Optimize the spectrum sensing and decision making strategies under uncertainty for SATCOM

The ability to provide accurate spectrum sensing and decision making under an uncertainty environment is proving useful for the military SATCOM to increases the spectrum utilization. Dynamic spectrum access(DSA) allows a secondary user to access the spectrum holes that are not occupied by the primary users. However, the spectrum sensing for DSA is normally performed in a complex SATCOM environment under uncertainty, caused by the high GEO/LEO mobility, weak signals after a long distance of propagation, the high interference and jamming in an adversarial environment, etc. The uncertainty results in a high error probability in the spectrum sensing. In such a case, DSA requires a decision-making process to optimally determine which channels to sense and access. In this paper, we propose an approach for optimal spectrum sensing and decision making that mathematically models the uncertainty in the SATCOM while the whole system throughput is maximized. Specifically, we model the DSA with decision making as a Partially Observable Markov Decision Process (POMDP) problem. Optimal DSA strategy has been discussed by an optimization process. Monte Carlo simulations are carried out and our simulation results demonstrate the efficiency of the proposed DSA strategy.