In this paper, a Doppler-tolerant waveform is proposed as a transmitting signal for joint radar and communication systems. In the proposed waveform, communication signals are multiplexed at the side band of a linear frequency modulated (LFM) pulse, based on the orthogonal frequency division multiplexing (OFDM) scheme. Therefore, the proposed waveform can maintain Doppler-tolerance in radar use as well as the original LFM pulse can. In addition, it is also capable of flexibly increasing the transmission rate in communication use by assigning more communication signals at the side-band subcarriers. Numerical simulations were carried out to comprehensively examine the proposed waveform in terms of the probability of detection in radar use and the symbol error rate in communication use. In conclusion, the proposed waveform is suited to the transmitting signal for joint radar and communication systems, especially with maintaining Doppler-tolerance to detect fast-moving targets.

The signal levels of Ku-band BS broadcast radio wave and JCSAT-5A beacon radio wave have been simultaneously measured at Osaka Electro-Communication University (OECU, Neyagawa, Osaka), NTT Yokosuka R&D Center (Yokosuka, Kanagawa), and satellite base station (Matsuyama, Ehime), respectively, from April 2022 to March 2023. The yearly cumulative distribution of rain attenuation at Yokosuka station shows the same increasing tendency compared to the ITU-R recommendations, as at Neyagawa station, while the increasing tendency is not clear at Matsuyama station. Also, site diversity techniques are examined among these three stations with relatively long distances of about 300-700 km. The site diversity effects among the three stations are almost consistent with the ITU-R recommendations between eastern and western areas of Japan. The 99.9% annual available time (0.1% unavailable time) percentage of satellite operations is shown to be guaranteed by the rain margins of 3-5 dB for the yearly rain attenuation statistics at the three stations. The monthly rain attenuation statistics, however, indicate that the rain margins of 6-10 dB are required to maintain the same 99.9% available time percentage primarily around summer time. The increase in rain margins is successfully suppressed under 3 dB using the site diversity operations. This increase in rain margins is well explained by the worst month statistics of the ITU-R recommendations.

Federated Learning (FL) facilitates deep learning model training across distributed networks while ensuring data privacy. When deployed on edge devices, network pruning becomes essential due to the constraints of computational resources. However, traditional FL pruning methods face bias issues arising from the varied distribution of local data, which poses a significant challenge. To address this, we propose DDPruneFL, an innovative FL pruning framework that utilizes Discriminative Data (DD). Specifically, we utilize minimally pre-trained local models, allowing each client to extract semantic concepts as DD, which then inform an iterative pruning process. As a result, DDPruneFL significantly outperforms existing methods on four benchmark datasets, adeptly handling both IID and non-IID distributions and Client Selection scenarios. This model achieves state-of-the-art (SOTA) performance in this field. Moreover, our studies comprehensively validate the effectiveness of DD. Furthermore, a detailed computational complexity analysis focused on Floating-point Operations (FLOPs) is also conducted. The FLOPs analysis reveals that DDPruneFL significantly improves performance during inference while only marginally increasing training costs. Additionally, it exhibits a cost advantage in inference when compared to other pruning FL methods of the same type, further emphasizing its cost-effectiveness and practicality.

The effects of site diversity techniques on Ku-band rain attenuation are investigated using two kinds of simultaneous BS (Broadcasting Satellite) signal observations: one was conducted among Osaka Electro-Communication University (OECU) in Neyagawa, Kyoto University in Uji, and Shigaraki MU Observatory in Koka for the past ten years, and the other was conducted among the headquarter of OECU in Neyagawa and their other premises in Shijonawate and Moriguchi for the past seven years, respectively. The site diversity effects among these sites with horizontal separations of 3-50 km are found to be largely affected by the passage direction of rain areas characterized by each rain type, such as warm, cold, and stationary fronts or typhoon and shower. The performance of the site diversity primarily depends on the effective distance between the sites projected to the rain area motions. The unavailable time percentages are theoretically shown to be reduced down to about 61-73% of the ITU-R predictions by choosing a pair of the sites aligned closest to the rain area motion in the distance of 3-50 km. Then, we propose three kinds of novel site diversity methods that choose the pair of sites based on such as rain type, rain front motion, or rain area motion at each rainfall event, respectively. As a result, the first method, which statistically accumulates the average passage directions of each rain type from long-term observations, is even useful for practical operations of the site diversity, because unavailable time percentages are reduced down to about 75-85% compared with the theoretical limit of about 61-73%. Also, the third method based on the rain area motion directly obtained from the three-site observations yields the reduction in unavailable time percentages close to this theoretical limit.

To shorten the distance between base stations (BSs) and user terminals, next-generation mobile communications (6G) plans to install large numbers of remote antenna units (RAUs) on traffic signals and street lights and connect these RAUs to base band units (BBUs) on buildings using terahertz (THz) band fronthaul radio lines capable of data rates that exceed 100 Gbit/s. However, when THz band fronthaul wireless circuits are densely deployed in urban areas, the challenge is to maintain line-of-sight (LOS) between RAUs and BBUs and prevent interference between fronthaul wireless links. In this study, the three-dimensional (3D) radiation pattern of a 300-GHz-band high-gain antenna was measured using the near-field-to-far-field (NF-FF) conversion method, and the accuracy was compared with the far-field measurement results. Moreover, an algorithm for automatically deploying a 300-GHz-band wireless fronthaul link is proposed, which can be used to position BBUs in locations where one BBU can be connected to as many RAUs as possible. Propagation simulations for fronthaul wireless links placed by the automatic deployment algorithm, using the measured 3D radiation patterns from high-gain antennas, show no interference between the fronthaul wireless links.

In 2004, Ryoh Fuji-Hara et al. (IEEE Trans. Inf. Theory. 50(10):2408-2420, 2004) proposed an open problem of finding a maximum multiplicative subgroup G in ℤn satisfying two conditions: (1) the sum of any two distinct elements in G is nonzero; (2) any difference from G is still a unit in ℤn. The subgroups satisfying Condition (2) is called difference unit group. Difference unit group is related to difference packing, zero-difference balanced function and partitioned difference family, and thus have many applications in coding and communication. Suppose the canonical factorization of n is ∏ki=1 peii. In this letter, we mainly answer the open problem with the result that the maximum cardinality of such a subgroup G is $\frac{d}{2^m}$, where d = gcd(p1 － 1, p2 － 1, ・・・, pk － 1) and m = ν2(d). Also an explicit construction of such a subgroup is introduced.

Characteristics of rain attenuation statistics for the Ku-band satellite signals are investigated among the three earth stations at Osaka Electro-Communication University (OECU, Neyagawa, Osaka), NTT Yokosuka R&D Center (Yokosuka, Kanagawa), and satellite base station (Matsuyama, Ehime), respectively, from April 2022 to March 2023. The time difference of the attenuation occurrence among these stations is well explained by the motion of rain fronts and extratropical cyclones obtained from the weather charts. Rain attenuation characteristics such as duration time are shown to be largely affected by the speed of the rain area motion around each station. The scale of rain cells inferred from duration time and rain area speed is found to be increased up to around 10 km for the 5 dB attenuation according to the rainfall rate at each rainfall event. The time delayed diversity effects are also examined using the attenuation data observed at 1 min interval. The results are converted to the site diversity effects with the distance up to about 10 km by the rain area motion around each station. A novel method is thus proposed to estimate the site diversity effects from the 1 min attenuation data observed at only one station during at least one year. The joint time percentages agree fairly well with the ITU-R recommendations up to about 10 km distance at the original time percentages of more than 0.05%.

The development of optical fiber transmission technologies has led to the emergence of various types of optical fibers have been introduced. In addition, the increase in the transmission capacity of optical fiber communications and the emergence of new applications have gained significant attention in high-power transmission technologies. Particularly, for beyond 5G/6G networks that are based on radio-over-fiber, which transmits wireless radio frequency signals along fiber links, power-over-fiber and high-power signal transmissions are important for the availability and simplification of remote antenna units in mobile communications to improve the scalability. This paper introduces various types of optical fibers and describes representative high-power transmission technologies that use specialized optical fibers.

Intelligent reflecting surface (IRS) is an effective technology to improve the energy and spectral efficiency of wireless powered communication network (WPCN). Under user cooperation, we propose an IRS-assisted WPCN system where the wireless devices (WDs) collect wireless energy in the downlink (DL) and then share data. The adjacent single-antenna WDs cooperate to form a virtual antenna array so that their information can be simultaneously transmitted to the multi-antenna common hybrid access point (HAP) through the uplink (UL) using multiple-input multiple-output (MIMO) technology. By jointly optimizing the passive beamforming at the IRS, the active beamforming in the DL and the UL, the energy consumed by data sharing, and the time allocation of each phase, we formulate an UL throughput maximization problem. However, this optimization problem is non-convex since the optimization variables are highly coupled. In this study, we apply the alternating optimization (AO) technology to decouple the optimization variables and propose an efficient algorithm to avoid the difficulty of directly solving the problem. Numerical results indicate that the joint optimization method significantly improves the UL throughput performance in multi-user WPCN compared with various baseline methods.

This paper proposes an anomaly-detection method using the Fast xFlow Proxy, which enables fine-grained measurement of communication traffic. When a fault occurs in services or networks, communication traffic changes from its normal behavior. Therefore, anomalies can be detected by analyzing their autocorrelations. However, in large-scale carrier networks, packets are generally encapsulated and observed as aggregate values, making it difficult to detect minute changes in individual communication flows. Therefore, we developed the Fast xFlow Proxy, which analyzes encapsulated packets in real time and enables flows to be measured at an arbitrary granularity. In this paper, we propose an algorithm that utilizes the Fast xFlow Proxy to detect not only the anomaly occurrence but also its cause, that is, the location of the fault at the end-to-end. The idea is not only to analyze the autocorrelation of a specific flow but also to apply spatial analysis to estimate the fault location by comparing the behavior of multiple flows. Through extensive simulations, we demonstrate that base station, network, and service faults can be detected without any false negative detections.

With the emphasis on personal information privacy protection in wireless communications, the new dimension low-interception covert transmission technology represented by the vortex wave with Orbital Angular Momentum (OAM) has received attention from both academia and industry. However, the current OAM low-interception transmission techniques all assume that the eavesdropper can only receive plane wave signals, which is a very ideal situation. Once the eavesdropper is configured with an OAM sensor, the so-called mode covert channel will be completely exposed. To solve this problem, this paper proposes a vortex microwave photon low-interception transmission method. The proposed method utilizes the differential operation between plane and vortex microwave photons signals to construct the covert differential channel, which can hide the user data in the mode domain. Compared with the traditional spread spectrum transmission, our proposed covert differential channel schemes need less transmitted power to achieve reliable transmission, which means less possibility of being intercepted by the eavesdropper.

To fully exploit the attribute information in graphs and dynamically fuse the features from different modalities, this letter proposes the Attributed Graph Clustering Network with Adaptive Feature Fusion (AGC-AFF) for graph clustering, where an Attribute Reconstruction Graph Autoencoder (ARGAE) with masking operation learns to reconstruct the node attributes and adjacency matrix simultaneously, and an Adaptive Feature Fusion (AFF) mechanism dynamically fuses the features from different modules based on node attention. Extensive experiments on various benchmark datasets demonstrate the effectiveness of the proposed method.

An unmanned aerial vehicle (UAV) can be used for wireless communication and localization, among many other things. When terrestrial networks are either damaged or non-existent, and the area is GPS-denied, the UAV can be quickly deployed to provide communication and localization services to ground terminals in a specific target area. In this study, we propose an UAV operation model for unified communication and localization using reinforcement learning (UCL-RL) in a suburban environment which has no cellular communication and GPS connectivity. First, the UAV flies to the target area, moves in a circular fashion with a constant turning radius and sends navigation signals from different positions to the ground terminals. This provides a dynamic environment that includes the turning radius, the navigation signal transmission points, and the height of the unmanned aerial vehicle as well as the location of the ground terminals. The proposed model applies a reinforcement learning algorithm where the UAV continuously interacts with the environment and learns the optimal height that provides the best communication and localization services to the ground terminals. To evaluate the terminal position accuracy, position dilution of precision (PDOP) is measured, whereas the maximum allowable path loss (MAPL) is measured to evaluate the communication service. The simulation result shows that the proposed model improves the localization of the ground terminals while guaranteeing the communication service.

In this paper, we delve into wireless communications in the 300 GHz band, focusing in particular on the continuous bandwidth of 44 GHz from 252 GHz to 296 GHz, positioning it as a pivotal element in the trajectory toward 6G communications. While terahertz communications have traditionally been praised for the high speeds they can achieve using their wide bandwidth, focusing the beam has also shown the potential to achieve high energy efficiency and support numerous simultaneous connectivity. To this end, new performance metrics, EIRPλ and EINFλ, are introduced as important benchmarks for transmitter and receiver performance, and their consistency is discussed. We then show that, assuming conventional bandwidth and communication capacity, the communication distance is independent of carrier frequency. Located between radio waves and light in the electromagnetic spectrum, terahertz waves promise to usher in a new era of wireless communications characterized not only by high-speed communication, but also by convenience and efficiency. Improvements in antenna gain, beam focusing, and precise beam steering are essential to its realization. As these technologies advance, the paradigm of wireless communications is expected to be transformed. The synergistic effects of antenna gain enhancement, beam focusing, and steering will not only push high-speed communications to unprecedented levels, but also lay the foundation for a wireless communications landscape defined by unparalleled convenience and efficiency. This paper will discuss a future in which terahertz communications will reshape the contours of wireless communications as the realization of such technological breakthroughs draws near.

A novel temporal convolution network-gated recurrent unit (NTCN-GRU) algorithm is proposed for the greatest of constant false alarm rate (GO-CFAR) frequency hopping (FH) prediction, integrating GRU and Bayesian optimization (BO). GRU efficiently captures the semantic associations among long FH sequences, and mitigates the phenomenon of gradient vanishing or explosion. BO improves extracting data features by optimizing hyperparameters besides. Simulations demonstrate that the proposed algorithm effectively reduces the loss in the training process, greatly improves the FH prediction effect, and outperforms the existing FH sequence prediction model. The model runtime is also reduced by three-quarters compared with others FH sequence prediction models.

Smart cities aim to improve the quality of life of citizens and efficiency of city operations through utilization of 5G communication technology. Based on various technologies such as IoT, cloud computing, artificial intelligence, and big data, they provide smart services in terms of urban planning, development, and management for solving problems such as fine dust, traffic congestion and safety, energy efficiency, water shortage, and an aging population. However, as smart city has an open network structure, an adversary can easily try to gain illegal access and perform denial of service and sniffing attacks that can threaten the safety and privacy of citizens. In smart cities, the global mobility network (GLOMONET) supports mobile services between heterogeneous networks of mobile devices such as autonomous vehicles and drones. Recently, Chen et al. proposed a user authentication scheme for GLOMONET in smart cities. Nevertheless, we found some weaknesses in the scheme proposed by them. In this study, we propose a secure lightweight authentication for roaming services in a smart city, called SLARS, to enhance security. We proved that SLARS is more secure and efficient than the related authentication scheme for GLOMONET through security and performance analysis. Our analysis results show that SLARS satisfies all security requirements in GLOMONET and saves 72.7% of computation time compared to that of Chen et al.’s scheme.

Power line communication (PLC) provides a flexible-access, wide-distribution, and low-cost communication solution for distribution network services. However, the PLC self-organizing networking in distribution network faces several challenges such as diversified data transmission requirements guarantee, the contradiction between long-term constraints and short-term optimization, and the uncertainty of global information. To address these challenges, we propose a backpressure learning-based data transmission reliability-aware self-organizing networking algorithm to minimize the weighted sum of node data backlogs under the long-term transmission reliability constraint. Specifically, the minimization problem is transformed by the Lyapunov optimization and backpressure algorithm. Finally, we propose a backpressure and data transmission reliability-aware state-action-reward-state-action (SARSA)-based self-organizing networking strategy to realize the PLC networking optimization. Simulation results demonstrate that the proposed algorithm has superior performances of data backlogs and transmission reliability.

The concept of dual function radar-communication (DFRC) provides solution to the problem of spectrum scarcity. This paper examines a multiple-input multiple-output (MIMO) DFRC system with the assistance of a reconfigurable intelligent surface (RIS). The system is capable of sensing multiple spatial directions while serving multiple users via orthogonal frequency division multiplexing (OFDM). The objective of this study is to design the radiated waveforms and receive filters utilized by both the radar and users. The mutual information (MI) is used as an objective function, on average transmit power, for multiple targets while adhering to constraints on power leakage in specific directions and maintaining each user’s error rate. To address this problem, we propose an optimal solution based on a computational genetic algorithm (GA) using bisection method. The performance of the solution is demonstrated by numerical examples and it is shown that, our proposed algorithm can achieve optimum MI and the use of RIS with the MIMO DFRC system improving the system performance.

Boolean functions play an important role in symmetric ciphers. One of important open problems on Boolean functions is determining the maximum possible resiliency order of n-variable Boolean functions with optimal algebraic immunity. In this letter, we search Boolean functions in the rotation symmetric class, and determine the maximum possible resiliency order of 9-variable Boolean functions with optimal algebraic immunity. Moreover, the maximum possible nonlinearity of 9-variable rotation symmetric Boolean functions with optimal algebraic immunity-resiliency trade-off is determined to be 224.

Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) is envisioned as a key enabling technology of 6G wireless communication. In UM-MIMO systems, downlink channel state information (CSI) has to be fed to the base station for beamforming. However, the feedback overhead becomes unacceptable because of the large antenna array. In this letter, the characteristic of CSI is explored from the perspective of data distribution. Based on this characteristic, a novel network named Attention-GRU Net (AGNet) is proposed for CSI feedback. Simulation results show that the proposed AGNet outperforms other advanced methods in the quality of CSI feedback in UM-MIMO systems.