Frequency Hopping System Research Articles

Intelligent decision-making for a “Three-Variable” frequency-hopping pattern based on OC-CDRL

The frequency hopping pattern of the existing frequency hopping communication system is not designed according to the electromagnetic interference environment, resulting in blind anti-jamming. Therefore, to address this problem, a “three-variable” frequency-hopping pattern is proposed, where the frequency, hopping rate, and instantaneous bandwidth of the frequency-hopping signal vary randomly based on the background electromagnetic interference. The decision-making problem of the “three-variable” frequency-hopping pattern is modeled as a Markov decision process (MDP) by constructing the state-action-reward tuple. The designed frequency varies continuously within a small frequency band selected from a pseudo-random sequence to alleviate the problem of dimension explosion in decision-making. At the same time, discrete values for the hopping rate and instantaneous bandwidth are designed. To solve this MDP problem efficiently, a combined deep reinforcement learning algorithm (OC-CDRL) based on optimistic exploration and conservative estimation is proposed, which combines the features of TD3 and D3QN algorithms and designs the corresponding states, actions, and rewards to deal with continuous and discrete action spaces, respectively. To address the problem that the D3QN algorithm tends to fall into local optimal solutions, an optimistic exploration strategy (OES) for action selection is proposed to improve the degree of exploration. Moreover, the loss function is improved by conservatively estimating state–action pairs outside the experience replay buffer, reducing the overestimation of the optimistic action-value function and increasing the stability and convergence of the algorithm. Comparative simulation results of the algorithms in different electromagnetic interference environments show that the OC-CDRL algorithm effectively avoids most regions with higher interference and has better adaptability and anti-jamming capability.

Construction of secure adaptive frequency hopping sequence sets based on AES algorithm

AbstractCommunication security has become particularly crucial with the rapid development of the Internet of Things (IoT). Frequency hopping spread spectrum (FHSS) technology, a prevalent method in wireless communication, has a wide range of applications in the Internet of Things. Enhancing the security of frequency hopping sequences is an essential means to improve the security of frequency hopping communication in the Internet of Things, as the performance of frequency hopping sequences plays a crucial role in frequency hopping systems. This paper proposes constructing secure adaptive frequency hopping sequence sets based on the advanced encryption standard (AES) algorithm. As a block cipher algorithm with superior security, the AES algorithm can provide a fundamental guarantee for the security of the proposed frequency hopping sequences. The mapping methods from ciphertext sequences to frequency hopping sequences proposed in this paper can achieve the construction of frequency hopping sequences of any frequency set size to meet the requirements of adaptive frequency hopping. In addition, we also model and analyse the problem of overlapping spectrum band of the IoT groups in the industrial, scientific, and medical (ISM) band, aiming to achieve better packet transmission performance by adjusting the frequency set size.

Demonstration of THz frequency hopping in the 300 GHz band based on UTC-PD and tunable DFB laser array

We explored the potential of an optoelectronic frequency hopping system within the 300 GHz band, leveraging a tunable distributed feedback laser array and uni-traveling carrier photodiode. Our experiments successfully achieved a 10-channel terahertz (THz) frequency hopping, marking a significant advancement in THz secure communication technologies. Notably, the system exhibited a rapid frequency-hopping capability with a short transition time of 0.8 ms between channels, ranging from 288 to 331 GHz. Further, we conducted data transmission tests at a rate of 5 Gbit s−1 across several channels. The results were promising, showing each channel maintained a clear eye pattern and a low bit error rate, crucial factors for reliable and secure data transmission. These findings not only demonstrate the efficacy of our system but also open new avenues for high-speed, secure THz communication.

EQS-Band Human Body Communication through frequency hopping and MCU-Based transmitter

Human Body Communication (HBC) is an emerging technology that uses the human body as a communication channel. It offers significant advantages over traditional RF techniques in terms of power consumption and security. In recent developments, Electro-quasistatic HBC (EQS-HBC) in the frequency band below 1 MHz has been employed to enable communication without signal radiation beyond the body, effectively turning the body into a wired communication medium. This paper delves into the application of the EQS band for HBC. Experimental results show the determinantal effect of intermittent noise that sporadically disrupts communications across the band of interest. To address this challenge, we introduce an innovative frequency-hopping transceiver system, which allows the transmitter to seamlessly adapt to different frequencies. In addition, we present a miniature transmitter design, incorporating a simplified micro-controller unit (MCU) to facilitate the implementation of HBC. Furthermore, to validate this proposed design, we present a fully functional prototype of an HBC system that effectively employs frequency hopping techniques for practical applications.

Channel Estimation Methods for Frequency Hopping System Based on Machine Learning

Channel Estimation Methods for Frequency Hopping System Based on Machine Learning

A High-Performance, Low-Cost, and Integrated Hairpin Topology RF Switched Filter Bank for Radar Applications.

Switched filter banks find widespread application in frequency-hopping radar systems and communication networks with multiple operating frequencies, especially in situations demanding elevated filter element isolation. In this paper, the design and implementation of a highly isolated switchable narrow-bandpass filter bank architecture using hairpin microstrip topology is presented. The filter bank has four discrete bandpass filters with passbands of 2.0-2.2 GHz, 2.3-2.5 GHz, 3.1-3.3 GHz, and 3.9-4.1 GHz. These filters span the radar S-frequency band (2.0-4.0 GHz). In order to switch between channels with a switching speed of nanoseconds, low-loss and highly isolated SP4T switches are implemented. Advanced design system (ADS) software is used to design the various filter functionalities, and the entire system is tested on a vector network analyzer (VNA). The proposed architecture makes it much easier to put the filter bank into practice and switch it to the desired frequency, which is useful for radar receiver applications.

Analysis of Transceiver RF Impairments on Artificial Noise Suppression in Frequency-Hopping Systems

Analysis of Transceiver RF Impairments on Artificial Noise Suppression in Frequency-Hopping Systems

Variable-Speed Frequency-Hopping Signal Sorting: Spectrogram Is Sufficient

In this paper, we present a novel signal sorting method aimed at reducing the impact of interference and noise while achieving blind detection and accurate sorting of a variable-speed frequency-hopping communication system. To achieve this, we combine spectrogram analysis with an innovative sorting approach. First, we generate the spectrogram of the received signal, and then employ a morphology filter to effectively eliminate noise and sweep frequency interference from the spectrogram. Subsequently, we identify and mark connected domains in the spectrogram, from which we extract the duration data to create a dataset specifically for separating fixed-frequency interference. Furthermore, we propose a specialized time alignment algorithm designed to accommodate the unique characteristics of variable-speed frequency-hopping signals, enabling precise sorting of variable-speed frequency-hopping signals. Through rigorous comparative evaluations against existing algorithms, we demonstrate that our proposed approach provides superior accuracy by offering a clearer representation of the time–frequency situation of the received signals. The proposed method provides a high correct sorting probability which is equal to 0.8 when signal-to-noise ratio is 0 dB and reaches 1 when signal-to-noise ratio reaches over 12 dB. In comparison, the correct sorting probability of the comparison algorithm is far inferior to the proposed algorithm.

A Capacity Enhancement Method for Frequency-Hopping Anti-Jamming Communication Systems

In this paper, we study the enhancement of channel transmission information by expanding the transmission channel in the frequency-hopping rate dimension in a communication system. This is achieved using the frequency-hopping spread spectrum (FHSS) without increasing communication resources, such as power and bandwidth. The anti-jamming capability of the original information is maintained during this process. The spectral characteristics of the extended signal for frequency-hopping (FH) transmission are investigated, a demodulation method based on carrier reconstruction is proposed, the bit error rate performance is simulated, and the capacity enhancement and anti-jamming ability of the extended signal for FH transmission are analyzed.

Intelligent Reception of Frequency Hopping Signals Based on CVDP

The frequency hopping communication systems have been widely used in anti-jamming communication due to their anti-interception and anti-interference capabilities. With the increasingly complex electromagnetic environment, the transmitter of the frequency hopping communication system adopts more flexible frequency hopping patterns to cope with interference. Therefore, to address the problem of traditional frequency hopping receiver systems being unable to receive properly due to intelligent frequency hopping sequence decisions made at the transmitter, we design a CVDP (CNN_VIT_Dual Multi-head Probsparse Self-attention) network based on a convolutional neural network (CNN) module and Transformer Encoder module to realize the intelligent reception of frequency hopping signals. The designed CNN module extracts the global features and spatial information of the time-frequency spectrograms and serves as the input of the VIT (Vision Transformer) network, which not only solves the problem that the VIT network is difficult to converge on small data sets but also improves the stability and robustness of the VIT network. In the Transformer Encoder module of the VIT network, a dual multi-head self-attention mechanism is used to extract critical time-frequency features and a Probsparse self-attention idea is introduced to reduce the computational complexity. Simulation results on hopping frequency estimation and received BER(Bit Error Rate) of CVDP networks in different interference and channel environments show that when a hopping sequence is unknown, CVDP-based intelligent hopping receiver systems can achieve nearly the same receiver performance as conventional reception systems in which a hopping sequence is known.

Deep-Learning-Based Recovery of Frequency-Hopping Sequences for Anti-Jamming Applications

The frequency-hopping communication system has been widely used in anti-jamming communication due to its anti-interception and anti-jamming performance. With the increasingly complex electromagnetic environment, the frequency-hopping communication system needs more flexible frequency-hopping patterns to deal with interferences, which brings great challenges to the communication receiver. In this paper, an intelligent receiving scheme of frequency-hopping sequences is proposed, which combines time–frequency analysis with deep learning to realize an intelligent estimation of frequency-hopping sequences. A hybrid network module is designed by combining a convolutional neural network (CNN) with a gated recurrent unit (GRU). In the proposed network module, the combination of a residual network (ResNet) and squeeze and extraction (SE) improves the feature extraction and expression capabilities of the CNN network. The GRU network is proposed to solve the problem of dealing with signals with variant input lengths. A transfer learning scheme is further proposed to deal with communications systems with different frequency-hopping sets. Simulation results show that the proposed method has strong generalization ability and robustness, and the bit error rate (BER) performance of intelligent receiving is close to the receiving performance under ideal conditions.

Optimal Constructions of Low-Hit-Zone Frequency-Hopping Sequence Sets via Cyclotomy

In complex environments of wireless communication, to improve the communication anti-interference performance, quasi-synchronous frequency-hopping (FH) communication system requires low-hit-zone (LHZ) FH sequence sets with optimal Hamming correlation (HC) properties and flexible parameters. In this paper, based upon cyclotomy theory, two classes of LHZ FH sequence sets with flexible parameters not included in the literatures are designed, and the periodic HC properties of which are analyzed. It turns out that the designed LHZ FH sequence sets are optimal on the maximum periodic HC. And thus the new constructions can be used to provide optimal FH sequence sets for quasi-synchronous FH communication system.

Optimal and near-optimal frequency-hopping sequences based on Gaussian period

<abstract><p>Frequency-hopping sequences (FHSs) have a decisive influence on the whole frequency-hopping communication system. The Hamming correlation function plays an important role in evaluating the performance of FHSs. Constructing FHS sets that meet the theoretical bounds is crucial for the research and development of frequency-hopping communication systems. In this paper, three new classes of optimal FHSs based on trace functions are constructed. Two of them are optimal FHSs and the corresponding periodic Hamming autocorrelation value is calculated by using the known Gaussian period. It is shown that the new FHSs are optimal according to the Lempel-Greenberger bound. The third class of FHSs is the near-optimal FHSs.</p></abstract>

Blind Vector Parameter Estimation for Burst Type CPM Transmissions

Short burst continuous phase modulation transmission is of practical relevance in e.g. frequency hopping systems applied in sensor or tactical networks. The channel conditions can be seen as mutually uncorrelated for each burst due to spectral and or temporal separation of those. Because of this time variant nature, a recurring acquisition of the impairment parameters is required for each burst. In this work, a blind joint estimation of several parameters in a flat fading environment for continuous phase modulation bursts is realized by the expectation maximization algorithm. The main contributions are first the formulation of the expectation and maximization steps to enable the joint computation of the maximum likelihood parameter estimates and second the analysis of the likelihood functions to obtain an optimized initialization for the algorithm. It is shown, that the joint estimator produces unbiased estimates and its performance in terms of the mean squared estimation error achieves the theoretical limits, i.e. the modified Cramér-Rao-Vector-Bound and slightly outperforms a state of the art pilot based estimator. Furthermore, the effective throughput is discussed and bit and frame error rates are compared to each other and to the perfectly synchronized estimator. Its computational complexity is analyzed and efficient computation steps and further approaches are outlined to decrease it.

An Interference Sensing Algorithm Based on Duration Units of Frequency Points for Adaptive Frequency-Hopping System

An Interference Sensing Algorithm Based on Duration Units of Frequency Points for Adaptive Frequency-Hopping System

Time-frequency analysis-based deep interference classification for frequency hopping system

It is known that interference classification plays an important role in protecting the authorized communication system and avoiding its performance degradation in the hostile environment. In this paper, the interference classification problem for the frequency hopping communication system is discussed. Considering the possibility of the presence of multiple interferences in the frequency hopping system, in order to fully extract effective features of the interferences from the received signals, the linear and bilinear transform-based composite time-frequency analysis method is adopted. Then, the time-frequency spectrograms obtained from the time-frequency analysis are constructed as matching pairs and input to the deep neural network for classification. In particular, the Siamese neural network is used as the classifier, where the paired spectrograms are input into the two sub-networks of the deep networks, and these two sub-networks extract the features of the paired spectrograms for interference-type classification. The simulation results confirm that the proposed algorithm can obtain higher classification accuracy than both traditional single time-frequency representation-based approach and the AlexNet transfer learning or convolutional neural network-based methods.

Optimal Quasi-Orthogonal FH Sequences With Adaptive Array Receiver for Massive Connectivity in Asynchronous Multi-Cluster Networks

This paper is concerned with the enabling of massive connectivity in a multi-cluster network. In order to tackle significant amount of interference imposed by inter- and intra-cluster users, we consider a frequency-hopping (FH) system where an improved quasi-orthogonal hopping pattern, called optimal strong no-hit-zone FH sequence (SNHZ-FHS) set, is adopted in each cluster. We propose a flexible construction of SNHZ-FHS sets and derive their Hamming correlation values at different access delays. Since the maximum number of supportable users under traditional FH networks is strictly limited by the number of frequency slots, we investigate the design of a novel class of adaptive array beam-forming (BF) receiver in which SNHZ-FHS patterns (i.e., SNHZ-FH/BF) are reused over asynchronous multi-cluster uplink channels. Extensive numerical comparisons show that our proposed SNHZ-FH/BF system provides an effective means for attaining higher user capacity as well as remarkable capability of interference suppression.

Microwave Spark Plug to Support Ignitions With High Compression Ratios

Upcoming gasoline engines should run with a larger number of fuels beginning from petrol over methanol up to gas by a wide range of compression ratios and a homogeneous charge. In this article, the microwave (MW) spark plug, based on a high-speed frequency hopping system, is introduced as a solution, which can support a nitrogen compression ratio up to 1:39 in a chamber and more. First, an overview of the high-speed frequency hopping MW ignition and operation system as well as the large number of applications are presented. Both gives an understanding of this new base technology for MW plasma generation. Focus of the theoretical part is the explanation of the internal construction of the spark plug, on the achievable of the high voltage generation as well as the high efficiency to hold the plasma. In detail, the development process starting with circuit simulations and ending with the numerical multiphysics field simulations is described. The concept is evaluated with a reference prototype covering the frequency range between 2.40 and 2.48 GHz and working over a large power range from 20 to 200 W. A larger number of different measurements starting by vector hot- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S_{11}$ </tex-math></inline-formula> measurements and ending by combined working scenarios out of hot temperature, high pressure and charge motion are winding up the article. The limits for the successful pressure tests were given by the pressure chamber. Pressures ranged from 1 to 39 bar and charge motion up to 25 m/s as well as temperatures from 30° to 125°.

Cognitive-Based High Robustness Frequency Hopping Strategy for UAV Swarms in Complex Electromagnetic Environment

Unmanned aerial vehicles (UAVs) confront various interference in the process of missions, and frequency hopping (FH) technology is one of the effective means of anti-interference for UAV. The FH system can avoid interference frequency points and possess certain anti-interference ability by making the carrier frequency continuously popping. However, the increasingly complex electromagnetic environment of UAV swarms requires more efficient anti-interference measure. To further improve the anti-interference ability of UAVs, this paper proposes a cognitive-based high robustness FH strategy. By adding a cognitive module to FH system, UAVs can avoid the interference frequency points adaptively and sensitively. The proposed system can identify typical suppressed interference and filter the interference frequency points. Cognitive FH system can avoid interference points completely with accurate detections and enhance the robustness for UAV swarms in complex electromagnetic environment compared to conventional FH system. Simulation results have shown that BER performance of proposed cognitive FH strategy is better than conventional FH strategy for typical suppressed interference.

Intelligent Anti-Jamming Decision Algorithm of Bivariate Frequency Hopping Pattern Based on DQN With PER and Pareto

To improve the anti-jamming performance of frequency hopping system in complex electromagnetic environment, a Deep Q-Network algorithm with priority experience replay (PER) based on Pareto samples (PPER-DQN) is proposed, which makes intelligent decision for bivariate FH pattern. The system model, state-action space and reward function are designed based on the main parameters of the FH pattern. The DQN is used to improve the flexibility of the FH pattern. Based on the definition of Pareto dominance, the PER based on the TD-error and immediate reward is proposed. To ensure the diversity of the training set, it is formed by Pareto sample set and several random samples. When selecting Pareto sample, the confidence coefficient is introduced to modify its priority. It guarantees the learning value of the training set and improves the learning efficiency of DQN. The simulation results show that the efficiency, convergence speed and stability of the algorithm are effectively improved. And the generated bivariate FH pattern has better performance than the conventional FH pattern.