Equilibrium Approximating and Online Learning for Anti-Jamming Game of Satellite Communication Power Allocation

Abstract

Satellite communication systems are increasingly facing serious environmental challenges such as malicious jamming, monitoring, and intercepting. As a current development of artificial intelligence, intelligent jammers with learning ability can effectively perceive the surrounding spectrum environment to dynamically change their jamming strategies. As a result, the current mainstream satellite communication anti-jamming technology based on wide interval high-speed frequency hopping is unable to deal with this problem effectively. In this work, we focus on anti-jamming problems in the satellite communication domain, and reformulate the power allocation problem under two kinds of confrontation scenarios as one-shot and repeated games model. Specifically, for the problem of multi-channel power allocation under a one-shot confrontation scenario, we firstly model the problem of allocating limited power resource between communication parties and a jammer on multi-channel based on a BG (Blotto Game) model. Secondly, a DO-SINR (Double Oracle-Signal to Interference plus Noise Ratio) algorithm is designed to approximate the Nash equilibrium of the game between two parties. Experiments show that the DO-SINR algorithm can effectively obtain the approximate Nash equilibrium of the game. For the problem of multi-channel power allocation under a repeated confrontation scenario, we firstly transform the problem into an online shortest path problem with a graph structure to make the problem solving process more intuitive, and then design the Exp3-U (Exp3-Uniform) algorithm which utilizes the graph structure to solve the multi-channel power allocation problem. Experiments show that our algorithm can minimize the expected regret of communication parties during online confrontation, while maintaining good operating efficiency. The two power allocation problems constructed in this paper are common problem formed in confrontation scenarios. Our research and analysis can simulate some actual confrontation scenarios of the satellite communication power allocation, which can be used to improve the adaptability of satellite communication systems in complex environments.

Adaptive Spectrum Anti-Jamming in UAV-Enabled Air-to-Ground Networks: A Bimatrix Stackelberg Game Approach

“…Jammers, endowed with learning capabilities, can fluidly recalibrate their jamming tactics, adeptly sensing the spectral milieu. This agility renders traditional anti-jamming mechanisms somewhat obsolete, catalyzing a shift towards AI-centric solutions [31][32][33][34][35]. For instance, ref.…”

“…For instance, ref. [32] reimagines power allocation challenges in adversarial contexts, crafting algorithms that approximate the Nash equilibrium between communicators and a jammer. Ref.…”

Adaptive Satellite Navigation Anti-Interference Algorithm Based on Inverse Cosine Function

“…Narrowband interference is a common form of interference signal utilized by a variety of interference equipment because it is simple to produce, cheap, and has a strong interference impact [11]. The three basic processing domains used for narrowband interference suppression are time, frequency, and combined domain [12][13][14][15]. One of the most popular methods for reducing narrowband interference in navigation receivers is timedomain anti-interference processing [16].…”