Frequency hopping (FH) communication has good anti-fading, anti-jamming and anti-eavesdropping capabilities, so it is one of the main ways to combat electronic jamming. In order to further improve the anti-jamming capability of FH communication, the parameters such as fixed frequency interval, hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics. In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming, a heuristically accelerated Q-learning (HAQL) method is proposed in this paper. Firstly, a theoretical model for the parameter decision-making of FH system is made, and the key parameters affecting the energy efficiency of the system are analyzed. Secondly, a Q-learning model in complex electromagnetic environment is proposed, which includes setting states, actions and rewards, as well as a HAQL-based decision-making algorithm is put forward. Lastly, simulations are carried out under different jamming environments, and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm, the e-greedy QL algorithm and the HQL-OSGM algorithm, respectively.

Integrated sensing and communication (IS-AC) is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC. In this paper, we investigate the beamforming design problem for multiple-input multiple-output (MIMO) ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio (SINR) constraints of communication users. Particularly, we discuss two cases of ISAC transmit beamforming, i.e., Case-I and Case-II, which do not have and do have the dedicated probing signal, respectively. For these two cases of transmit beamforming design problems, we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors. Then, we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems. Furthermore, we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff. Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario, whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario. It is also shown that the stronger the correlation between radar and communication channels, the greater the performance gain of the system.

The space-air-ground integrated network (SAGIN) is an important sixth-generation (6G) scenario that is enabled by dynamic spot beam forming by a phased array antenna (PAA). The extremely high mobility of satellites and more complicated radio resource control (RRC) have brought introduced a new challenge, and the issue of determining appropriate moments and procedures for executing handover (HO) for all users in a coverage area is urgent. The existing research considers the users as an entirety, and it determines the HO moment under the assumption that all of the satellite subpoints (SSP) pass through the centre of the cell. However, when using this scheme, the HO failure ratio (HOFR) would experience great degradation caused by the imbalance between the unified HO moments and the uncertain spatial distribution of users' (SDU) spatial-temporal variation. This paper proposes a novel HO moment determination method for a low-orbit satellite internet network (LEO-SIN). The rules of SDU variance under SSP motion are first proposed, and they calculate dynamic UE requests within the constraints of the footprint boundary and with SSP motions. Then, we first formulate the problems of multiuser-directed graphs for HO moment determination and prove that it is a nondeterministic polynomial-time(NP) hard problem. An animal survival algorithm based on the Dingo of algorithm (DOA) is proposed to solve the above problems. Multiuser fused directed graphs are first designed to determine HO moments based on the rules of SDU variation and the animal survival algorithm. The simulations show that the proposed method has a better HO performance for LEO-SIN.

This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface (IRS) with a decode-and-forward (DF) relay to enhance spectral efficiency in extended-range scenarios. By combining the amplification capability of the active IRS and the signal regeneration function of the DF relay, the proposed system effectively mitigates path loss and fading. We derive closed-form upper bounds on the achievable rate and develop an optimal power allocation strategy under a total power constraint. Numerical results demonstrate that the hybrid scheme significantly outperforms conventional passive IRS-assisted or active IRS-only configurations, particularly under conditions of limited reflecting elements or moderate signal-to-noise ratios.

Multiple-input multiple-output (MIMO) technology has been promoted to achieve high-speed data transmission. Compared to the orthogonal frequency division multiplexing (OFDM) based MIMO systems, the single-carrier scheme (SC) has attracted lots of attention due to its low peak-to-average ratio (PAPR) feature and is quite suitable for long-distance transmission. However, one of the significant challenges of SC-MIMO systems is the vast complexity of channel equalization and signal detection, especially for the inter-symbol interference (ISI) caused by the multipath channel. The single carrier frequency domain equalization-based minimum mean square error (SCFDE-MMSE) algorithm is proved to achieve satisfying performance. However, it involves large numbers of DFTs and large-scale matrix inversions, which is unacceptable for practical systems. In this paper, a low-complexity SCFDE-MMSE (LC-SCFDE-MMSE) algorithm is proposed. Firstly, the characteristics of cyclic matrix and DFT cyclic shift are combined to reduce the number of DFTs. Secondly, SCFDE is transformed into a symbol-wise manner to avoid large-scale matrix inversions. Finally, a frequency-domain interpolation method is proposed to reduce the number of small-scale matrix inversions further. According to the evaluation results, the proposed LC-SCFDE-MMSE reduces the complexity of the traditional SCFDE-MMSE algorithm by more than one order of magnitude with less than 0.1 dB performance loss.

Advanced persistent threat (APT) can use malware, vulnerabilities, and obfuscation countermeasures to launch cyber attacks against specific targets, spy and steal core information, and penetrate and damage critical infrastructure and target systems. Also, the APT attack has caused a catastrophic impact on global network security. Traditional APT attack detection is achieved by constructing rules or manual reverse analysis using expert experience, with poor intelligence and robustness. However, current research lacks a comprehensive effort to sort out the intelligent methods of APT attack detection. To this end, we summarize and review the research on intelligent detection methods for APT attacks. Firstly, we propose two APT attack intelligent detection frameworks for endpoint samples and malware, and for malware-generated audit logs. Secondly, this paper divides APT attack detection into four critical tasks: malicious attack detection, malicious family detection, malicious behavior identification, and malicious code location. In addition, we further analyze and summarize the strategies and characteristics of existing intelligent methods for each task. Finally, we look forward to the forefront of research and potential directions of APT attack detection, which can promote the development of intelligent defense against APT attacks.

Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks (HWSNs). Low mapping efficiency and service interruption caused by mobility seriously affect the reliability of sensing tasks and ultimately affect the long-term revenue of the infrastructure providers. In response to these problems, this paper proposes an efficient virtual network embedding algorithm with a reliable service guarantee. Based on the topological attributes of nodes, a method for evaluating the physical network resource importance degree is proposed, and the nodes with rich resources are selected to improve embedding efficiency. Then, a method for evaluating the physical network reliability degree is proposed to predict the probability of mobile sensors providing uninterrupted services. The simulation results show that the proposed algorithm improves the acceptance rate of virtual sensor networks (VSN) embedding requests and the long-term revenue of the infrastructure providers.