Study of HARQ Techniques for Satellite Network Support of 5G Wireless System

Integrating the satellite network with a 5G network to equip the latter with worldwide coverage and high availability is an innovative and interesting idea, however, due to the large distance of the physical link between the two networks, which is in order of hundreds or thousands of kilometers, the communications conducted over this link may not be reliable. Depending on link adaptation is a good idea to increase the link reliability and better exploit the wireless communications channel, but, in this particular link, the adaptation process alone is not enough since the channel information reported to the transmitter is outdated (the channel changes much faster than the round trip time (RTT) of the non−terrestrial system. In this thesis, The implementation of HARQ (hybrid automatic repeat request) in cooperation with ACM (adaptive coding and modulation) is considered to better handle the problem. Using HARQ control loop of feedbacks and transmissions, the reliability of the system is secured, and, by introducing a suitable margin to optimally compromise the throughput efficiency and the frame error rate (FER), and applying that margin to the parameters decided by ACM, the channel can be exploited as well as possible. As for the large RTT and outdated CSI (channel state information), the prediction will be used to forecast the channel variations and tune the ACM parameters properly to maximize the throughput efficiency of the system. Through comparing several linear and nonlinear prediction models, the prediction models proposed to replace the one−tap filter (already used) are linear prediction filter model that uses AR (autoregressive) autocorrelation computation for prediction, nonlinear ARX (autoregressive with exogenous variables) model, and a more modern model based on deep learning. MATLAB simulations are made, and based on the results obtained, using HARQ substantially increases the system performance as compared to a single−shot transmission system, HARQ can substantially increase the throughput efficiency of the system, sometimes up to 70%, therefore HARQ is recommended to be used in the transmission system of the 5G− satellite integrated network (the performance gain is worth tolerating the additional HARQ delay). Furthermore, the system performance gained by using HARQ and ACM with the one−tap filter can be further increased, where, in the results obtained via simulation in this thesis, the throughput efficiency of the system is increased at some points, by 15% in the system using the nonlinear model, and by 25% in the systems using the linear and the deep learning models (the performance is improved even more when considering lower FER), finally, comparing the three proposed prediction models, it turns out that among them the deep learning model and the linear model have the highest performance (both have a very close performance with a slight advantage to the deep learning model). The results suggest that, using the mentioned techniques, a reliable 5G−satellite link with good performance can be achieved, and that the performance can be further improved using more sophisticated prediction models.