The current orthogonal cooperative system (OCS) achieves diversity through the use of relays and the consumption of an additional time slot (TS). To guarantee the orthogonality of the received signal and avoid the mutual interference at the destination, the source has to be mute in the second TS. Consequently, the spectral efficiency (SE) is halved. In this paper, linear constellation precoded orthogonal frequency division multiplexing with index modulation (LCP-OFDM-IM) based OCS is proposed, where the source activates the complementary subcarriers to convey the symbols over two TSs. Hence the source can consecutively transmit information to the destination without the mutual interference. Compared with the current OFDM based OCS, the LCP-OFDM-IM based OCS can achieve a higher SE, since the subcarrier activation patterns (SAPs) can be exploited to convey additional information. Furthermore, the optimal precoder, in the sense of maximizing the minimum Euclidean distance of the symbols conveyed on each subcarrier over two TSs, is provided. Simulation results show the superiority of the LCP-OFDM-IM based OCS over the current OFDM based OCS.

Virtual network embedding has been intensively studied for a decade. The time complexity of most conventional methods has been reduced to the cube of the number of links. Since customers are likely to request a dense virtual network that connects every node pair directly (|E|=O(|V|2)) based on a traffic matrix, the time complexity is actually O(|E|3=|V|6). If we were allowed to reduce this dense network to a sparse one before embedding, the time complexity could be decreased to O(|V|3); the time saving would be of the order of a million times for |V|=100. The network reduction, however, combines several virtual links into a broader link, which makes the embedding cost (solution quality) much worse. This paper analytically and empirically investigates the trade-off between the embedding time and cost for the virtual network reduction. We define two simple reduction operations and analyze them with several interesting theorems. The analysis indicates that an exponential drop in embedding time can be achieved with a linear increase in embedding cost. A rigorous numerical evaluation justifies the desirability of the trade-off.

Mobile edge computing (MEC) is a new computing paradigm, which provides computing support for resource-constrained user equipments (UEs). In this letter, we design an effective incentive framework to encourage MEC operators to provide computing service for UEs. The problem of jointly allocating communication and computing resources to maximize the revenue of MEC operators is studied. Based on auction theory, we design a multi-round iterative auction (MRIA) algorithm to solve the problem. Extensive simulations have been conducted to evaluate the performance of the proposed algorithm and it is shown that the proposed algorithm can significantly improve the overall revenue of MEC operators.

To increase the number of wireless devices such as mobile or IoT terminals, cryptosystems are essential for secure communications. In this regard, random number generation is crucial because the appropriate function of cryptosystems relies on it to work properly. This paper proposes a true random number generator (TRNG) method capable of working in wireless communication systems. By embedding a TRNG in such systems, no additional analog circuits are required and working conditions can be limited as long as wireless communication systems are functioning properly, making TRNG method cost-effective. We also present some theoretical background and considerations. We next conduct experimental verification, which strongly supports the viability of the proposed method.

Angular Momentum (AM) has been considered as a new dimension of wireless transmissions as well as the intrinsic property of Electro-Magnetic (EM) waves. So far, AM is utilized as a discrete mode not only in the quantum states, but also in the statistical beam forming. Traditionally, the continuous value of AM is ignored and only the quantized mode number is identified. However, the recent discovery on electrons in spiral motion producing twisted radiation with AM, including Spin Angular Momentum (SAM) and Orbital Angular Momentum (OAM), proves that the continuous value of AM is available in the statistical EM wave beam. This is also revealed by the so-called fractional OAM, which is reported in optical OAM beams. Then, as the new dimension with continuous real number field, AM should turn out to be a certain spectrum, similar to the frequency spectrum usually in the wireless signal processing. In this letter, we mathematically define the AM spectrum and show the applications in the information theory analysis, which is expected to be an efficient tool for the future wireless communications with AM.

Due to the superior performance, deep learning has been widely applied to various applications, including image classification, bioinformatics, and cybersecurity. Nevertheless, the research investigations on deep learning in the adversarial environment are still on their preliminary stage. The emerging adversarial learning methods, e.g., generative adversarial networks, have introduced two vital questions: to what degree the security of deep learning with the presence of adversarial examples is; how to evaluate the performance of deep learning models in adversarial environment, thus, to raise security advice such that the selected application system based on deep learning is resistant to adversarial examples. To see the answers, we leverage image classification as an example application scenario to propose a framework of Evaluating Deep Learning for Image Classification (EDLIC) to conduct comprehensively quantitative analysis. Moreover, we introduce a set of evaluating metrics to measure the performance of different attacking and defensive techniques. After that, we conduct extensive experiments towards the performance of deep learning for image classification under different adversarial environments to validate the scalability of EDLIC. Finally, we give some advice about the selection of deep learning models for image classification based on these comparative results.

Music classification has been inspired by the remarkable success of deep learning. To enhance efficiency and ensure high performance at the same time, a hybrid architecture that combines deep learning and Broad Learning (BL) is proposed for music classification tasks. At the feature extraction stage, the Random CNN (RCNN) is adopted to analyze the Mel-spectrogram of the input music sound. Compared with conventional CNN, RCNN has more flexible structure to adapt to the variance contained in different types of music. At the prediction stage, the BL technique is introduced to enhance the prediction accuracy and reduce the training time as well. Experimental results on three benchmark datasets (GTZAN, Ballroom, and Emotion) demonstrate that: i) The proposed scheme achieves higher classification accuracy than the deep learning based one, which combines CNN and LSTM, on all three benchmark datasets. ii) Both RCNN and BL contribute to the performance improvement of the proposed scheme. iii) The introduction of BL also helps to enhance the prediction efficiency of the proposed scheme.

The decentralized energy network is one of the promising solutions as a next-generation power grid. In this system, each house has a photovoltaic (PV) panel as a renewable energy source and a battery which is an essential component to balance between generation and demand. The common objective of the battery management on such systems is to minimize only the purchased energy from a power company, but battery degradation caused by charge/discharge cycles is also a serious problem. This paper proposes a State-of-Health (SOH) aware system-level battery management methodology for the decentralized energy network. The power distribution problem is often solved with mixed integer programming (MIP), and the proposed MIP formulation takes into account the SOH model. In order to minimize the purchased energy and reduce the battery degradation simultaneously, the optimization problem is divided into two stages: 1) the purchased energy minimization, and 2) the battery aging factor reducing, and the trade-off exploration between the purchased energy and the battery degradation is available. Experimental results show that the proposed method achieves the better trade-off and reduces the battery aging cost by 14% over the baseline method while keeping the purchased energy minimum.

Heterogeneous networks (HetNets) technology is expected to be applied in next generation cellular networks to boost system capacity. However, applying HetNets introduces a significant amount of interference among different tiers within the same cell. In this paper, we propose a weighted rank constrained rank minimization (WRCRM) based interference alignment (IA) approach for three-tier HetNets. The concept of RCRM is applied in a different way to deal with the basic characteristic of different tiers: their different interference tolerance. In the proposed WRCRM approach, interference components at different tiers are weighted with different weighting factors (WFs) to reflect their vulnerability to interference. First, we derive an inner and a loose outer bound on the achievable degrees of freedom (DoF) for the three-tier system that is modeled as a three-user mutually interfering broadcast channel (MIBC). Then, the derived bounds along with the well-known IA feasibility conditions are used to show the effectiveness of the proposed WRCRM approach. Results show that there exist WF values that maximize the achievable interference-free dimensions. Moreover, adjusting the required number of DoF according to the derived bounds improves the performance of the WRCRM approach.

The equivalent transmission-path model is a propagation-oriented channel model for predicting the bit error rate due to intersymbol interference in single-input single-output systems. We extend this model to develop a new calculation scheme for maximal-ratio combining diversity reception in single-input multiple-output configurations. A key part of the study is to derive a general formula expressing the joint probability density function of the amplitude ratio and phase difference of the two-path model. In this derivation, we mainly take a theoretical approach with the aid of Monte Carlo simulation. Then, very high-accuracy estimation of the average bit error rate due to intersymbol interference (ISI) for CQPSK calculated based on the model is confirmed by computer simulation. Finally, we propose a very simple calculation formula for the prediction of the BER due to ISI that is commonly applicable to various modulation/demodulation schemes, such as CQPSK, DQPSK, 16QAM, and CBPSK in maximal-ratio combining diversity reception.

The modern radar signals are in a wide frequency space. The receiving bandwidth of the radar reconnaissance receiver should be wide enough to intercept the modern radar signals. The Nyquist folding receiver (NYFR) is a novel wideband receiving architecture and it has a high intercept probability. Chirp signals are widely used in modern radar system. Because of the wideband receiving ability, the NYFR will receive the concurrent multiple chirp signals. In this letter, we propose a novel parameter estimation algorithm for the multiple chirp signals intercepted by single channel NYFR. Compared with the composite NYFR, the proposed method can save receiving resources. In addition, the proposed approach can estimate the parameters of the chirp signals even the NYFR outputs are under frequency aliasing circumstance. Simulation results show the efficacy of the proposed method.

Here, we present a novel spectroscopic imaging method based on the boundary-extraction scheme for wide-beam terahertz (THz) three-dimensional imaging. Optical-lens-focusing systems for THz subsurface imaging generally require the depth of the object from the surface to be input beforehand to achieve the desired azimuth resolution. This limitation can be alleviated by incorporating a wide-beam THz transmitter into the synthetic aperture to automatically change the focusing depth in the post-signal processing. The range point migration (RPM) method has been demonstrated to have significant advantages in terms of imaging accuracy over the synthetic-aperture method. Moreover, in the RPM scheme, spectroscopic information can be easily associated with each scattering center. Thus, we propose an RPM-based terahertz spectroscopic imaging method. The finite-difference time-domain-based numerical analysis shows that the proposed algorithm provides accurate target boundary imaging associated with each frequency-dependent characteristic.

More and more attacks are found due to the insecure channel between different network domains in legacy mobile network. In this letter, we discover an attack exploiting SUCI to track a subscriber in 5G network, which is directly caused by the insecure air channel. To cover this issue, a secure authentication scheme is proposed utilizing the existing PKI mechanism. Not only dose our protocol ensure the authentication signalling security in the channel between UE and SN, but also SN and HN. Further, formal methods are adopted to prove the security of the proposed protocol.

We propose a non-photorealistic rendering method for generating edge-preserving bubble images from gray-scale photographic images. Bubble images are non-photorealistic images embedded in many bubbles, and edge-preserving bubble images are bubble images where edges in photographic images are preserved. The proposed method is executed by an iterative processing using absolute difference in window. The proposed method has features that processing is simple and fast. To validate the effectiveness of the proposed method, experiments using various photographic images are conducted. Results show that the proposed method can generate edge-preserving bubble images by preserving the edges of photographic images and the processing speed is high.

This paper discusses the parallelization of boost and buck converters. Passivity-based control is applied to each converter to achieve the asymptotic stability of the system. The ripple characteristics, error characteristics, and time constants of the parallelized converters are discussed with considering the dependency on the feedback gains. The numerical results are confirmed to coincide with the results in the experiment for certain feedback gains. The stability of the system is also discussed in simulation and experiment. The results will be a step to achieve the design of parallel converters.

In this letter, we adopt two multi-carrier relay selections, i.e., bulk and per-subcarrier (PS), to the multi-hop decode-and-forward relaying orthogonal frequency-division multiplexing with index modulation (OFDM-IM) system. Particularly, in the form of average outage probability (AOP), the influence of joint selection and non-joint selection acting on the last two hops on the system is analyzed. The closed-form expressions of AOPs and the asymptotic AOPs expressions at high signal-to-noise ratio are given and verified by numerical simulations. The results show that both bulk and PS can achieve full diversity order and that PS can provide additional power gain compared to bulk when JS is used. The theoretical analyses in this letter provide an insight into the combination of OFDM-IM and cooperative communication.

This paper proposes a defragmentation scheme using reroutable backup paths in toggled-based quasi 1+1 path protected elastic optical networks (EONs) to improve the efficiency of defragmentation and suppress the fragmentation effect. The proposed scheme can reallocate spectrum slots of backup paths and reroute of backup paths. The path exchange function of the proposed scheme makes the primary paths become the backup state while the backup paths become the primary. This allows utilization of the advantages of defragmentation in both primary and backup paths. We formulate a static spectrum reallocation problem with rerouting (SSRR) in the toggled-based quasi 1+1 path protected EON as an integer linear programming (ILP) problem. The decision version of SSRR is proven to be an NP-complete problem. A heuristic algorithm is introduced to solve the problem for large networks networks where the ILP problem is not tractable. For a dynamic traffic scenario, an approach that suppresses the fragmentation considering rerouting and path exchanging operations is presented. We evaluate the performances of the proposed scheme by comparing it to the conventional scheme in terms of dependencies on node degree, processing time of network operations and interval time between scheduled defragmentations. The numerical results obtained from the performance evaluation indicate that the proposed scheme increases the traffic admissibility compared to the conventional scheme.

Distributing codes to specific target sensors in order to fix bugs and/or install a new application is an important management task in WSNs (Wireless Sensor Networks). For the energy efficient dissemination of such codes to specific target sensors, it is required to select the minimum required number of forwarders with the fewest control messages. In this paper, we propose a novel RPL (Routing Protocol for Low-power and lossy networks)-based tree construction scheme for target-specific code dissemination, which is called R-TCS. The main idea of R-TCS is that by leveraging the data collection tree created by a standard routing protocol RPL, it is possible to construct the code dissemination tree with the minimum numbers of non-target sensors and control messages. Since by creating a data collection tree each sensor exchanges RPL messages with the root of the tree, every sensor knows which sensors compose its upwards route, i.e. the route towards the root, and downwards route, i.e. the route towards the leaves. Because of these properties, a target sensor can select the upward route that contains the minimum number of non-target sensors. In addition, a sensor whose downward routes do not contain a target sensor is not required to transmit redundant control messages which are related to the code dissemination operation. In this way, R-TCS can reduce the energy consumption which typically happens in other target-specific code dissemination schemes by the transmission of control messages. In fact, various performance evaluation results obtained by means of computer simulations show that R-TCS reduces by at least 50% energy consumption as compared to the other previous known target-specific code dissemination scheme under the condition where ratio of target sensors is 10% of all sensors.

When considering the deployment of a radio communications network, the study of multipath interference and its impact on the quality of signal reception is of the outmost importance in order to meet the necessary performance requirements. This work considers specifically the case of the lunar surface as the mission scenario for a community of autonomous mobile exploration robots, which communicate through a radiofrequency network to accomplish their mission. In this application, the low height of the mobile robots makes the influence of multipath interference effects on the performance of the radio communication channel relevant. However, no specific information about lunar soil reflection coefficients characteristics is available for radiofrequency communication bands. This work reviews the literature on the electrical parameter of Lunar soil. From this base, the reflection coefficients are estimated for the assumed radio profile in different communications frequency bands. Finally, the results obtained are discussed.

In this article, we propose a method to identify the link layer home network topology, motivated by applications to cost reduction of support centers. If the topology of home networks can be identified automatically and efficiently, it is easier for operators of support centers to identify fault points. We use MAC address forwarding tables (AFTs) which can be collected from network devices. There are a couple of existing methods for identifying a network topology using AFTs, but they are insufficient for our purpose; they are not applicable to some specific network topologies that are typical in home networks. The advantage of our method is that it can handle such topologies. We also implemented these three methods and compared their running times. The result showed that, despite its wide applicability, our method is the fastest among the three.