In this paper, we propose a beamforming design method for a cooperative NOMA downlink system wherein a relay node assisting a far user operates in full-duplex mode to achieve high spectral efficiency. The proposed method, based on the zero-forcing (ZF) principle, suppresses both self-interference and inter-user interference. Simulation results show that the proposed method is considerably superior to the conventional transmit ZF method, achieving performance comparable to that of the optimum method while reducing complexity.

The inaudible sound communication system of our implementation estimates the correct positions of received symbols in its decoding process by calculating the correlations with the pre-defined synchronization patterns. This paper describes that a theoretical approach based on solving Euler graphs taking account of constraint conditions may potentially provide more efficient synchronization patterns, compared with the conventional technique that employs random sequences for designing synchronization patterns.

A composite high gain antenna whose working frequencies are separated far away from each other is proposed in this paper. It is composed of a dielectric superstrate that is excited by patch antennas. The superstrate works as electromagnetic band gap (EBG) resonator for C band achieving the gain of 16.7 dBi at 4.8 GHz in simulation. While it also works as Fresnel lens for K band, the gain reaches 30.4 dBi at 24 GHz. Compared to a single patch antenna, 7.2 dB and 21.4 dB gain enhancement are obtained in those two frequencies respectively. The impact of the superstrate is also verified by the experiment. It has been confirmed that the superstrate increases gain at two frequency bands.

In a post-disaster area, Unmanned Aerial Vehicles (UAVs) are considered one of the most effective ways to provide emergency wireless communication services. In this letter, we investigate the UAV-based emergency wireless communication network for a post-disaster area. Our optimization problem aims to optimize the UAV 3D flight trajectory to maximize the number of visited ground users during the flight round. Then, a dual-cost-aware multi-armed bandit algorithm is adopted to tackle this problem under the limited available energy for both the UAV and ground users. Finally, simulation results show that the proposed algorithm could solve the optimization problem and maximize the achievable throughput under these constraints.

Dual-band omnidirectional antenna with single radome is proposed. To ensure the characteristic of the proposed radome, mathematical calculation under multi-layer multi-reflection condition is derived. The cross points of reflection coefficient phase and ideal phase limitation show the potentially available frequency. The magnitude of the reflection coefficient at the same time selects the available frequency from potential frequencies. Simulation is utilized to evaluate the correctness of the calculation. Finally, the gain enhancement effect is exactly evaluated through the simulated radiation pattern results. And 1 dB increment of average gain in proposed omnidirectional antenna at both frequencies is observed. Also further optimization towards the PRS or radome is necessary.

Economic losses due to delays in traffic congestion is serious social problems. Platooning has recently been attracting attentions from many researchers to alleviate traffic jams, especially in highway. On highways, platooning can have positive effects, such as running at a constant speed with multiple vehicles which leads to fuel-efficient driving, reducing air resistance and so on. However, the impacts of platooning in urban roads have not been addressed in detail since traffic lights may break the platoons. In this paper, we propose a platooning method using L2 norm and cosine similarity to form platoon with highly similar routes. Also, we investigate the sorting method within a platoon according to each vehicle’s straightness to eliminate Head of Line blocking at intersections and improve throughput at intersections. We propose a Cyber-Physical System approach to control platoon collaboratively in urban roads. Computer simulation results confirmed that the proposed method shortens the average travel time by 34.31%. This paper also shows the validity of forming platoon based on destination vectors and sorting vehicles within a platoon.

In the fifth-generation (5G) wireless communications, due to the advantages such as wide range and low cost, sub-6 frequency band is widely used. It is a challenge to develop the antennas for sub-6 base stations which are wide band, high gain and compact. In this paper, a center-fed collinear antenna array with a compact size is developed which based on the turnstile antenna. Non-uniform dipole array has been used to achieve broadband so that the disadvantages of series can be improved. The gain bandwidth has been significantly increased as compared to uniform array antennas. Wider directivity gain bandwidth of 35% is provided by the non-uniform array. The proposed array antenna can be used to omnidirectional radiation applications. The directivity gain bandwidth reached to 20.7% better than traditional series fed antennas.

A method for direction of arrival (DOA) estimation and object localization based on 1-bit time-modulated reflectarray (TMRA) is presented. The multi-harmonic multi-beam (MHMB) characteristic of 1-bit TMRA is analyzed firstly to reveal the mapping relationship between target’s angular feature and received spectrum feature. Then the operating principle and perception procedures for single and multiple targets scenarios are discussed in detail. Benefited from the mapping relationship, the proposed method shows flexibility on simultaneous multi-target detection, which is difficult to realize by conventional methods. Furthermore, the proposed method enables the environment-perception capability of existing 1-bit TMRA without increasing the system complexity, making it suitable for the realization of a low-cost multifunctional reconfigurable intelligent surface (RIS).

Image inference using deep learning (DL) has recently become popular in a variety of applications. In the near future, real-time inference for delay sensitive images will be widespread with the edge computing paradigm, where DL processing will be executed at the edge of the network. In this study, a DL inference method in near future edge computing is proposed to infer a large number of images, which are aggregated from various end devices toward an edge server and are temporarily stored in a queue, with different requirements on inference time. With the proposed method, the inference time including waiting time in a queue for a delay sensitive image is guaranteed and that for a delay tolerant image is minimized by adaptively partitioning the DL processing executed for delay tolerant images between an edge and a cloud server depending on the arrival conditions of images at an edge server. The effectiveness of the proposed method is evaluated via simulation.

There are many problems in setting appropriate quality requirements for communication flows. If flows that require low latency or high reliability are treated the same as other flows, these flows are susceptible to congestion. Therefore, we are studying technologies to effectively utilize network resources by identifying flows and setting appropriate quality requirements. When identifying flows, there is a problem that the traffic behavior changes due to available bandwidth limitations, and the identification accuracy decreases. In this paper, we explain the cause of the problem and show our improved application category estimation method mitigating the impact of available bandwidth fluctuations.

This paper proposes MAP estimation using two temporally consecutive data using signals from eight ultrasonic sensors forming a linear array. First, we estimate the distance to the obstacle from the time difference between the eight received signals. Then, assuming that the ranging error follows a Gaussian distribution and that each of the eight ranging values is independent, we can get the existence probability of the obstacle’s position by a pair of two obtained distances. Finally, we estimate the position of the obstacle by multiplying 28 (₈C₂) existence probabilities obtained. The conventional method estimates the position of an obstacle by the above procedure. However, the estimation accuracy in the angular direction was poor, resulting in the spread of the existence probability in the horizontal direction. In the proposed MAP estimation using two temporally consecutive data, we obtain the existence probability of an obstacle by the procedure shown above, and then use it as a prior probability of the obstacle’s estimated position. Furthermore, we recursively perform the same process to obtain the existence probability of the obstacle. In this way, we improve the accuracy of the estimation of the position of the obstacle by the existence probability. We present the experiment results to show the effectiveness of the proposed method.

This study proposes a novel method for determining the number of simultaneously accessing sensors in physical wireless parameter conversion sensor networks (PhyC-SN), which can collect sensor information from numerous sensors simultaneously, using phase variation due to frequency offset as an identifier. However, the identification accuracy deteriorates when the frequency offsets of the simultaneously accessed sensors are close to each other. In the proposed method, the transmitted signal is divided by time and the frequency offset is switched for each signal transmission. Computer simulations reveal that the identification accuracy of collision detection improves and an appropriate number of frequency switches exist.