МЕТОД АДАПТИВНОГО ВИБОРУ РОЗМІРУ ДІАГРАМ СТАНІВ ТУРБО КОДІВ У СИСТЕМАХ 5G ТА IoT

Abstract

The article proposes a method for optimizing the operation of the turbocode encoder/decoder in 5G and IoT systems due to the adaptive selection of the state diagram size using the proposed decoding uncertainty indicator.The principles of forming state diagrams of the turbo code encoder and decoder are considered, and the uncertainty of data decoding is clarified. Using the a priori and a posteriori data of the turbo code decoder, an algorithm for changing the state diagram of the turbo code encoder/decoder is proposed.The essence of the method is to optimize the operation of the turbo code encoder and decoder by using adaptive selection of the state diagram size using the proposed decoding uncertainty indicator. The implementation of the method will allow to increase the given indicators of reliability of information without reducing the bandwidth of systems and networks of wireless data transmission systems.In contrast to the known results, depending on the signal-to-noise ratio in the channel and the values of the normalized number of sign changes of the a posteriori-prior logarithmic relations of the likelihood functions about the transmitted data bits of the turbo code decoder, an adaptive selection of the state diagram size of the TC encoder/decoder is made.The simulation analysis shows that in order to ensure the given indicators of information reliability, the method selects a rational size of the TC encoder/decoder state diagram, which is confirmed by comparison with other simulation results.The method can be used together with other methods of adaptation, for example, with adaptation of coding speed, poly-nomials of TC component codes, in systems with multi-parameter adaptation operating under conditions of a priori uncertainty. The types of virtual agents in social networks are distinguished: primary source, bot accounts, troll accounts, real people