In wireless communication AWGN (Additive White Gaussian Noise) properties of most of the communication media introduce noise in real data during transmission

Convolution encoding with Viterbi decoding is a powerful method for forward error correction. It has been widely deployed in many wireless communication systems to improve the limited capacity of the communication channels. Viterbi algorithm, is the most extensively employed decoding algorithm for convolutional codes. In this paper, we present ARM based implementation of Viterbi decoder that uses survivor path with parameters for wireless communication in an attempt to reduce the power and cost and at the same time increase the speed. The decoder was simulated using Keil software. Keywords-CommunicationViterbi, Encoder, Decoding, Algorithm I.INTRODUCTION In wireless communication AWGN (Additive White Gaussian Noise) properties of most of the communication media introduce noise in real data during transmission. The approach to error correction coding taken by modern digital communications system starts with the ground breaking work of Shannon, Hamming and Golay [1-3]. Channel Coding is a technique to introduce redundant code in real code to remove interference and error during transmission. Coded data in sender side thus increased by volume and error effect becomes less compare with uncoded data. Receiver end receives this data and decodes the data using some techniques. Viterbi decoding is one of the popular techniques to decode data effectively. Viterbi algorithm (VA) is an optimum decoding algorithm for the convolutional code. Convolutional encoding and Viterbi Decoding are widely used for reliable data transmission. The task facing the designer of a digital communication system is that of providing a cost-effective facility for transmitting information from one end of the system at a rate and a level of reliability and quality that are acceptable to the user at the other end. Viterbi decoding was developed by Andrew J. Viterbi in 1967 [1] . Since then, other researchers have expanded on his work by finding good Convolutional codes, exploring the performance limits of the technique, and varying decoder design parameters to optimize the implementation of the technique in hardware and software. The Viterbi decoding algorithm is also used in decoding trellis-coded modulation technique which is used as an effective coding technique for band limited channels as in telephone line modems to squeeze high ratios of bits-per-second in 3 kHz-bandwidth analog telephone lines [1,2]. For years, convolutional coding with Viterbi decoding has been the predominant Forward error correction (FEC) technique used in space communications, particularly in geostationary satellite communication networks, such as VSAT (very small aperture terminal)[1]. II. CONVOLUTIONAL CODES Convolutional codes are commonly specified by three parameters; (n, k, m), where: n is the number of output bits, k is the number of input bits, and m is the number of shift register stages of the coder. The constraint length L of the code represents the number of bits in the encoder memory that affect the generation of the n output bits and is defined as L = m k. The code rate r of the code is a measure of the code efficiency and is defined by r = k/n [4] Varsha P. Patil, Prof. D. G. Chougule / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 2,Mar-Apr 2012, pp.1303-1307 1304 | P a g e 1.1. Code Parameters and the Structure of the Convolutional Code Figure1 shows the convolution encoder structure CC (2, 1, 3) used in this paper and is built from its parameters. It consists of 3 (m=3) shift register stages and two modulo-2 adders (n= 2) giving the outputs of the encoder. The rate of the code is r = 1/2. The outputs of the adders are sampled sequentially yielding the code symbols. The outputs V1 and V2 of the adders are governed by the following generator polynomials: V1=U0 XOR U1 XOR U2 (1)