Anti-Jamming Null Space Projection Beamforming Based on Symbiotic Radio

With the development of information technology,more and more devices are connected to the Internet through wireless communication to complete data interconnection.Due to the broadcast characteristics ofwireless channels,wireless networks have suffered more and more malicious attacks.Physical layer security has received extensive attention from industry and academia.MIMO is considered to be one of the most important technologies related to physical layer security.Through beamforming technology,messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR by legitimate users.Combining the symbiotic radio(SR)technology,this paper considers a symbiotic radio antijamming MIMO system equipped with a multi-antenna system at the main base station.In order to avoid the interference signal and improve the SINR of the signal received by the user.The base station is equipped with a uniform rectangular antenna array,and using Null Space Projection(NSP)Beamforming,Intelligent Reflecting Surface(IRS)can assist in changing the beam’s angle.The simulation results show that NSP Beamforming could make a better use of the null space of interference,which can effectively improve the received SINR of users under directional interference,and improve the utilization efficiency of signal energy.

GNSS array receiver faced with overloaded interferences:anti-jamming performance and the incident directions of interferences

Anti-jamming solutions based on antenna arrays enhance the anti-jamming ability and the robustness of global navigation satellite system(GNSS)receiver remarkably.However,the performance of the receiver will deteriorate significantly in the overloaded interferences scenario.We define the overloaded interferences scenario as where the number of interferences is more than or equal to the number of antenna arrays elements.In this paper,the effect mechanism of interferences with different incident directions is found by studying the anti-jamming performance of the adaptive space filter.The theoretical analysis and conclusions,which are first validated through numerical examples,reveal the relationships between the optimal weight vector and the eigenvectors of the input signal autocorrelation matrix,the relationships between the interference cancellation ratio(ICR),the signal to interference and noise power ratio(SINR)of the adaptive space filter output and the number of interferences,the eigenvalues of the input signal autocorrelation matrix.In addition,two simulation experiments are utilized to further corroborate the theoretical findings through soft anti-jamming receiver.The simulation results match well with the theoretical analysis results,thus validating the effect mechanism of overloaded interferences.The simulation results show that,for a four elements circular array,the performance difference is up to 19 dB with different incident directions of interferences.Anti-jamming performance evaluation and jamming deployment optimization can obtain more accurate and efficient results by using the conclusions.

Dynamic Spectrum Anti-Jamming with Distributed Learning and Transfer Learning

Physical-layer security issues in wireless systems have attracted great attention.In this paper,we investigate the spectrum anti-jamming(AJ)problem for data transmissions between devices.Considering fast-changing physical-layer jamming attacks in the time/frequency domain,frequency resources have to be configured for devices in advance with unknown jamming patterns(i.e.the time-frequency distribution of the jamming signals)to avoid jamming signals emitted by malicious devices.This process can be formulated as a Markov decision process and solved by reinforcement learning(RL).Unfortunately,stateof-the-art RL methods may put pressure on the system which has limited computing resources.As a result,we propose a novel RL,by integrating the asynchronous advantage actor-critic(A3C)approach with the kernel method to learn a flexible frequency pre-configuration policy.Moreover,in the presence of time-varying jamming patterns,the traditional AJ strategy can not adapt to the dynamic interference strategy.To handle this issue,we design a kernelbased feature transfer learning method to adjust the structure of the policy function online.Simulation results reveal that our proposed approach can significantly outperform various baselines,in terms of the average normalized throughput and the convergence speed of policy learning.

Anti-jamming channel access in 5G ultra-dense networks: a game-theoretic learning approach

This paper investigates the Quality of Experience(QoE)oriented channel access anti-jamming problem in 5th Generation Mobile Communication(5G)ultra-dense networks.Firstly,considering that the 5G base station adopts beamforming technology,an anti-jamming model under Space Division Multiple Access(SDMA)conditions is proposed.Secondly,the confrontational relationship between users and the jammer is formulated as a Stackelberg game.Besides,to achieve global optimization,we design a local cooperation mechanism for users and formulate the cooperation and competition among users as a local altruistic game.By proving that the local altruistic game is an Exact Potential Game(EPG),we further prove the existence of pure strategy Nash Equilibrium(NE)among users and Stackelberg Equilibrium(SE)between users and jammer.Thirdly,to obtain the equilibrium solutions of the proposed games,we propose an anti-jamming channel selection algorithm and improve its convergence speed through heterogeneous learning parameters.The simulation results validate the convergence and effectiveness of the proposed algorithm.Compared with the throughput optimization scheme,our proposed scheme obtain a greater network satisfaction rate.Finally,we also analyze user fairness changes during the algorithm convergence process and get some interesting conclusions.

Studies on Novel Anti-jamming Technique of Unmanned Aerial Vehicle Data Link

Based on the M-ary spread spectrum （M-ary-SS）, direct sequence spread spectrum （DS-SS）, and orthogonal frequency division multiplex （OFDM）, a novel anti-jamming scheme, named orthogonal code time division multi-subchannels spread spectrum modulation （OC-TDMSCSSM）, is proposed to enhance the anti-jamming ability of the unmanned aerial vehicle （UAV） data link. The anti-jamming system with its mathematical model is presented first, and then the signal formats of transmitter and receiver are derived. The receiver＇s bit error rate （BER） is demonstrated and anti-jamming performance analysis is carded out in an additive white Ganssian noise （AWGN） channel. Theoretical research and simulation results show the anti-jamming performance of the proposed scheme better than that of the hybrid direct sequence frequency hopping spread spectrum （DS/FH SS） system. The jamming margin of the OC-TDMSCSSM system is 5 dB higher than that of DS/FH SS system under the condition of Rician channel and full-band jamming, and 6 dB higher under the condition of Rician channel environment and partial-band jamming.

Put Others Before Itself:A Multi-Leader One-Follower Anti-Jamming Stackelberg Game Against Tracking Jammer

This paper mainly investigates the coordinated anti-jamming channel access problems in multiuser scenarios where there exists a tracking jammer who senses the spectrum and traces the channel with maximal receiving power.To cope with the challenges brought by the tracking jammer,a multi-leader onefollower anti-jamming Stackelberg(MOAS)game is formulated,which is able to model the complex interactions between users and the tracking jammer.In the proposed game,users act as leaders,chose their channel access strategies and transmit firstly.The tracking jammer acts as the follower,whose objective is to find the optimal jamming strategy at each time slot.Besides,the existence of Stackelberg equilibriums(SEs)is proved,which means users reach Nash Equilibriums(NEs)for each jamming strategy while the jammer finds its best response jamming strategy for the current network access case.An active attraction based anti-jamming channel access(3ACA)algorithm is designed to reach SEs,where jammed users keep their channel access strategies unchanged to create access chances for other users.To enhance the fairness of the system,users will adjust their strategies and relearn after certain time slots to provide access chances for those users who sacrifice themselves to attract the tracking jammer.

Space-borne antenna adaptive anti-jamming method based on gradient-genetic algorithm

A novel space-borne antenna adaptive anti-jamming method based on the genetic algorithm （GA）, which is combined with gradient-like reproduction operators is presented, to search for the best weight for pattern synthesis in radio frequency （RF）. Combined, the GA＇s the capability of the whole searching is, but not limited by selection of the initial parameter, with the gradient algorithm＇s advantage of fast searching. The proposed method requires a smaller sized initial population and lower computational complexity. Therefore, it is flexible to implement this method in the real-time systems. By using the proposed algorithm, the designer can efficiently control both main-lobe shaping and side-lobe level. Simulation results based on the spot survey data show that the algorithm proposed is efficient and feasible.

Cognitive anti-jamming receiver under phase noise in high frequency bands

This paper investigates the jamming sensing performance of the simultaneous transmit and receive based cognitive anti-jamming(SCAJ) receiver impaired by phase noise in local oscillators(LO) over fading channels. Firstly, energy detection(ED)based on the jamming to noise ratio(JNR) of the high frequency bands SCAJ receiver with phase noise under different channels is analyzed. Then, the probabilities of jamming detection and false alarm in closed-form for the SCAJ receiver are derived. Finally,the modified Bayesian Cramer-Rao bound(BCRB) of jamming sensing for the SCAJ receiver is presented. Simulation results show that the performance degradation of the SCAJ system due to phase noise is more severe than that due to the channel fading in the circumstances where the signal bandwidth(BW) is kept a constant. Moreover, the signal BW has an effect on the phase noise in LO, and the jamming detection probability of the wideband SCAJ receiver with lower phase noise outperforms that of the narrowband receiver using the same center frequency. Furthermore,an accurate phase noise estimation and compensation scheme can improve the jamming detection capability of the SCAJ receiver in high frequency bands and approach to the upper bound.

An Active Anti-Jamming Approach for Frequency Diverse Array Radar with Adaptive Weights

Due to the rapid development of electronic countermeasures(ECMs),the corresponding means of electronic counter countermeasures(ECCMs)are urgently needed.In this paper,an act-ive anti-jamming method based on frequency diverse array radar is proposed.By deriving the closed form of the phase center in a uniform line array FDA,we establish a model of the FDA signal based on adaptive weights and derive the effect of active anti-jamming in this regime.The pro-posed active anti-jamming method makes it difficult for jammers to detect or locate our radar.Fur-thermore,the effectiveness of the two frequency increment schemes in terms of anti-jamming is ana-lyzed by comparing the deviation of phase center.Finally,the simulation results verify the effective-ness and superiority of the proposed method.

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.

Anti-Jamming Algorithm Based on Spatial Blind Search for Global Navigation Satellite System Receiver

A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed,which uses multiple single-constrained subspace projection parallel filters.If the direction of arrival(DOA)of a satellite signal is unknown,the traditional subspace projection anti-jamming algorithm cannot form the correct beam pointing.To overcome the problem of the traditional subspace projection algorithm,multiple single-constrained subspace projection parallel filters are used.Every single-constrained anti-jamming subspace projection algorithm obtains the optimal weight vector by searching the DOA of the satellite signal and uses the output of cross correlation as a decision criterion.Test results show that the algorithm can suppress the jamming effectively,and generate high gain toward the desired signal.The research provides a new idea for the engineering implementation of a multi-beam anti-jamming algorithm based on subspace projection.

Combined algorithm of acquisition and anti-jamming based on SFT

A communication and navigation receiver is required to remove hostile jamming signals and synchronize receiving signals effectively especially for satellite communication and navigation whose resources are becoming more and more limited. This paper proposes a novel signal receiving method by combining the pro- cesses of anti-jamming and synchronization to reduce the overall computationa~ complexity at the expense of slightly affecting the detection probability, which is analyzed in detail by derivations. Furthermore, this paper introduces sparse Fourier transformation （SFT） into the proposed algorithm to replace fast Fourier transfor- mation （FFT） so as to further reduce the calculation time especially in large frequency offset environments.

EFFICIENT DESIGN OF ANTI-JAMMING RATELESS CODING IN COGNITIVE OFDM

Efficient anti-jamming rateless coding based on cognitive Orthogonal Frequency Division Multiplexing (OFDM) modulation in Cognitive Radio Network (CRN) is mainly discussed. Rateless coding with small redundancy and low complexity is presented, and the optimal design methods of building rateless codes are also proposed. In CRN, anti-jamming rateless coding could recover the lost packets in parallel channels of cognitive OFDM, thus it protects Secondary Users (SUs) from the in-terference by Primary Users (PUs) efficiently. Frame Error Rate (FER) and throughput performance of SU employing anti-jamming rateless coding are analyzed in detail. Performance comparison between rateless coding and piecewise coding are also presented. It is shown that, anti-jamming rateless coding provides low FER and Word Error Rate (WER) performance with uniform sub-channel selection. Meanwhile, it is also verified that, in higher jamming rate and longer code redundancy scenario, rateless coding method could achieve better FER and throughput performance than another anti-jamming coding schemes.

TIME-VARYING AR MODELING AND ADAPTIVE IIR NOTCH FILTER FOR ANTI-JAMMING DSSS RECEIVER

Using Time-Varying AR (TVAR) model and adaptive notch filter is a new method for the non-stationary jammer suppression in Direct Sequence Spread Spectrum (DSSS). The performance of TVAR model for Instantaneous Frequency (IF) estimation will be affected by some factors such as basis functions. Focusing on this problem, the optimal basis function of TVAR model for the IF estimation of the LFM signal is obtained in this paper. Besides the depth and width of notching, the phase properties of notch filter affect the Signal-to-Interference plus-Noise Ratio (SINR) of correlation output to the narrowband jammer suppression in DSSS, in response to the problem the closed solution of correlation output SINR improvement has been derived when a single frequency jammer passes through direct IIR notch filter, and its performance has been compared with those of five coefficient FIR filters. Later, a novel method for LFM jammer suppression based on Fourier basis TVAR model and direct IIR notch filter is proposed. The simulation results show the effectiveness of the proposed method.

Comparison of the Radar Receiver Anti-Jamming Circuits Performance

This paper researches on some key technologies of anti-jamming of an air-borne radar receiver, the automatic testing of AGC, IAGC and multi-filtering under one million noisy pulses by the computer simulation system. The system tests the width of the jamming pulse whose width is 100% bigger, 60% bigger and 100% smaller than the Radar signal’s respectively and show the SNR curve.

A target parameter estimation method via atom-reconstruction in radar mainlobe jamming

Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.

Joint power control and passive beamforming optimization in RIS-assisted anti-jamming communication

Due to the openness of the wireless propagation environment,wireless networks are highly susceptible to malicious jamming,which significantly impacts their legitimate communication performance.This study investigates a reconfigurable intelligent surface(RIS)assisted anti-jamming communication system.Specifically,the objective is to enhance the system’s anti-jamming performance by optimizing the transmitting power of the base station and the passive beamforming of the RIS.Taking into account the dynamic and unpredictable nature of a smart jammer,the problem of joint optimization of transmitting power and RIS reflection coefficients is modeled as a Markov decision process(MDP).To tackle the complex and coupled decision problem,we propose a learning framework based on the double deep Q-network(DDQN)to improve the system achievable rate and energy efficiency.Unlike most power-domain jamming mitigation methods that require information on the jamming power,the proposed DDQN algorithm is better able to adapt to dynamic and unknown environments without relying on the prior information about jamming power.Finally,simulation results demonstrate that the proposed algorithm outperforms multi-armed bandit(MAB)and deep Q-network(DQN)schemes in terms of the anti-jamming performance and energy efficiency.

Adaptive Antenna Utilizing Power Inversion and Linearly Constrained Minimum Variance Algorithms

This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.

Anti-Jamming with Adaptive Arrays Utilizing Power Inversion Algorithm

The convergence rate of the power inversion （PI） algorithm is quite sensitive to the power of the interference with the used fixed parameters in the PI algorithm leading to degradation of its ability to handle interference. This paper presents a normalized PI algorithm that traces the stochastic characteristics of the interference. The algorithm adaptively adjusts the recursive step size to determine the constrained optimized parameters for the Iowpass filter. Simulations show that the normalized PI algorithm achieves faster convergence and produces deeper nulls. The algorithm makes GPS receivers more robust in environments with large variations in the interference strength.

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.