Biblio

Currently, the pulse position modulation (PPM) schemes are suffering from bandwidth application where the line rate is double that of the initial data rate. Thus, the offset pulse position modulation (OPPM) has been suggested to rectify this concern. Several attempts to improve the OPPM can be found in the open literature. This study focuses on the utilization of Reed Solomon (RS) codes to enhance the forward error correction (FEC) bit error rate, which is not yet explored. The performance of errors of the uncoded OPPM was compared to the one used by RS coded OPPM using the number of photons per pulse, the transmission's efficacy, and bandwidth growth. The results demonstrate that employing FEC coding would increase the system's error performance especially when the RS is operating at its finest settings. Specifically, when operating with a capacity that is equivalent to or even more 0.7, the OPPM with RS code outperforms the uncoded OPPM where the OPPM with MLSD needs only 1.2×103 photons per pulse with an ideal coding rate of about 3/4.

The discussion about forward error correction (FEC) used for 800G unamplified link (800LR) is ongoing. Aiming at two potential options for FEC bit error ratio (BER) threshold, we propose two FEC schemes, respectively based on channel-polarized (CP) multilevel coding (MLC) and bit interleaved coded modulation (BICM), with the same inner FEC code. The field-programmable gate array (FPGA) verification results indicate that with the same FEC overhead (OH), proposed CP-MLC outperforms BICM scheme with less resource and power consumption.

We show that a new type of dielectric cavity featuring deep sub-wavelength light confinement allows a significant speedup of all-optical signal processing functionalities, without compromising the energy efficiency. The effect is due to enhanced diffusion dynamics in an unconventional geometry.

This paper presents a physically-secure wireless communication system utilizing orbital angular momentum (OAM) waves at 0.31THz. A trustworthy key distribution mechanism for symmetric key cryptography is proposed by exploiting random hopping among the orthogonal OAM-wave modes and phases. Keccak-f[400] based pseudorandom number generator provides randomness to phase distribution of OAM-wave modes for additional security. We assess the security vulnerabilities of using OAM modulation in a THz communication system under various physical-layer threat models as well as analyze the effectiveness of these threat models for varying attacker complexity levels under different conditions.

Acoustic communication is a key enabler for underwater Internet of Things networks between autonomous underwater platforms. Underwater Internet of Things networks face a harsh communications environment and limited energy resources which makes them susceptible to interference, whether intentional (i.e., jamming) or unintentional. Resilient, power efficient waveforms and modulation schemes are needed for underwater acoustic communications in order to avoid outages and excessive power drain. We explore the impact of modulation scheme on the resiliency of underwater acoustic communications in the presence of channel impairments, interference, and jamming. In particular, we consider BFSK and OFDM schemes for underwater acoustic communications and assess the utility of Polar coding for strengthening resiliency.

The expanding streaming culture of large amounts of data, as well as the requirement for faster and more reliable data transport systems, necessitates the development of innovative communication technologies such as Visible Light Communication (VLC). Nonetheless, incorporating VLC into next-generation networks is challenging due to technological restrictions such as air absorption, shadowing, and beam dispersion. One technique for addressing some of the challenges is to use the multiple input multiple output (MIMO) technique, which involves the simultaneous transmission of data from several sources, hence increasing data rate. In this work, the data transmission performance of the MIMO-VLC system is evaluated using a variety of factors such as distance from the source, data bit rate, and modulation method.

Many portable imaging devices use the operation of "trunc" (rounding towards zero) instead of rounding as the final quantizer for computing DCT coefficients during JPEG compression. We show that this has rather profound consequences for steganography and its detection. In particular, side-informed steganography needs to be redesigned due to the different nature of the rounding error. The steganographic algorithm J-UNIWARD becomes vulnerable to steganalysis with the JPEG rich model and needs to be adjusted for this source. Steganalysis detectors need to be retrained since a steganalyst unaware of the existence of the trunc quantizer will experience 100% false alarm.

Four-dimensional (4-D) antenna arrays formed by introducing time as the forth controlling variable are able to be used to regulate the radiation fields in space, time and frequency domains. Thus, 4-D antenna arrays are actually the excellent platform for achieving physical layer secure transmission. However, traditional direction modulation technique of 4-D antenna arrays always inevitably leads to higher sidelobe level of radiation pattern or less randomness. Regarding to the problem, this paper proposed a physical layer secure transmission technique based on 4-D antenna arrays, which combine the advantages of traditional phased arrays, and 4-D arrays for improving the physical layer security in wireless networks. This technique is able to reduce the radiated power at sidelobe region by optimizing the time sequences. Moreover, the signal distortion caused by time modulation can be compensated in the desired direction by pre-modulating transmitted signals.

Visible light communications (VLC) have been the focus of many recent investigations due to its potential for transmitting data at a higher bitrate than conventional communication systems. Alongside the advantages of being energy efficient through the use of LEDs (Light Emitting Diodes), it is imperative that these systems also take in consideration privacy and security measures available. This work highlights the technical aspects of a typical 16-QAM (Quadrature Amplitude Modulation) VLC system incorporating an enhanced privacy feature using an hyperchaotic map to scramble the symbols. The results obtained in this study showed a low dispersion symbol constellation while communicating at 100 Baud and with a 1 m link. Using the measured EVM (Error Vector Magnitude) of the constellation, the BER (Bit Error Rate) of this system was estimated to be bellow 10−12 which is lower than the threshold limit of 3.8.10−3 that corresponds to the 7% hard-decision forward error correction (HD- FEC) for optimal transmission, showing that this technique can be implemented with higher bitrates and with a higher modulation index.

In this paper, we investigated a self-oscillating ring system with variation of the delay time, which demonstrates the phenomenon of laminar chaos. The presence of laminar chaos is demonstrated for various laws of time delay variation - sinusoidal, sawtooth, and triangular. The behavior of coupled systems with laminar chaos and diffusive coupling is investigated. The presence of synchronous behavior is shown.

A physical layer security (PLS) technique called Gray Code Hopping (GCH) is presented offering simplistic implementation and no bit error rate (BER) performance degradation over the main channel. A synchronized transmitter and receiver "hop" to an alternative binary reflected Gray code (BRGC) mapping of bits to symbols between each consecutive modulation symbol. Monte Carlo simulations show improved BER performance over a similar technique from the literature. Simulations also confirm compatibility of GCH with either hard or soft decision decoding methods. Simplicity of GCH allows for ready implementation in adaptive 5th Generation New Radio (5G NR) modulation coding schemes.

Interleave division multiple access (IDMA) is a multiple-access scheme and it is expected to improve frequency efficiency. Meanwhile, the damage caused by cyberattacks is increasing yearly. To solve this problem, we propose a method of applying radio-wave encryption to IDMA based on chaos modulation to realize physical layer security and the channel coding effect. We show that the proposed scheme ensures physical layer security and obtains channel coding gain by numerical simulations.

In this paper, two methods are introduced for securing voice communication. The first technique applies multilevel chaos-based block cipher and the second technique applies non-autonomous chaotic modulation. In the first approach, the encryption method is implemented by joining Arnold cat map with the Lorenz system. This method depends on permuting and substituting voice samples. Applying two levels of a chaotic system, enhances the security of the encrypted signal. the permutation process of the voice samples is implemented by applying Arnold cat map, then use Lorenz chaotic flow to create masking key and consequently substitute the permuted samples. In the second method, an encryption method based on non-autonomous modulation is implemented, in the master system, and the voice injection process is applied into one variable of the Lorenz chaotic flow without modifying the state of controls parameter. Non-autonomous modulation is proved to be more suitable than other techniques for securing real-time applications; it also masters the problems of chaotic parameter modulation and chaotic masking. A comparative study of these methods is presented.

Underwater wireless optical communications are studied through single photon detection, photon states modulation and quantum key encryption. These studies will promote the development of optical communication applications in underwater vehicles and underwater sensor networks.

For the intra-pulse modulation classification of radar signal, traditional deep learning algorithms have poor recognition performance without numerous training samples. Meanwhile, the receiver may intercept few pulse radar signals in the real scenes of electronic reconnaissance. To solve this problem, a structure which is made up of signal pretreatment by Smooth Pseudo Wigner-Ville (SPWVD) analysis algorithm, convolution neural network (CNN) and relation network (RN) is proposed in this study. The experimental results show that its classification accuracy is 94.24% under 20 samples per class training and the signal-to-noise ratio (SNR) is -4dB. Moreover, it can classify the novel types without further updating the network.

Most of existing signal modulation recognition methods attempt to establish a machine learning mechanism by training with a large number of annotated samples, which is hardly applied to the real-world electronic reconnaissance scenario where only a few samples can be intercepted in advance. Few-Shot Learning (FSL) aims to learn from training classes with a lot of samples and transform the knowledge to support classes with only a few samples, thus realizing model generalization. In this paper, a novel FSL framework called Attention Relation Network (ARN) is proposed, which introduces channel and spatial attention respectively to learn a more effective feature representation of support samples. The experimental results show that the proposed method can achieve excellent performance for fine-grained signal modulation recognition even with only one support sample and is robust to low signal-to-noise-ratio conditions.

Radio Frequency Identification (RFID) technology has attracted much attention due to its variety of applications, e.g., inventory control and object tracking. Tag identification protocols are essential in such applications. However, in such protocols, significant time and power are consumed on inevitable simultaneous tag replies (collisions) because tags can't sense the media to organize their replies to the reader. In this paper, novel reader-tag interaction method is proposed in which low-complexity Digital Baseband Modulation Termination (DBMT) circuit is added to RFID tags to enhance collision resolution efficiency in conjunction with Streamlined Collision Resolution (SCR) scheme. The reader, in the proposed SCR, cuts off or reduces the power of its continuous wave signal for specific periods if corrupted data is detected. On the other hand, DBMT circuit at the tag measures the time of the reader signal cutoff, which in turn, allows the tag to interpret different cutoff periods into commands. SCR scheme is applied to ALOHA- and Tree-based protocols with varying numbers of tags to evaluate the performance under low and high collision probabilities. SCR provides a significant enhancement to both types of protocols with robust synchronization within collision slots. This novel reader-tag interaction method provides a new venue for revisiting tag identification and counting protocols.

The discovery of adversarial examples poses a serious risk to the deep neural networks (DNN). By adding a subtle perturbation that is imperceptible to the human eye, a well-behaved DNN model can be easily fooled and completely change the prediction categories of the input samples. However, research on adversarial attacks in the field of modulation recognition mainly focuses on increasing the prediction error of the classifier, while ignores the importance of decreasing the perceptual invisibility of attack. Aiming at the task of DNNbased modulation recognition, this study designs the Fitting Difference as a metric to measure the perturbed waveforms and proposes a new method: the Nesterov Adam Iterative Method to generate adversarial examples. We show that the proposed algorithm not only exerts excellent white-box attacks but also can initiate attacks on a black-box model. Moreover, our method decreases the waveform perceptual invisibility of attacks to a certain degree, thereby reducing the risk of an attack being detected.

Recent work has shown the impact of adversarial machine learning on deep neural networks (DNNs) developed for Radio Frequency Machine Learning (RFML) applications. While these attacks have been shown to be successful in disrupting the performance of an eavesdropper, they fail to fully support the primary goal of successful intended communication. To remedy this, a communications-aware attack framework was recently developed that allows for a more effective balance between the opposing goals of evasion and intended communication through the novel use of a DNN to intelligently create the adversarial communication signal. Given the near ubiquitous usage of for-ward error correction (FEC) coding in the majority of deployed systems to correct errors that arise, incorporating FEC in this framework is a natural extension of this prior work and will allow for improved performance in more adverse environments. This work therefore provides contributions to the framework through improved loss functions and design considerations to incorporate inherent knowledge of the usage of FEC codes within the transmitted signal. Performance analysis shows that FEC coding improves the communications aware adversarial attack even if no explicit knowledge of the coding scheme is assumed and allows for improved performance over the prior art in balancing the opposing goals of evasion and intended communications.

Visual reasoning between visual image and natural language description is a long-standing challenge in computer vision. While recent approaches offer a great promise by compositionality or relational computing, most of them are oppressed by the challenge of training with datasets containing only a limited number of images with ground-truth texts. Besides, it is extremely time-consuming and difficult to build a larger dataset by annotating millions of images with text descriptions that may very likely lead to a biased model. Inspired by the majority success of webly supervised learning, we utilize readily-available web images with its noisy annotations for learning a robust representation. Our key idea is to presume on web images and corresponding tags along with fully annotated datasets in learning with knowledge embedding. We present a two-stage approach for the task that can augment knowledge through an effective embedding model with weakly supervised web data. This approach learns not only knowledge-based embeddings derived from key-value memory networks to make joint and full use of textual and visual information but also exploits the knowledge to improve the performance with knowledge-based representation learning for applying other general reasoning tasks. Experimental results on two benchmarks show that the proposed approach significantly improves performance compared with the state-of-the-art methods and guarantees the robustness of our model against visual reasoning tasks and other reasoning tasks.

Visible light communication (VLC) is considered as an emerging system for wireless indoor multimedia communications. As any wireless communication system, its channels are open and reachable to both licensed and unlicensed users owing to the broadcast character of visible-light propagation in public areas or multiple-user scenarios. In this work, we consider the physical-layer security approaches for VLC to mitigate this limitation. The physical-layer security approaches can be divided into two categories: keyless security and key-based security approaches. In the last category, recently, the authors introduced physical-layer key-generation approaches for optical orthogonal frequency division multiplexing (OFDM) systems. In these approaches, the cyclic prefix (CP) samples are exploited for key generation. In this paper, we study the effect of the length of key space and order of modulation on the security level, BER performance, and key-disagreement-rate (KDR) of the introduced key-based security approaches. From the results, our approaches are more efficient in higher order of modulation as the KDR decreases with the increase of order of modulation.

Deep Learning (DL), in spite of its huge success in many new fields, is extremely vulnerable to adversarial attacks. We demonstrate how an attacker applies physical white-box and black-box adversarial attacks to Channel decoding systems based on DL. We show that these attacks can affect the systems and decrease performance. We uncover that these attacks are more effective than conventional jamming attacks. Additionally, we show that classical decoding schemes are more robust than the deep learning channel decoding systems in the presence of both adversarial and jamming attacks.

To build the fifth generation (5G) mobile network, the sharing structure in the 5G network adopted in industries has gained great research interesting. However, in this structure data are shared among diversity networks, which introduces the threaten of network security, such as covert timing channels. To eliminate the covert timing channel, we propose to inject noise into the covert timing channel. By analyzing the modulation method of covert timing channels, we design the jamming strategy on the covert channel. According to the strategy, the interference algorithm of the covert timing channel is designed. Since the interference algorithm depends heavily on the memory, we construct a distributing jammer. Experiments results show that these covert time channel can be blocked under the distributing jammer.

In this paper, we outline a novel, forward error correction-based information hiding technique for adaptive rate wireless communication systems. Specifically, we propose leveraging the functionality of wireless local area network modulation and coding schemes (MCS) and link adaptation mechanisms to significantly increase covert channel throughput. After describing our generalized information hiding model, we detail implementation of this technique within the IEEE 802.11ad, directional multi-Gigabit standard. Simulation results demonstrate the potential of the proposed techniques to develop reliable, high-throughput covert channels under multiple MCS rates and embedding techniques. Covert channel performance is evaluated in terms of the observed packet error ratio of the underlying communication system as well as the bit error ratio of the hidden data.

This paper mainly investigates the physical layer security for visible light communication (VLC) based on spatial modulation (SM). The indoor VLC system includes multiple transmitters, a legitimate receiver and an eavesdropper. In the system, we consider two constraints of the input signal: non-negative and dimmable average optical intensity constraints. According to the principle of information theory and the spatial modulation scheme of uniform selection (US), the upper and the lower bounds on the secrecy rate for SM based VLC are derived, respectively. Numerical results show that the performance gap between the upper and lower bounds of the secrecy rate is small and relatively close, which indicates that the derived secrecy rate bounds can be used to evaluate the system performance. Moreover, when the number of transmitters is set to be one, the spatial modulation disappears, and the secrecy rate bounds in this paper are consistent with the existing results. To further improve the secrecy performance, a channel adaptive selection (CAS) scheme is proposed for selecting the active transmitter. Numerical result indicates that the CAS scheme has better performance than the US scheme.