Throughput Analysis of Dynamic Spectrum Anti-Jamming Multiple-Access in HF Communication Systems

A multiple-access networking scheme based on the new dynamic spectrum anti-jamming system is proposed in this paper. The network consists of a center node and multiple user nodes. The center node detects spectrum holes in the operation band periodically according to the user performance target. Detected spectrum holes are allocated to users who request communication. Throughput of this networking scheme is analyzed over a high-frequency(HF) interference channel. The effect of error correction coding and spectrum hole information transmission error is discussed. Throughput of this scheme and conventional frequency-hopping multiple-access(FHMA) scheme are compared. Results show that user performance increase leads to throughput decrease, which can be offset by error correction coding. If spectrum hole information transmission is in error, the throughput is not affected much as long as the bit error rate is below 10-2. Furthermore, throughput of this scheme is obviously superior to the throughput of FHMA scheme.

Robust Trajectory and Communication Design for Angle-Constrained Multi-UAV Communications in the Presence of Jammers

This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We aim to maximize the throughput overall GTs by jointly optimizing the UAVs’trajectory,the GTs’scheduling and power allocation.Unlike most prior studies,we consider the UAVs’turning and climbing angle constraints,the UAVs’three-dimensional(3D)trajectory constraints,minimum UAV-to-UAV(U2U)distance constraint,and the GTs’transmit power requirements.However,the formulated problem is a mixed-integer non-convex problem and is intractable to work it out with conventional optimization methods.To tackle this difficulty,we propose an efficient robust iterative algorithm to decompose the original problem be three sub-problems and acquire the suboptimal solution via utilizing the block coordinate descent(BCD)method,successive convex approximation(SCA)technique,and S-procedure.Extensive simulation results show that our proposed robust iterative algorithm offers a substantial gain in the system performance compared with the benchmark algorithms.

A Heterogeneous Information Fusion Deep Reinforcement Learning for Intelligent Frequency Selection of HF Communication

The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the crowded spectrum, the time-varying channels, and the malicious intelligent jamming. The existing frequency hopping, automatic link establishment and some new anti-jamming technologies can not completely solve the above problems. In this article, we adopt deep reinforcement learning to solve this intractable challenge. First, the combination of the spectrum state and the channel gain state is defined as the complex environmental state, and the Markov characteristic of defined state is analyzed and proved. Then, considering that the spectrum state and channel gain state are heterogeneous information, a new deep Q network(DQN) framework is designed, which contains multiple sub-networks to process different kinds of information. Finally, aiming to improve the learning speed and efficiency, the optimization targets of corresponding sub-networks are reasonably designed, and a heterogeneous information fusion deep reinforcement learning(HIF-DRL) algorithm is designed for the specific frequency selection. Simulation results show that the proposed algorithm performs well in channel prediction, jamming avoidance and frequency channel selection.

Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment

The spectrum access problem of cognitive users in the fast-changing dynamic interference spectrum environment is addressed in this paper.The prior knowledge for the dynamic spectrum access is modeled and a reliability quantification scheme is presented to guide the use of the prior knowledge in the learning process.Furthermore,a spectrum access scheme based on the prior knowledge enabled RL(PKRL)is designed,which effectively improved the learning efficiency and provided a solution for users to better adapt to the fast-changing and high-density electromagnetic environment.Compared with the existing methods,the proposed algorithm can adjust the access channel online according to historical information and improve the efficiency of the algorithm to obtain the optimal access policy.Simulation results show that,the convergence speed of the learning is improved by about 66%with the invariant average throughput.

CDMA抗干扰移动通信体制的研究

ＣＤＭＡ抗干扰移动通信体制的研究主研人员：李仲令葛造坤郭传王晓蕾在宽带信号的抗干扰传输系统中，信号的高速率与要求高抗干扰性形成尖锐矛盾。在该项目支持下完成的“同步直扩码分多址发射终滞”，先将高速信号经分解形成速率Ｍ倍的Ｍ个倍码序殉，分别与Ｍ个正交扩频...

无线通信“N+1维”内生抗干扰理论与技术

The existing theory and techniques of wireless communication anti-jamming have reached their performance limit recently.With this focus,by leveraging the inherent characteristics of wireless communication and referring to the principle of cyberspace endogenous security,this paper investigates the core issues of endogenous security in the electromagnetic space,namely,endogenous anti-jamming(EAJ),which can defend against unknown electromagnetic attacks effectively.Specifically,the subspace method is first adopted to establish the unified framework for the conventional spread-spectrum,intelligent,and endogenous antijamming,in which both the intrinsic development law of each technique and the internal logic between them are revealed.Then,the fundamental concept,key techniques,and development suggestions of wireless communication“N+1 dimensionality”endogenous anti-jamming are proposed to seek a disruptive breakthrough.