The Viterbi algorithm is widely used for decoding of the convolutional codes. The trace-back method is preferable to the register exchange method because of lower power consumption especially for convolutional codes with many states. A drawback of the conventional trace-back is that it generally requires long latency to obtain the decoded data. In this paper, a method of the trace-back with source states instead of decision bits is proposed which reduces the number of memory accesses. The dedicated memory is also presented which supports the proposed trace-back method. The reduced memory accesses result in smaller power consumption and a shorer decode latency than the conventional method.

This paper proposes efficient DSP instructions and their hardware architecture for the Viterbi algorithm. The implementation of the Viterbi algorithm on a DSP chip has been attracting more interest for its flexibility, programmability, etc. The proposed architecture can reduce the Trace Back (TB) latency and can support various wireless communication standards. The proposed instructions perform the Add Compare Select (ACS) and TB operations in parallel and the architecture has special hardware, called the Offset Calculation Unit (OCU), which automatically calculates data addresses for acceleration of the trellis butterfly computations. When the constraint length K is 5, the proposed architecture can reduce the decoding cycles about 17% compared with Carmel DSP and about 45% compared with TMS320C55x.

In this paper, a new implementation of the Viterbi decoder is proposed. The Modified State-Mapping VD algorithm combines the TB algorithm with the RE algorithm. By updating the starting point of the state for each memory bank, and by using Trace Back and Trace Forward information, LIFO (Last Input First Output) operation can be eliminated, which reduces the latency of the TB algorithm and decreases the resource usage of the RE algorithm. When the memory unit is 3, the resource usage is 13184 bits and the latency is 54 clocks. The latency of the proposed algorithm is 25% smaller than the MRE algorithm and 50% smaller than the k-pointer even TB algorithm. In addition, resource usage is 50% smaller than the RE algorithm. The resource usage is a little larger than that of the MRE algorithm for the small value of k, but it becomes smaller after k is larger than 16.

Turbo codes are of particular use in applications of wireless communication systems, where various types of communication are required and the data rate must be changed, depending on the situation. In such applications, adaptation of turbo coding specifications is required in terms of coding block size, data speed, parity bit arrangement or configuration of a convolutional coder, as well as the need for real time processing. We present new ideas to provide these capabilities for a low power decoder circuit by focusing on the configuration of a convolutional decoding algorithm, which occupies a significant proportion of the hardware circuit. We utilize the Soft Output Viterbi Algorithm (SOVA) for the base algorithm, produced by adding the concept of a soft output to the Viterbi Algorithm (VA). The Maximum A Posteriori (MAP) algorithm and its simplified version of MAX-LOG-MAP are also widely known. MAP is recognized as a means of achieving very good bit error rate (BER) characteristics. On the other hand SOVA has been regarded as a method which can be simply implemented with less computational resources, but at a cost of higher degradation. However, in many of recent systems we combine turbo coding with some other method such as Automatic Repeat Request (ARQ) to maintain a good error correction performance and we only have to pay attention to the performance in the range of low carrier-to-noise ratio (CNR), where SOVA has fairly satisfactory BER characteristics. This makes the SOVA approach attractive for a low power programmable IP macro solution, when the fundamental advantage of SOVA is fully utilized in the implementation of an LSI circuit. We discuss the processing algorithm and circuit configuration and show that about 40% reduction in power consumption can be achieved. It is also shown that the IP macro can handle 1.5 Mbps information decoding at 100 MHz clock rate.