Study And Application Of Low Complexity Adaptive Decoding Algorithm For Turbo Product Code

Effectiveness and reliability of information transmission are two very important indicators in moderncommunication systems. In order to achieve these two indicators, experts in the field of communicationhave studied and explored constantly. Channel coding is a key technology to improve system performance,which can largely guarantee the validity of information transmission. Turbo Product Code is an efficientforward error correction coding technique. Its decoding complexity is relatively low with fast iterativeconvergence rate. What’s more, it can still guarantee a strong error correction performance at low SNR.These advantages allow Turbo product codes become a hot research in the field of communicationsystems. On the other hand, in order to improve the effectiveness of information transmission, MIMO(Multiple-Input Multiple-Output) technology has aroused extensive research during recent years. It canimprove the information transmission rate and channel capacity by increasing the transmit antennas andreceive antennas.This paper will combine the technology of TPC with MIMO, and focus on the TPC error correctionperformance in SISO (Single-Input Single-Output) and MIMO systems. Besides, the performance of TPCin efficient spectrum modulation techniques SOQPSK/OQPSK of aeronautical telemetry is also analyzed.Most importantly, an adaptive Chase decoding algorithm is proposed, which can greatly reduce thedecoding complexity, improve the efficiency of information transmission and reduce decoding delay withlittle BER performance loss.Different from the previous reported results, during decoding, the new adaptive algorithm is based onthe statistics of the number of the candidate sequences with the same minimum squared Euclideandistance in each row or column of TPC block firstly, and then the Least Reliable Bits (LRBs) can changeaccording to the statistical results via the proposed steps. It can be verified from Monte Carlo simulations,when using the same extended hamming code with bit rate0.66as TPC subcodes, the Bit Error Rate(BER) is10-4, the coding loss of the proposed adaptive algorithm is just about0.03dB compared with R.Pyndiah’s iterative decoding algorithm using the fixed LRBs parameter in Chase decoder, but the averagecomplexity of the proposed algorithm could be reduced about45%.Finally, by using Xilinx ISE Design Suite12.2development platform, the hardware functionalsimulation of the TPC coding and decoding based on FPGA is successfully achieved in the paper. It gives the overall system design as well as the input and output interfaces of each module. The programminglanguage is Verilog, a hardware description language. The ModelSim is used as the functional simulationsoftware. Through simulation, the results in ModelSim are consistent with those in Matlab.