the decoding speed. Suppose that we have labeled the states from 0 to Email this article Login required.
To fully achieve the iteration bound, we could add another pipeline stage, though it is very costly. Since the performance is the same as that of the conventional T-algorithm. Finally, we presented a design case. In a real design the overhead increases architwcture faster than what is given by 5 when other factors such as comparisons or expansion of metrics as we mentioned above are taken into consideration.
The results are shown in Table IV. Sri lakshmi is currently working as an assi. Each PM in all VDs is quantized as 12 bits. Article Tools Print this article. Firstbranch metrics are calculated in the B unit BMU from t-algrithm received symbols. Implementation of such a table is not trivial. Hamming distance and Euclidean distance .
It biterbi clear that the conventional T- algorithm is not suitable for high-speed applications.
The trellis butterflies for a VD usually have a symmetric structure. Basically M-Algorithm requires a sorting process in a t-algorithj loop where as T— Algorithm only searches for the optimal path metric [P] that is the maximum value or the minimum value of Ps. Breadth-first trellis decoding with adaptive effort Stanley J. Therefore, for high-speed applications, it should not be considered.
On the other hand the SST decoedr scheme requires predecoding and re encoding process and is not suitable for TCM decoders.
Citations Publications citing this paper. Consider a VD for a convoluional code with a constraint length k, where each state receives p candidate paths.