Simulation and Implementation of Convolution Encoder and Viterbi Decoder

In the present world, satellite communication has got many applications such as payload information reception in which the messages transmitted are encoded into the communication channel and then decoding it at the receiver end. Viterbi algorithm that enables clear and practically error-free communication over long distances, from moving low power transmitters and receivers. During the reception of encoded message, the data might get corrupted due to lots of disturbances in the communication channel. So it is necessary for the decoder tool to also have function of correcting the error that might occur. Viterbi algorithm has got many applications due to its error detection and correction nature. 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. In practice the decoder starts to decode bits once it has reached a time step that is a small multiple of the constraint length. The received signal is not a clear chain of zeros and ones but is code symbols from which the actual information bits can be reconstructed. Some individual bits can be dropped or distorted, because with the code symbols the missing bits can be guessed with high confidence. The decoder in the receiver evaluates the certainty by comparing the result with neighboring bits and makes the best possible guess. The result is a clear practically undamaged message. The key is in a time series of incoming information, with each set of bits tagged in order of arrival. The algorithm makes it possible to spread a carrier frequency over a wide area of the electromagnetic spectrum. Thousands of low emitting power transmitters can operate in same band range at the same time in small areas without interfering with each other, because their carrier frequencies are coded with different patterns. T he important concept to understand is that a trellis is constructed by computing the cost of being in each possible convolution encoder state at every symbol period. The data bit (0 or 1) most likely to have caused entry to each state is stored in a table. Convolutional encoding with Viterbi decoding is a FEC technique that is well suited for use with channels where the transmitted signal is corrupted mainly by Additive White Gaussian Noise (AWGN). The convolutional encoder inserts redundant information bits into the data stream so that the decoder can reduce and correct errors caused by the channel. However, these extra bits increase the data rate (bits/s) and as a consequence, also increase the bandwidth of the encoded signal. Using a technique known as puncturing, the data rate can be dynamically changed according to the channel quality. The technique works by deleting symbols from the encoded data and thus, reduces the coding rate. FEC is typically used in digital communications systems to enable the receiver to detect and correct errors without having to ask the sender for additional data. Convolutional coding and Viterbi decoding, along with quadrature phase-shift keyed modulation (QPSK), is presented as an efficient system for reliable communication. The hardware realization consists of add compare and select block(ACS); branch metric unit(BMU) block; clock divided by 2 block; serial-in-parallel out(SIPO) register block; Memory block; last-in-first-out(LIFO) structure. Performance results obtained theoretically and through computer simulation, are given for optimum short constraint length codes for a range of code constraint lengths and code rates. In present project, the hardware implementation is for code rate= 1?2 and constraint length K=3. The hardware realization is done on ALTERA?S MAX 7000S FAMILY EPM7160SLC84-7 programmable logic device. The hardware implementation is done for a single branch because of limited macro cells in EPM7160SLC84-7.Modern disk drives with ?PRML? technology to speed-up accesses; speech recognition systems, natural language systems, and a variety of communication networks use this scheme or its variants. Today the algorithm is used in billions of cell phones, magnetic recording, most satellite TV receivers, a variety of cable TV systems, voice recognition, and even DNA sequence analysis. The Transfer Control Protocol and the Internet Protocol (TCP/IP), Wi-Fi and Bluetooth are another uses of the Viterbi algorithm and methods based on it. In short, Viterbi's algorithm is enabling today's exploding wireless world.