Towards furthering the industrial revolution, the concept of a new cellular network began to be drawn up around 2010 as the fifth generation (5G) mobile wireless communication system. One of the main differences between the fourth generation (4G) mobile communication system Long Term Evolution (LTE) and 5G new radio (NR) is the frequency bands utilized. 5G NR assumes higher frequency bands. Effective utilization of the higher frequency bands needs to resolve the technical issue of the larger path-loss. Massive multiple-input multiple-output (Massive MIMO) beamforming (BF) technology contributes to overcome this problem, hence further study of Massive MIMO BF for each frequency band is necessary toward high-performance and easy implementation. In this paper, then, we propose a Massive MIMO method with fully-digital BF based on two-tap precoding for low super high frequency (SHF) band downlink (DL) transmissions (called as Digital FBCP). Additionally, three intersite coordination algorithms for Digital FBCP are presented for multi-site environments and one of the three algorithms is enhanced. It is shown that Digital FBCP achieves better throughput performance than a conventional algorithm with one-tap precoding. Considering performance of intersite coordination as well, it is concluded that Digital FBCP can achieve around 5 Gbps in various practical environments.

A W-band corporate-feed 16×16-slot array antenna with low sidelobe level is designed and fabricated. The basic unit of the array is a 2×2-circular-slot subarray with step square cavities and uses an E-plane waveguide as the feeding line. An efficient method to design an unequal power-splitting ratio but equal phase (UPEP) E-plane waveguide T-junction (E-T) is proposed for constructing a 1-to-64 power-tapering feed network, which is the critical part to realize low sidelobe level. The whole array is fabricated with aluminum by milling and bonded by the vacuum brazing process. The measured results demonstrate that the array can achieve a 7.2% bandwidth with VSWR<1.5 and holistic sidelobe levels lower than -23.5dB in E-plane and H-plane from 89GHz ∼ 95.8GHz. The measured gain is higher than 31.7dBi over the working band with the antenna efficiency better than 67.5%.

Joint transmit and receive antenna selection (JTRAS) for transceive spatial modulation (TRSM) is investigated in this paper. A couple of low-complexity and efficient JTRAS algorithms are proposed to improve the reliability of TRSM systems by maximizing the minimum Euclidean distance (ED) among all received signals. Specifically, the QR decomposition based ED-JTRAS achieves near-optimal error performance with a moderate complexity reduction as compared to the optimal ED-JTRAS method. The singular value decomposition based ED-JTRAS achieves sub-optimal error performance with a significant complexity reduction. Simulation results show that the proposed methods remarkably improve the system reliability in both uncorrelated and spatially correlated Rayleigh fading channels, as compared to the conventional norm based JTRAS method.

The beamforming (BF) provided by Massive MIMO is a promising technique for the fifth-generation (5G) mobile communication system. In low SHF bands such as 3-6GHz, fully digital Massive MIMO can be a feasible option. Previous works proposed eigenvector zero-forcing (E-ZF) as a digital precoding algorithm to lower the complexity of block diagonalization (BD). On the other hand, another previous work aiming to reduce complexity of BD due to the number of antenna elements proposed digital fixed BF and channel-state-information based precoding (Digital FBCP) with BD whose parameter is the number of beams. Moreover, in order to lower the complexity of the Digital FBCP with BD while retaining the transmission performance, this paper proposes Digital FBCP with E-ZF as a lower complexity digital BF algorithm. The pros and cons of these digital BF algorithms in terms of transmission performance and computational complexity are clarified to select the most appropriate algorithm for the fully digital Massive MIMO. Furthermore, E-ZF can be implemented to 4.5GHz-band fully digital Massive MIMO equipment only when the number of antenna elements is less than or equal to 64, and thus 5G experimental trial employing E-ZF was carried out in Tokyo, Japan where early 5G commercial services will launch. To the best of our knowledge, this was the first outdoor experiment on 4.5GHz-ban Massive MIMO in a dense urban area. An outdoor experiment in a rural area was also carried out. This paper shows both a coverage performance under the single user condition and system throughput performance under a densely deployed four-user condition in the outdoor experimental trials employing the E-ZF algorithm. We reveal that, in the MU-MIMO experiment, the measured system throughput is almost 80% of the maximum system throughput even if users are closely located in the dense urban area thanks to the E-ZF algorithm.

Accurate traffic flow prediction is the precondition for many applications in Intelligent Transportation Systems, such as traffic control and route guidance. Traditional data driven traffic flow prediction models tend to ignore traffic self-features (e.g., periodicities), and commonly suffer from the shifts brought by various complex factors (e.g., weather and holidays). These would reduce the precision and robustness of the prediction models. To tackle this problem, in this paper, we propose a CNN-based multi-feature predictive model (MF-CNN) that collectively predicts network-scale traffic flow with multiple spatiotemporal features and external factors (weather and holidays). Specifically, we classify traffic self-features into temporal continuity as short-term feature, daily periodicity and weekly periodicity as long-term features, then map them to three two-dimensional spaces, which each one is composed of time and space, represented by two-dimensional matrices. The high-level spatiotemporal features learned by CNNs from the matrices with different time lags are further fused with external factors by a logistic regression layer to derive the final prediction. Experimental results indicate that the MF-CNN model considering multi-features improves the predictive performance compared to five baseline models, and achieves the trade-off between accuracy and efficiency.

Massive multiple input and multiple output (Massive MIMO) is a key technique to achieve high system capacity and user data rate for the fifth generation (5G) radio access network (RAN). To implement Massive MIMO in 5G, how much Massive MIMO meets our expectation with various user equipment (UEs) in different environments should be carefully addressed. We focused on using Massive MIMO in the low super-high-frequency (SHF) band, which is expected to be used for 5G commercial bands relatively soon. We previously developed a prototype low-SHF-band centralized-RAN Massive MIMO system that has a flexible active antenna system (AAS)-unit configuration and facilitates advanced radio coordination features, such as coordinated beamforming (CB) coordinated multi-point (CoMP). In this study, we conduct field trials to evaluate downlink (DL) multi-user (MU)-MIMO performance by using our prototype system in outdoor and indoor environments. The results indicate that about 96% of the maximum total DL system throughput can be achieved with 1 AAS unit outdoors and 2 AAS units indoors. We also investigate channel capacity based on the real propagation channel estimation data measured by the prototype system. Compared with without-CB mode, the channel capacity of with-CB mode increases by a maximum of 80% and 104%, respectively, when the location of UEs are randomly selected in the outdoor and indoor environments. Furthermore, the results from the field trial of with-CB mode with eight UEs indicate that the total DL system throughput and user data rate can be significantly improved.

This work presents an FSK inductive-coupling transceiver using a load-modulated transmitter and LC-oscillator-based receiver for energy-budget-unbalanced applications. By introducing the time-domain load modulated transmitter for FSK instead of the conventional current-driven scheme, energy reduction of the transmitter side is possible. For verifying the proposed scheme, a test chip was fabricated in 65nm CMOS, and two chips were stacked for verifying the inter-chip communication. The measurement results show 0.64fJ/bit transmitter power consumption while its input voltage is 60mV, and the communication distance is 150μm. The footprint of the transmitter is 0.0016mm2.

This work presents the lowest power consumption sub-mm2 supply-modulated OOK transmitter for self-powering a continuous glucose monitoring (CGM) contact lens. By combining the transmitter with a glucose fuel cell that functions as both the power source and a sensing transducer, a self-powered CGM contact lens was developed. The 385×385μm2 test chip implemented in 65-nm standard CMOS technology operates at 270pW with a supply voltage of 0.165V. Self-powered operation of the transmitter using a 2×2mm2 solid-state glucose fuel cell was thus demonstrated.

A low voltage stochastic flash ADC (analog-to-digital converter) is presented, with an inverter-based comparative unit which is used to replace comparator for comparison. Aiming at the low voltage and low power consumption, a key of our design is in the simplicity of the structure. The inverter-based comparative unit replacing a comparator enables us to decrease the number of transistors for area saving and power reduction. We insert the inverter-chain in front of the comparative unit for the signal stability and discuss an appropriate circuit structure for the resolution by analyzing three different ones. Finally, we design the whole stochastic flash ADC for verifying our idea, where the supply voltage can go down to 0.6V on the 65nm CMOS process, and through post-layout simulation result, we can observe its advantage visually in voltage, area and power consumption.

VLSIs that perform signal processing near infrared sensors cooled to ultra-low temperature are demanded. Delay test of those chips must be executed at ultra-low temperature while functional test could be performed at room temperature as long as hold timing errors do not occur. In this letter, we focus on the hold timing violation and evaluate the feasibility of functional test of ultra-low temperature circuits at room temperature. Experimental evaluation with a case study shows that the functional test at room temperature is possible.

Body bias generators are useful circuits that can reduce variability and power dissipation in LSI circuits. However, the amplifier implemented into the body bias generator is difficult to design because of its complexity. To overcome the difficulty, this paper proposes a clearer cell-based design method of the amplifier than the existing cell-based design methods. The proposed method is based on a simple analytical model, which enables to easily design the amplifiers under various operating conditions. First, we introduce a small signal equivalent circuit of two-stage amplifiers by which we approximate a three-stage amplifier, and introduce a method for determining its design parameters based on the analytical model. Second, we propose a method of tuning parameters such as cell-based phase compensation elements and drive-strength of the output stage. Finally, based on the test chip measurement, we show the advantage of the body bias generator we designed in a cell-based flow over existing designs.

Stimulus response caused by low-frequency electromagnetic exposure can be used to realize effective medical treatments. However, it is well known that the membrane potential of nerve cells exhibits nonlinearity, particularly in the case of modulated signals, it is important to analyze the nonlinear stimulation effect based on a nerve cell model. This paper adopts the Frankenhaeuser-Huxley (FH) model as the nerve cell model, and evaluates the stimulus response based on the FH model when nerve cells are exposed to low-frequency modulated radio signals such as On-Off Keying (OOK) modulation. This paper investigated the nonlinear effect of the stimulus intensity from the viewpoint of the spike frequency with different modulation parameter values including the induced amplitude and duty cycle. It was confirmed that action potential (AP) rate was higher with OOK-type radio signals than with unmodulated signals.

A high-rate coding scheme that polar codes are concatenated with low density generator matrix (LDGM) codes is proposed in this paper. The scheme, referred to as polar-LDGM (PLG) codes, can boost the convergence speed of polar codes and eliminate the error floor behavior of LDGM codes significantly, while retaining the low encoding and decoding complexity. With a sensibly designed Gaussian approximation (GA), we can accurately predict the theoretical performance of PLG codes. The numerical results show that PLG codes have the potential to approach the capacity limit and avoid error floors effectively. Moreover, the encoding complexity is lower than the existing LDPC coded system. This motives the application of powerful PLG codes to satellite communications in which message transmission must be extremely reliable. Therefore, an adaptive relaying protocol (ARP) based on PLG codes for the relay satellite system is proposed. In ARP, the relay transmission is selectively switched to match the channel conditions, which are determined by an error detector. If no errors are detected, the relay satellite in cooperation with the source satellite only needs to forward a portion of the decoded message to the destination satellite. It is proved that the proposed scheme can remarkably improve the error probability performance. Simulation results illustrate the advantages of the proposed scheme

In this study, under the assumption that a robot (1) has a remotely controllable yawing camera and (2) moves in a uniform linear motion, we propose and investigate how to improve the target recognition rate with the camera, by using wireless feedback loop control. We derive the allowable data rate theoretically, and, from the viewpoint of error and delay control, we propose and evaluate QoS-Hybrid ARQ schemes under data rate constraints. Specifically, the theoretical analyses derive the maximum data rate for sensing and control based on the channel capacity is derived with the Shannon-Hartley theorem and the path-loss channel model inside the human body, i.e. CM2 in IEEE 802.15.6 standard. Then, the adaptive error and delay control schemes, i.e. QoS-HARQ, are proposed considering the two constraints: the maximum data rate and the velocity of the camera's movement. For the performance evaluations, with the 3D robot simulator GAZEBO, we evaluated our proposed schemes in the two scenarios: the static environment and the dynamic environment. The results yield insights into how to improve the recognition rate considerably in each situation.

In this paper, we consider a group testing (GT) problem. We derive a lower bound on the probability of error for successful decoding of defected binary signals. To this end, we exploit Fano's inequality theorem in the information theory. We show that the probability of error is bounded as an entropy function, a density of a pooling matrix and a sparsity of a binary signal. We evaluate that for decoding of highly sparse signals, the pooling matrix is required to be dense. Conversely, if dense signals are needed to decode, the sparse pooling matrix should be designed to achieve the small probability of error.

This article presents a universal and versatile model of multiservice overflow systems based on Hayward's concept. The model can be used to analyze modern telecommunications and computer networks, mobile networks in particular. The advantage of the proposed approach lies in its ability to analyze overflow systems with elastic and adaptive traffic, systems with distributed resources and systems with non-full-availability in primary and secondary resources.

Low Power Wide Area Network (LPWAN) is designed for low-bandwidth, low-power, long-distance, large-scale connected IoT applications and realistic for networking in an emergency or restricted situation, so it has been proposed as an attractive communication technology to handle unexpected situations that occur during and/or after a disaster. However, the traditional LPWAN with its default protocol will reduce the communication efficiency in disaster situation because a large number of users will send and receive emergency information result in communication jams and soaring error rates. In this paper, we proposed a LPWAN based decentralized network structure as an extension of our previous Disaster Information Sharing System (DISS). Our network structure is powered by Named Node Networking (3N) which is based on the Information-Centric Networking (ICN). This network structure optimizes the excessive useless packet forwarding and path optimization problems with node name routing (NNR). To verify our proposal, we conduct a field experiment to evaluate the efficiency of packet path forwarding between 3N+LPWA structure and ICN+LPWA structure. Experimental results confirm that the load of the entire data transmission network is significantly reduced after NNR optimized the transmission path.

This paper presents an ultra-low-power class-AB bulk-driven operational transconductance amplifier operating in the subthreshold region. Employing the partial positive feedback in current mirrors, the effective transconductance and output voltage swing are enhanced considerably without additional power consumption and layout area. Both traditional and proposed OTAs are designed and simulated for a 180 nm CMOS process. They dissipate an ultra low power of 192 nW. The proposed OTA features not only a DC gain enhancement of 14 dB but also a slew rate improvement of 200%. In addition, the improved gain leads to a 5.3 times wider unity-gain bandwidth than that of the traditional OTA.

This paper proposes a novel low complexity lattice reduction-aided iterative receiver for overloaded MIMO. Novel noise cancellation is proposed that increases an equivalent channel gain with a scalar gain introduced in this paper, which results in the improvement of the signal to noise power ratio (SNR). We theoretically analyze the performance of the proposed receiver that the lattice reduction raises the SNR of the detector output signals as the scalar gain increases, when the Lenstra-Lenstra-Lova's (LLL) algorithm is applied to implement the lattice reduction. Because the SNR improvement causes the scalar gain to increase, the performance is improved by iterating the reception process. Computer simulations confirm the performance. The proposed receiver attains a gain of about 5dB at the BER of 10-4 in a 6×2 overloaded MIMO channel. Computational complexity of the proposed receiver is about 1/50 as much as that of the maximum likelihood detection (MLD).

The ability of Software Defined Networking (SDN) to dynamically adjust the network behaviour and to support fine-grained routing policies becomes increasingly attractive beyond the boundaries of Data Centre domains, where SDN has already gained enormous momentum. However, the wider adoption of SDN in ISP (Internet Service Provider) networks is still uncertain due to concerns about the scalability of a centralized traffic management in large-scale environments. This is particularly problematic when ISP offers virtual-link services, which imply a performance guaranteed data transfer between two network points. Our solution is a new approach to virtual-link mapping in SDN-based ISP networks. Within the problem's scope, we address traffic engineering (TE), QoS provisioning and failure recovery issues. In order to decrease the controller load, computational effort, and processing delay, we introduce a function split between online routing and TE. The TE functions are performed periodically, with configurable periodicity. In order to reduce the control overhead, we restrict the traffic optimization problem to load balancing over multiple static tunnels. This allows retention of the traditional MPLS routers in the network core and to achieve fast virtual-link restoration in case of physical-link failures. The online routing and admission control algorithms have been designed with the goal of low complexity, and to minimize Flow-table updates. In our simulation study, we compare the proposed virtual-link mapping solution with the solutions that exploit routing flexibility in fully SDN-enabled networks. We find that the throughput loss due to the use of static traffic tunnels is relatively small, while the control overhead is reduced significantly. A prototype of the proposed SDN control-plane is developed and validated in the Mininet emulator.