A general framework of LSTM and transfer learning based CFDAMA strategy in broadband satellite system

Abstract

The speeding development of wireless communication technology not only provides people with increasingly available bandwidth but also makes itself presents a trend of being heterogeneous, wide-band. Nowadays, because of its broadband service capability and wide coverage, satellite networks have been paid more and more attention. This paper investigates the framework of a long-short term memory (LSTM) and transfer learning-based Combined Free/Demand Assignment Multiple Access (CFDAMA) scheme (CFDAMALSTMTL), which is verified as an effective multiple access control scheme in the broadband satellite system. As we know, there is a delay time T between the user sending a request to the satellite and receiving a reply from the satellite, and the traditional multiple access control schemes has not processed the data traffic generated in this period of time. In this paper, we propose a new prediction strategy, which combines LSTM with transfer learning, to predict the data generated in this period. We introduce the prediction method into the CFDAMA scheme so that it can reduce data accumulation by the way of sending the sum slots requested by the user and the predicted request slots generated in this delay time. In the experimental verification, we give the performance comparison of CFDAMA-LSTMTL, CFDAMA-PA, and CFDAMA-PB, which gives the effectiveness of the CFDAMA-LSTMTL in a broadband satellite system.