Efficient multiplexing of ultra-reliable and low-latency communications (URLLC) and enhanced mobile broadband (eMBB) traffic, as well as ensuring the various reliability requirements of these traffic types in 5G wireless communications, is becoming increasingly important, particularly for vertical services. Interference management techniques, such as coordinated inter-cell scheduling, can enhance reliability in dense cell deployments. However, tight inter-cell coordination necessitates frequent information exchange between cells, which limits implementation. This paper introduces a novel RAN slicing framework based on centralized frequency-domain interference control per slice and link adaptation optimized for URLLC. The proposed framework does not require tight inter-cell coordination but can fulfill the requirements of both the decoding error probability and the delay violation probability of each packet flow. These controls are based on a power-law estimation of the lower tail distribution of a measured data set with a smaller number of discrete samples. As design guidelines, we derived a theoretical minimum radio resource size of a slice to guarantee the delay violation probability requirement. Simulation results demonstrate that the proposed RAN slicing framework can achieve the reliability targets of the URLLC slice while improving the spectrum efficiency of the eMBB slice in a well-balanced manner compared to other evaluated benchmarks.

Handover is an important property of cellular communication that enables the user to move from one cell to another without losing the connection. It is a very crucial process for the quality of the user’s experience because it may interrupt data transmission. Therefore, good handover management is very important in the current and future cellular systems. Several techniques have been employed to improve the handover performance, usually to increase the probability of a successful handover. One of the techniques is predictive handover which predicts the target cell using some methods other than the traditional measurement-based algorithm, including using machine learning. Several studies have been conducted in the implementation of predictive handover, most of them by modifying the internal algorithm of existing network elements, such as the base station. We implemented a predictive handover algorithm using an intelligent node outside the existing network elements to minimize the modification of the network and to create modularity in the system. Using a recently standardized Open Radio Access Network (O-RAN) Near Realtime Radio Intelligent Controller (Near-RT RIC), we created a modular application that can improve the handover performance by determining the target cell using machine learning techniques. In our previous research, we modified The Near-RT RIC original software that is using vector autoregression to determine the target cell by predicting the throughput of each neighboring cell. We also modified the method using a Multi-Layer Perceptron (MLP) neural network. In this paper, we redesigned the neural network using Long Short-Term Memory (LSTM) that can better handle time series data. We proved that our proposed LSTM-based machine learning algorithms used in Near-RT RIC can improve the handover performance compared to the traditional measurement-based algorithm.

We evaluated the transmission performance, including received power and transmission throughput characteristics, in 4×4 single-user multiple-input multiple-output (SU-MIMO) transmission for synchronous time division duplex (TDD) and downlink data channels in comparison with single-input single-output (SISO) transmission in an environment where a local 5G wireless base station was installed on the roof of a research building at our university. Accordingly, for the received power characteristics, the difference between the simulation value, which was based on the ray tracing method, and the experimental value at 32 points in the area was within a maximum difference of approximately 10 dB, and sufficient compliance was obtained. Regarding the transmission throughput versus received power characteristics, after showing a simulation method for evaluating throughput characteristics in MIMO, we compared the results with experimental results. The cumulative distribution function (CDF) of the transmission throughput shows that, at a CDF of 50%, in SISO transmission, the simulated value is approximately 115Mbps, and the experimental value is 105Mbps, within a difference of approximately 10Mbps. By contrast, in MIMO transmission, the simulation value is 380Mbps, and the experimental value is approximately 420Mbps, which is a difference of approximately 40Mbps. It was shown that the received power and transmission throughput characteristics can be predicted with sufficient accuracy by obtaining the delay profile and the system model at each reception point using the both ray tracing and MIMO simulation methods in actual environments.

The fifth-generation (5G) new radio (NR) standard employs ultra-reliable and low-latency communication (URLLC) to provide real-time wireless interactive capability for the internet of things (IoT) applications. To satisfy the stringent latency and reliability demands of URLLC services, grant-free (GF) transmissions with the K-repetition transmission (K-Rep) have been introduced. However, fading fluctuations can negatively impact signal quality at the base station (BS), leading to an increase in the number of repetitions and raising concerns about interference and energy consumption for IoT user equipment (UE). To overcome these challenges, this paper proposes novel adaptive K-Rep control schemes that employ site diversity reception to enhance signal quality and reduce energy consumption. The performance evaluation demonstrates that the proposed adaptive K-Rep control schemes significantly improve communication reliability and reduce transmission energy consumption compared with the conventional K-Rep scheme, and then satisfy the URLLC requirements while reducing energy consumption.

Fifth generation mobile communication system (5G) mobile operators need to explore new use cases and/or applications together with vertical industries, the industries that are potential users of 5G, in order to fully exploit the new 5G capabilities in terms of its application. Vehicle-to-Everything (V2X) communications for platooning are considered to be one of new 5G use cases whose ultra reliable and low latency communication (URLLC) aspects are required. The authors build a field experimental environment, towards application to truck platooning, with actual large-size trucks and a prototype system, for 5G New Radio (NR) technology based V2X communications. Its most distinctive feature is that the 5G NR-V2X prototype system is equipped with UE-to-UE radio interface (i.e., sidelink) for V2V Direct communication, in addition to the traditional radio interfaces between BS and UE for V2N/V2N2V communications. This paper presents performance evaluation and demonstration of real-time vehicle control information exchange using over the sidelink of 5G NR-V2X prototype system for automated follower truck platooning. This paper evaluates the V2V Direct communication latency and reliability performance of the sidelink, and clarify 5G NR sidelink achieves lower peak of latency and higher packet reception rate in V2V Direct communication performance than an optical wireless communication system product. Then, it also introduces a 5G URLLC use case demonstration of automated follower truck platooning trial employed with the prototype system in a public expressway environment.

Recently, there has been a surge of interest in Artificial Intelligence (AI) and its applications have been considered in various fields. Mobile networks are becoming an indispensable part of our society, and are considered as one of the promising applications of AI. In the Beyond 5G/6G era, AI will continue to penetrate networks and AI will become an integral part of mobile networks. This paper provides an overview of the collaborations between networks and AI from two categories, “AI for Network” and “Network for AI,” and predicts mobile networks in the B5G/6G era. It is expected that the future mobile network will be an integrated infrastructure, which will not only be a mere application of AI, but also provide as the process infrastructure for AI applications. This integration requires a driving application, and the network operation is one of the leading candidates. Furthermore, the paper describes the latest research and standardization trends in the autonomous networks, which aims to fully automate network operation, as a future network operation concept with AI, and discusses research issues in the future mobile networks.

It has become increasingly important for industries to promote digital transformation by utilizing 5G and industrial internet of things (IIoT) to improve productivity. To protect IIoT application performance (work speed, productivity, etc.), it is often necessary to satisfy quality of service (QoS) requirements precisely. For this purpose, there is an increasing need to automatically identify the root causes of radio-quality deterioration in order to take prompt measures when the QoS deteriorates. In this paper, a method for identifying the root cause of 5G radio-quality deterioration is proposed that uses machine learning. This Random Forest based method detects the root cause, such as distance attenuation, shielding, fading, or their combination, by analyzing the coefficients of a quadratic polynomial approximation in addition to the mean values of time-series data of radio quality indicators. The detection accuracy of the proposed method was evaluated in a simulation using the MATLAB 5G Toolbox. The detection accuracy of the proposed method was found to be 98.30% when any of the root causes occurs independently, and 83.13% when the multiple root causes occur simultaneously. The proposed method was compared with deep-learning methods, including bidirectional long short-term memory (bidirectional-LSTM) or one-dimensional convolutional neural network (1D-CNN), that directly analyze the time-series data of the radio quality, and the proposed method was found to be more accurate than those methods.

Beyond 5G is the next generation mobile communication system expected to be used from around 2030. Services in the 2030s will be composed of multiple systems provided by not only the conventional networking industry but also a wide range of industries. However, the current mobile communication system architecture is designed with a focus on networking performance and not oriented to accommodate and optimize potential systems including service management and applications, though total resource optimizations and service level performance enhancement among the systems are required. In this paper, a new concept of the Beyond 5G cross-industry service platform (B5G-XISP) is presented on which multiple systems from different industries are appropriately organized and optimized for service providers. Then, an architecture of the B5G-XISP is proposed based on requirements revealed from issues of current mobile communication systems. The proposed architecture is compared with other architectures along with use cases of an assumed future supply chain business.

In 5th generation (5G) and Beyond 5G mobile communication systems, it is expected that numerous antennas will be densely deployed to realize ultra-broadband communication and uniform coverage. However, as the number of antennas increases, total power consumption of all antennas will also increase, which leads to a negative impact on the environment and operating costs of telecommunication operators. Thus, it is necessary to simplify an antenna structure to suppress the power consumption of each antenna. On the other hand, as a way to realize ultra-broadband communication, millimeter waves will be utilized because they can transmit signals with a broader bandwidth than lower frequencies. However, since millimeter waves have a large propagation loss, a propagation distance is shorter than that of low frequencies. Therefore, in order to extend the propagation distance, it is necessary to increase an equivalent isotropic radiated power by beamforming with phased array antenna. In this paper, a phased antenna array module in combined with analog radio over fiber (A-RoF) technology for 40-GHz millimeter wave is developed and evaluated for the first time. An 8×8 phased array antenna for 40-GHz millimeter wave with integrated photodiodes and RF chains has been developed, and end-to-end transmission experiment including 20km A-RoF transmission and 3-m over-the-air transmission from the developed phased array antenna has been conducted. The results showed that the 40-GHz RF signal after the end-to-end transmission satisfied the criteria of 3GPP signal quality requirements within ±50 degrees of main beam direction.

This paper presents a power amplifier (PA) designed as a part of a transceiver front-end fabricated in 130-nm SiGe BiCMOS. The PA shares its output antenna port with a low noise amplifier using a low-loss transmission/reception switch. The output matching network of the PA is designed to provide high output power, low AM-AM distortion, and uniform performance over frequencies in the range of 24.25-29.5GHz. Measurements of the front-end in TX mode demonstrate peak S21 of 30.3dB at 26.7GHz, S21 3-dB bandwidth of 9.8GHz from 22.2to 32.0GHz, and saturated output power (Psat) above 20dBm with power-added efficiency (PAE) above 22% from 24 to 30GHz. For a 64-QAM 400MHz bandwidth orthogonal frequency division multiplexing (OFDM) signal, -25dBc error vector magnitude (EVM) is measured at an average output power of 12.3dBm and average PAE of 8.8%. The PA achieves a competitive ITRS FoM of 92.9.

This work shows a broadband, high-efficiency power amplifier (PA) monolithic microwave integrated circuit (MMIC) that uses InP-based metal-oxide-semiconductor (MOS) high-electron-mobility transistors (HEMTs) with an extended drain-side access region and broadband conjugate matching topology. Advanced device technologies, namely, double-side-doped structures, MOS gate structures, and asymmetric gate recess, were adopted, and the length of the drain-side access region was optimized to simultaneously obtain high power and efficiency. A common-source PA MMIC based on InP-based MOS-HEMTs was fabricated, and an interstage circuit was designed to maximize the S21 per unit stage in the broadband, resulting in a record-high power-added efficiency and wide bandwidth.

The increasing demand for millimeter-wave (mmWave) frequencies with wider signal bandwidths, such as 5G NR, requires large investments on test equipment. This work presents a 5G mmWave up/down-converter with a 40 GHz LO, fabricated in custom PCBs with off-the-shelf components. The mmWave converter has broad IF and RF bandwidths of 1∼5 GHz and 21∼45 GHz, and the built-in LO generates 20∼29.5 GHz and 33.5∼40 GHz of output. To achieve high linearity of the converter simultaneously, the LO must produce low-phase-noise and be capable of high harmonics/spur rejection, and design techniques related to these features are demonstrated. Additionally, a reconfigurable IF amplifier for bi-directional conversion is included and demonstrates low gain variation to maintain the linearity of the wideband modulation signals. The final designed converter is tested with 5G OFDM 64-QAM 100 MHz 1-CC (4-CC) signals and shows RF/IF output power of -3/8 dBm with a linear range of 35 (30)/38 (33) dB at an EVM of 25 dB.

To cope with ever growing mobile data traffic, we recently proposed a concept of cellular ultra-dense radio access network (RAN). In the cellular ultra-dense RAN, a number of distributed antennas are deployed in the base station (BS) coverage area (cell) and user-clusters are formed to perform small-scale distributed multiuser multi-input multi-output (MU-MIMO) transmission and reception in each user-cluster in parallel using the same frequency resource. We also proposed a decentralized interference coordination (IC) framework to effectively mitigate both intra-cell and inter-cell interferences caused in the cellular ultra-dense RAN. The inter-cell IC adopted in this framework is the fractional frequency reuse (FFR), realized by applying the channel segregation (CS) algorithm, and is called CS-FFR in this paper. CS-FFR divides the available bandwidth into several sub-bands and allocates multiple sub-bands to different cells. In this paper, focusing on the optimization of the CS-FFR, we find by computer simulation the optimum bandwidth division number and the sub-band allocation ratio to maximize the link capacity. We also discuss the convergence speed of CS-FFR in a cellular ultra-dense RAN.

A 2-D beam scanning array antenna fed by a compact 16-way 2-D beamforming network (BFN) designed in Broadside Coupled Stripline (BCS) is addressed. The proposed 16-way 2-D BFN is formed by interconnecting two groups of 4x4 Butler Matrix (BM). Each group is composed of four compact 4x4 BMs. The critical point of the design is to propose a simple and compact 4x4 BM without crossover in BCS to achieve a better transmission coefficient of the 16-way 2-D BFN with reduced size of merely 0.8λ0×0.8λ0×0.04λ0. Moreover, the complexity of the interface connection between the 2-D BFN and the 4x4 patch array antenna is reduced by using probe feeding. The 16-way 2-D BFN is able to produce the phase shift of ±45°, and ±135° in x- and y- directions. The 2-D BFN is easily integrated under the 4x4 patch array to form a 2-D phased array capable of switching 16 beams in both elevation and azimuth directions. The area of the proposed 2-D beam scanning array antenna module has been significantly reduced to 2λ0×2λ0×0.04λ0. A prototype operating in the frequency range of 4-6GHz is fabricated and measured to validate the concept. The measurement results agree well with the simulations.

One of the key technologies for the fifth-generation (5G) mobile communication system is massive multiple-input multiple-output (MIMO) that applies beamforming in order to effectively compensate for large propagation losses in high frequency bands and enable the spatial multiplexing of a large number of signal streams over multiple users. To further improve a system throughput, a coordinated cluster system in which a large number of massive MIMO base stations are deployed in high density has been investigated. The dense deployment greatly improves the system capacity by controlling base stations from a centralized base band unit. However, when clusters are closely located in order to serve densely populated areas, inter-beam interference between adjacent clusters becomes more severe. To suppress the interference to adjacent clusters, only a simple beam switch control scheme at a cluster boundary has been investigated as a conventional scheme. In this paper, the scheduling algorithm for massive MIMO downlink transmission near cluster boundaries, which combines two scheduling algorithms, has been proposed. In the proposed scheme, each base station divides its own cell to multiple areas, switches supporting areas sequentially, and serves users in those areas. The numerical results show that the throughputs improve with a little reduction in a fairness index (FI) when the number of users per resource block is one. The FI reaches the highest when the number of users per cell is equal to the number of divided areas. The proposed scheme reduces computational complexity as compared with those of conventional two schemes.

High-accuracy wideband signal transmission is essential for 5G and Beyond wireless communication systems. Memory nonlinearity in transmitters is a serious issue for the goal, because it deteriorates the quality of signal and lowers the system performance. This paper studies a post-reception nonlinear compensation (PRC) schemes consisting of frequency domain equalizers (FDEs) and a blind nonlinear compensator (BNLC). A frequency-domain memory nonlinearity modeling approach is employed, and several PRC configurations with FDEs and BNLC are evaluated through computer simulations. It is concluded that the proposed PRC schemes can effectively compensate memory nonlinearity in wideband transmitters via frequency-selective propagation channel. By implementing the PRC in a base station, uplink performance will be enhanced without any additional cost and power consumption in user terminals.

We propose a radio-over-fiber (RoF) system with 1-bit outphasing modulation. The proposed RoF system does not require a power-hungry digital-to-analog converter in access points and relaxes the operation speed of optical transceivers to reduce device cost. We introduce two configurations to enable 1-bit outphasing modulation in our system; mixed-signal and all-digital configurations. In the mixed-signal configuration, the effects of harmonics and phase/amplitude mismatch on the adjacent channel leakage ratio (ACLR) were analyzed through simulation, and wideband transmission with a signal bandwidth of 400 MHz was experimentally verified, complying with the 3rd Generation Partnership Project (3GPP) standard for millimeter-wave band. Moreover, wide-band transmission with a signal bandwidth of 1 GHz was also experimentally verified for beyond-5G and 6G. The all-digital configuration can be implemented in a standard digital design flow. This configuration was also verified to comply with the 3GPP standard by properly selecting the intermediate and sampling frequencies to mitigate the effects of folded harmonics and quantization noise. Finally, the proposed RoF system with both configurations has been shown to have a higher bandwidth efficiency compared with other systems complying with the 3GPP standard for the ACLR. Therefore, the proposed RoF system provides a cost-effective in-building wireless solution for 5G and 6G mobile network systems.

To accelerate research on Beyond 5G (B5G) technologies in Japan, we propose an algorithm that designs mesh-type metropolitan area network (MAN) models based on a priori Japanese regional railway information, because ground-truth communication network information is unavailable. Instead, we use the information of regional railways, which is expected to express the necessary geometric structure of our metropolitan cities while remaining strongly correlated with their population densities and demographic variations. We provide an additional compression algorithm for use in reducing a small-scale network model from the original MAN model designed using the proposed algorithm. Two Tokyo MAN models are created, and we provide day and night variants for each while highlighting the number of passengers alighting/boarding at each station and the respective population densities. The validity of the proposed algorithm is verified through comparisons with the Japan Photonic Network model and another model designed using the communication network information, which is not ground-truth. Comparison results show that our proposed algorithm is effective for designing MAN models and that our result provides a valid Tokyo MAN model.

This article presents a 28GHz high-accuracy phase and amplitude detection circuit for dual-polarized phased-array calibration. With dual-polarized calibration scheme, external LO signal is not required for calibration. The proposed detection circuit detects phase and amplitude independently, using PDC and ADC. By utilizing a 28GHz-to-140kHz downconversion scheme, the phase and amplitude are detected more accurately. In addition, reference signal for PDC and ADC is generated from 28GHz LO signal with divide-by-6 dual-step-mixing injection locked frequency divider (ILFD). This ILFD achieves 24.5-32.5GHz (28%) locking range with only 3.0mW power consumption and 0.01mm2 area. In the measurement, the detection circuit achieves phase and amplitude detections with RMS errors of 0.17degree and 0.12dB, respectively. The total power consumption of the proposed circuit is 59mW with 1-V supply voltage.

Local (private) 5G system can provide a secure and flexible network using the cellular-based technologies at their facilities (e.g., factories, agricultural lands, and buildings). We constructed a small-scale demonstration system that exhibits the remote control of a patrol and work robot with arms using a local 5G system. The constructed robot comprises a robot operating system-based unmanned ground vehicle, two laser range finders, a webcam, an omnidirectional camera, and a six-axis robot arm. To fabricate a demonstration system with open-source software, we assessed the one-way delay of video streaming by changing different CPU, camera types, drivers, applications, and video resolutions. According to the assessment findings, it was demonstrated that it is possible to realize approximately 100ms delay under the limited resolution condition, and the allowable maximum absolute delay of 300ms can be attained even for full HD (1920 × 1080) resolution of this demonstration. Furthermore, local 5G was demonstrated to reduce delay variations to the same level as wired systems. It was also clarified that the increase in delay due to the application of local 5G is relatively small (5-25% in total delay) in this demonstration. Finally, we employed the small-scale demonstration system for the online and onsite campus tours for high school students.