Telephone calls have an essential function as a communication tool during emergencies in putting people’s minds at ease because they enable them to hear others’ voices in real time. However, such events lead to increased telephone-call traffic and damage to communication equipment, resulting in limited available communication resources. Therefore, we need VoIP admission control for emergencies that effectively utilize these limited resources. In our VoIP control system, we assign the optimum sending parameters to each VoIP session, considering the available communication resources, the distance between users, and the users’ characteristics. These parameters, which include voice payload size (VPS), affect the speech quality, sending bitrate, and delay. We maximize the number of VoIP sessions accommodated in networks by selecting the optimum parameters. In this paper, to implement such admission control, we propose a traffic model for a single VoIP session, which enables the VPS selection from multiples of 5 ms and unifies variable VPS traffic models. We also propose a method for deriving the proposed model from an existing traffic model. Furthermore, we show the VPS-selection range calculated by the proposed model in terms of delay and average bitrate.

In this paper, a direction of arrival (DoA) estimation system using a passive metasurface reflector and a single dipole antenna is considered to further simplify the feeding network and control circuit configuration. The proposed method achieves DoA estimation by mechanically changing the radiation patterns and using multiple frequency responses. The numerical analysis of DoA estimation demonstrated that the proposed system achieved the root-mean-square error (RMSE) of 1.76° at the signal-to-noise ratio of 20 dB, which is comparable to the system with a programmable metasurface reflector considering switching diodes. Additionally, even with the estimation angular range set to ± 60° and ± 90°, the deterioration of the RMSE was small, indicating that the proposed method can estimate the DoA over a wider angular range compared to a 7-element array. The correct estimation results were also achieved in the experiments.

Microwave energy has been extensively studied and used in various medical applications. Some of them involves the use of generator to generate, transmit, and emit the energy into human body as a mean of therapy. In this case, accurate measurement and/or manipulation of the microwave is necessary in order to ensure safety to the patients. However, this is a challenging task due to the interferences from the reflected waves caused by mismatch at each connection. Time domain analysis (TDA) using a vector network analyzer (VNA) is a commonly employed technique to separate the reflected waves of the antenna from those of the antenna. However, its requirement for sweeping over a broad frequency band renders it impractical for integration within a generator. To address this limitation, we propose a novel method for estimating reflection coefficients utilizing an autoregressive (AR) model. The proposed method offers the advantage of estimating the distance and reflection coefficient of each reflector simultaneously by sweeping over a narrow frequency band and measuring the reflection amplitude and phase. To validate the efficacy of this approach, simulations were conducted, demonstrating that the implemented AR model works correctly. Furthermore, experimental validation was performed with 10 sets of Devices Under Test (DUTs) fabricated. The reflection coefficients at 2.45 GHz were estimated for coaxial-slot antennas in air, water, and isopropyl alcohol (IPA). The error rates of the estimated reflection coefficients were found to be -1.38 ± 3.69% for air, -7.85 ± 17.8% for water, and -0.551 ± 8.29% for IPA, respectively. In the case of water, where even with an error of +2σ from the mean value, the difference between the mean radiated power of DUTs and the estimated one was only 1.37%, indicating that the estimation could be performed with sufficient accuracy. In conclusion, our proposed estimation method is promising for accurate estimation radiated power and detection abnormal conditions in microwave medical devices.

This paper presents a novel deep learning framework designed to tackle the challenging direction-of-arrival (DOA) estimation problem for time-varying arrays. Measurements from various array geometries are formulated using distinct and spatially overcomplete observation systems. Subsequently, a mapping relationship is established between the proxy spectrum and the shared spatial spectrum for deep learning. We introduce a fully convolutional network (FCN) that learns this mapping from a large training dataset. The problem is modeled as a multi-label classification task and the FCN is trained to predict DOAs. Numerical simulations show that the proposed architecture can better resolve closely spaced directions in low signal-to-noise ratio (SNR) compared to subspace-based and sparse reconstruction-based methods, the proposed FCN-based DOA estimator also exhibits high estimation accuracy over the entire spatial domain, and its ability to accurately identify the number of sources is significantly improved with the introduction of another training approach for cases where the number of sources is unknown.

A fully planar and circular beam-switching antenna module with 360° in-plane coverage is proposed for collision avoidance radar payload of drones. It consists of a novel dual-mode single-pole-multi-throw switch, a proposed circular beamforming network (CBFN), one-bit phase shifters, and quasi-Yagi antennas. The switch can redirect the input power to any one of the output ports (single-ON mode) or any two adjacent output ports (dual-ON mode). Owing to these two modes, the total beam number doubles. The CBFN is constructed by arranging the modified sub-matrices (MSMs) side-by-side into a circle with adjacent MSMs sharing their edge components (ECs). The MSMs are binomial power dividers with the ECs replaced by three-way power dividers. The ECs can split the power from the switch into adjacent MSMs and the EC at the following stage. For verification, a 12-beam prototype module designed at 5.8 GHz was fabricated and tested. Besides the agreement between the simulated and measured results, the 12 beam patterns exhibit highly similar shapes with sidelobe level < -13 dB and less-than-1-dB gain variation between the single-ON and dual-ON modes. The consistent 30° half-power beamwidths of the 12 beam patterns altogether cover the entire horizontal plane with minimal overlaps.

For the line-of-sight (LoS) link space, in order to maximize the data transmission capacity of the unmanned aerial vehicles (UAV) swarm communication system, the joint spectrum, power and flight path resources optimization are carried out. The system contains UAV-to-base station (U2B) and UAV-to-UAV (U2U) data links. In order to improve the spectrum usage efficiency, the U2U links can reuse the orthogonal spectrum of the U2B links. Based on deep Q network (DQN), the UAV are regarded as agents. By interacting with the system, the U2U links intelligently selects the appropriate communication resources. Considering the data characteristics of spatial UAV distribution, three different attention module networks are further introduced including the squeeze-and-excitation module (SE), the convolutional block attention module (CBAM) and the channel attention (CA) to improve the system performance. SE, CBAM and CA are trained and tested respectively. Simulation data shows that compared with benchmark algorithm, the proposed algorithms can reduce the complexity of training and obtain higher data transmission capacity.

Multiple antennas aided wireless communications under dense urban environments often suffer from keyhole effect, which leads to rank deficiency. Secrecy performance of artificial noise (AN) aided multiple-input multiple-output multiple-antenna eavesdropper (MIMOME) keyhole channels is investigated in this paper. Expressions of the asymptotic lines of some vital secrecy metrics are obtained in terms of secrecy outage probability (SOP) and average secrecy rate (ASR) in the high signal-to-noise ratio (SNR) regime, and are verified by Monte-Carlo simulations. It is shown that the secrecy performance is influenced by the antenna numbers at the transceiver and the eavesdropper. Most importantly, by comparing the scheme aided with AN to that without AN, it is found that AN plays a great role in enhancing security of MIMOME keyhole channels.

This paper proposes an unsourced random access (URA) scheme that can accommodate massive connectivity in the fifth generation (5G) and future 6G mobile networks. While most of conventional studies on URA have assumed narrowband transmission over flat fading channels, the proposed scheme supposes that broadband signals are transmitted from some user terminals to one base station (BS) equipped with massive multiple-input multiple-output (MIMO) receive antennas. Since such transmitted signals can experience frequency selective fading, the paper employs orthogonal frequency division multiplexing (OFDM), where the transmitted signals are spread over time-frequency domain. The transmission frame is partitioned into several slots and each user independently selects one slot for uplink packet transmission upon the index modulation (IM) principle. Each packet is composed of the following three parts: The first part activates a slot index while the second part selects one pilot sequence and random access pattern (RAP) from a common pool. The remaining part is polar encoded and the corresponding modulated symbols are spread over the whole selected slot. On the receiver side of the proposed scheme, concatenated activity detection (AD) is proposed to detect the active pilot indices with low complexity. Using both the result of AD and estimated channel frequency responses, the multiuser detector of the proposed scheme provides soft information on the coded bit sequences for single-user channel decoders that can extract data bit sequences. Furthermore, successive interference cancellation (SIC) is meticulously designed and repeats subtraction of detected signals from the received signals, which can gradually improve the message recovery performance. Computer simulations demonstrate that the proposed scheme can achieve excellent packet recovery and convergence performance over frequency selective channels while avoiding a considerable increase in computational complexity.

This paper proposes overloaded MIMO spatial multiplexing for uplinks with the massive MIMO where the number of the transmit antennas is less than that of the receive antennas. The proposed uplink overloaded MIMO spatial multiplexing makes it possible to increase the uplink user throughput by raising the number of the signal streams to that of the receive antennas. Moreover, we propose a novel idea called as “iterative colored noise cancellation” to improve the transmission performance of the proposed overloaded MIMO spatial multiplexing. This paper analyses the transmission performance that the proposed spatial multiplexing is degraded by the colored noise. Iterative colored noise cancellation is proposed for mitigating the performance degradation. The performance of the proposed spatial multiplexing is evaluated in an overloaded MIMO system where 2 antennas and 4 antennas are placed on the transmitter and the receiver respectively. The proposed colored noise cancellation achieves a gain of about 10 dB. The proposed uplink overloaded spatial multiplexing attains a diversity order of about 6 even when the number of the spatially multiplexed signal streams is increased to 6.

This paper proposes a low complexity scheduling for uplink multi-user multiple-input-multiple-output (MU-MIMO) that takes an approach of iterative heuristic search. The proposed scheduling randomly selects some of all the users in a cell, and searches the best combination of users in the possible combinations of the selected users for the MU-MIMO communication. The proposed scheduling iterates the above user search, while the best combination of the user is carried over to the user combination search at the next iteration. The performance of the proposed scheduling is evaluated in a three-dimensional wireless network by computer simulation. Even though the proposed scheduling can be implemented with approximately 1/100 less complexity than the optimum scheduling which is regarded as a representative of conventional techniques, the performance of the proposed scheduling is shown to be near as superior as that of the optimum scheduling.

We have been studying spectrum division transmission techniques to better utilize the unused frequency resources scattered over the satellite transponder by attaching an adapter to the existing satellite modem. Past studies were focusing on spectrum division of contiguous signals between point to point communications. This paper newly focuses on the spectrum division of burst signals assuming a data gathering system from multi-points to a single point via satellite. In applying the direct spectrum division transmission to burst signals, the conventional phase synchronization technique cannot be applied as it is. To overcome this problem, this paper proposes the insertion of special phase synchronization signals in front of the burst preamble signals at Tx DSDT adapter. This proposal enables the receiver to estimate the spectrum phase at the cross point of spectrum division and to compensate for the spectrum phase difference between adjacent sub-spectra. This paper evaluates the fundamental BER performance and shows how the proposed technique works as expected.

In order to improve the detection performance of small targets under sea clutter background, a detection method based on bagging decision tree with multi-feature information fusion is proposed. First, the time-frequency domain characterization of the standard deviation ratio of the average range of the pulse and amplitudes (SDRARPA) is proposed to describe the discrete echo signal sharpness. Second, the frequency peak-to-average standard deviation ratio (FPASDR) is proposed to optimize the frequency peak-to-average ratio (FPAR) feature. The first two features and the average relative average amplitude (ARAA) form a three-feature information fusion. Weak target detection at sea surface using false alarm controllable bagging decision tree detector based on bagging decision tree classification method. Finally, based on the IPIX measured data, the performance of the algorithms is compared and analyzed for the radar signal data under the four polarization modes. Experimental results show that the detection method proposed in this paper obtains 98.1% and 98.8% average detection probability in 1.024 s and 2.048 s observation time, respectively. There is a significant improvement in the detection performance compared to the traditional detection methods based on convex packet detector and SVM detector.

Radar provides information on target distance, direction, and velocity, but not directly on angular velocity. We study signal processing for estimating angular velocity directly by radar. First, we describe the signal model. In addition, the Cramer-Rao lower bound (CRLB) is derived to show the feasibility of angular velocity estimation. Furthermore, a method for estimating angular velocity is proposed in which the angular velocity is obtained by capturing the variations in the angular spectrum after noise reduction for signals represented in two dimensions: array and slow time. Specifically, we focus the signal with a frequency transform in the slow-time direction, insert zeros outside the focused target, and perform an inverse frequency transformation to obtain the signal with less noise. In the array direction, zeros are inserted on both sides, frequency transform is carried out, and interpolation is performed to capture the time variation to the azimuth angle. The angular velocity is obtained by evaluating the captured angular change using the least-squares method. Evaluation results show that angular velocity estimation performance improves with more antennas and higher signal-to-noise power ratio. When inserting zeroes, the appropriate length of target extraction can mitigate the adverse effects of noise and the Gibbs phenomenon. However, the angular velocity estimation performance of the proposed method deviates from that of the CRLB and requires improvement.