A Viterbi decoder system comprises a convolutional encoder and Viterbi decoder. In general, the code words generated from the input series of convolutional encoder arrive at the decoder through a noisy channel; however, the channel noise can cause corruption of code words. The Viterbi decoder extracts the original input message from the corrupted data using the Viterbi algorithm based on the maximum likelihood principle. A Viterbi decoder mainly comprises four essential units: a branch metrics unit, add-compare-select unit, path metrics unit, and survivor-path memory unit. Related complex calculations are repeated in these units at each clock cycle. In this study, a power- and area-efficient Viterbi decoder architecture that also reduces the computational complexity is proposed. Initially, a hard-decision Viterbi decoder system architecture design for Very Large Scale Integration (VLSI) realization was fulfilled without any further improvement to compare the performance of fundamental and improved designs with respect to power consumption. The initial design constitutes an essential base for the improved power- and area-efficient Viterbi decoder architecture. The improvements were made to achieve the less complex and power-efficient architectural system design. The performance of the proposed architecture was tested by a fieldprogrammable gate array (FPGA) platform, and the results have been reported. The architectural design is described using the Verilog hardware description language for comparing the related tests and performance of FPGA platform.