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Abstract-This letter investigates the transmit power and trajectory optimization problem for unmanned aerial vehicle (UAV)-aided networks. Different from majority of the existing studies with fixed communication infrastructure, a dynamic scenario is considered where a flying UAV provides wireless services for multiple ground nodes simultaneously. To fully exploit the controllable channel variations provided by the UAV's mobility, the UAV's transmit power and trajectory are jointly optimized to maximize the minimum average throughput within a given time length. For the formulated non-convex optimization with power budget and trajectory constraints, this letter presents an efficient joint transmit power and trajectory optimization algorithm. Simulation results validate the effectiveness of the proposed algorithm and reveal that the optimized transmit power shows a water-filling characteristic in spatial domain.

This paper investigates the multiuser power control problem in relay-assisted anti-jamming systems. Because of the hierarchical confrontation characteristics between users and jammer, we take the incomplete information and observation error into consideration and formulate an anti-jamming Bayesian three-layer Stackelberg game, in which primary users act as leaders, relay users act as vice-leaders, and jammer acts as a follower. Both users and jammer have the ability to sense others' transmission power and choose optimal power to realize the maximum of utility. Based on the backward induction method, we propose a multiuser hierarchical iterative algorithm to obtain the Stackelberg equilibrium (SE) and prove the existence and uniqueness of SE. Finally, simulation results are compared with the Nash equilibrium to verify the effectiveness of the proposed game. Moreover, both the influence of incomplete information and the observation error on utility are analyzed. INDEX TERMS Power control, anti-jamming, three-layer Stackelberg game, Stackelberg equilibrium.

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This paper investigates the cooperative anti-jamming distributed channel selection problem in UAV communication networks. Considering the existence of malicious jamming and co-channel interference, we design an interference-aware cooperative anti-jamming scheme for the purpose of maximizing users’ utilities. Moreover, the channel switching cost and cooperation cost are introduced, which have a great impact on users’ utilities. Users in the UAV group sense the co-channel interference signal energy to judge whether they are influenced by co-channel interference. When the received co-channel interference signal energy is lower than the co-channel interference threshold, users conduct channel selection strategies independently. Otherwise, users cooperate with each other and take joint actions with a cooperative anti-jamming pattern under the impact of co-channel interference. Aiming at the independent anti-jamming channel selection problem under no co-channel interference, a Markov decision process framework is introduced, whereas for the cooperative anti-jamming channel selection case under the influence of co-channel mutual interference, a Markov game framework is employed. Furthermore, motivated by Q-learning with a “cooperation-decision-feedback-adjustment” idea, we design an interference-aware cooperative anti-jamming distributed channel selection algorithm (ICADCSA) to obtain the optimal anti-jamming channel strategies for users in a distributed way. In addition, a discussion on the quick decision for UAVs is conducted. Finally, simulation results show that the proposed algorithm converges to a stable solution with which the UAV group can avoid malicious jamming, as well as co-channel interference effectively and can realize a quick decision in high mobility UAV communication networks.

A new recognition algorithm to the symbol shaped signals is presented, in which eight digital modulation types are classified. The infection to signals and parameters' extraction aroused by symbol shape is introduced in detailed, and the modulation types are classified from the decision-tree classifier. The computer simulation results show that, the algorithm has a good recognition performance for the shaped signals, further more it has a better recognition performance than the methods without consideration of the symbol shape.I.

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In this paper, we study joint relay selection and the power control optimization problem in an anti-jamming relay communication system. Considering the hierarchical competitive relationship between a user and jammer, we formulate the anti-jamming problem as a Stackelberg game. From the perspective of game, the user selects relay and power strategy firstly which acts as the leader, while the jammer chooses power strategy then that acts as follower. Moreover, we prove the existence of Stackelberg equilibrium. Based on the Q-learning algorithm and multi-armed bandit method, a hierarchical joint optimization algorithm is proposed. Simulation results show the user’s strategy selection probability and the jammer’s regret. We compare the user’s and jammer’s utility under the proposed algorithm with a random selection algorithm to verify the algorithm’s superiority. Moreover, the influence of feedback error and eavesdropping error on utility is analyzed.