Research On Cross-layer Joint Transmission Mechanism Based On LTP For Deep Space Communications

Deep space communication is an important part of human spaceflight; it is also an important symbol of the development of national science and technology. Deep space communication has the characteristics which different from ground communications: extremely long space, extremely long delay, dynamic changed link, highly asymmetric up/down link, etc. In the face of these complex time-varying environment factors, it is very important to know that how to transfer the spatial data in a reliable and effective way.This paper mainly combine the LTP protocol with the data compression in the application layer, data correction in the transmission layer, spinal encoding in the data link layer/physical layer, then designs a DTN-oriented cross-layer joint transmission mechanism. This mechanism enhances the data transmission throughput further and reaches the goal of transmission optimizations; on the basis of transmit spatial data reliable and efficient.Studied the transmission mechanism of the LTP in DTN network protocol, and describes the state transition process in sender and receiver in details. Meanwhile, we analyzed the structure of division in LTP segment. The aim of LTP protocol is ensure the data can transmit reliable in the deep space link with long-space, long-delay, frequent interruptions.Build a cross-layer joint optimization model. Taking the deep space images as the example, combining the image compression in the application layer with image correction in the transmission layer, spinal encoding in the data link layer/physical layer, in order to minimize the number of total symbols needed. In the application layer and the transmission layer, compressed sensing is used to compress images. Compared with the conventional compression, the complexity of CS encoding is lower and it can realize image compression efficiently, at the same time, it also has the error correcting capability. Consequently, the CS can be used in the application layer and transmission layer. In the data link layer/physical layer, we use the spinal code which is an rateless encoding technique, its performance is better in the range of SNR(-10 d B~40d B) both in the channel of BSC?AWGN. It has lower complexity. At the same time, the incremental redundancy feature of spinal can makes it adapt to the change of channel automatically without the need of feedback.Simulate the cross-layer joint optimization model with MATLAB. This cross-layer transmission realizes continuous transmission of images data. Deal with the feedback when you receive it. Combine the feedback with Markov prediction then determine the next transmission strategy, in this way, we can take full use of the limited link resources. According to the throughput result, the mechanism of cross-layer transmission is close to the ideal transmission mechanism. And compared with other transmission mechanisms, it has a 6.3% better than prediction and retransmission mechanism, 13.8% better than additional symbols mechanism without prediction and 19.7% better than retransmission without prediction mechanism.Set up a distributed simulation platform, simulated three computers interconnected and the environment of deep space communication, such as PER, delay, asymmetric bandwidth. Then transmit the data on this platform successfully. At last, we validate the performance of LTP protocol in deep space link transmission preliminarily on this platform.