This letter presents a computational complexity reduction technique for space diversity based spectrum sensing when the number of receive antennas is greater than three (NR≥3 where NR is the number of receive antenna). The received signals are combined with phase inversion so as to not attenuate the combined signal, and a statistic for signal detection is computed from the combined signal. Because the computation of only one statistic is required regardless of the number of receive antenna, the complexity can be reduced. Numerical examples and simple analysis verify the effectiveness of the presented technique.

Nowadays, malware is a serious threat to the Internet. Traditional signature-based malware detection method can be easily evaded by code obfuscation. Therefore, many researchers use the high-level structure of malware like function call graph, which is impacted less from the obfuscation, to find the malware variants. However, existing graph match methods rely on approximate calculation, which are inefficient and the accuracy cannot be effectively guaranteed. Inspired by the successful application of graph convolutional network in node classification and graph classification, we propose a novel malware similarity metric method based on graph convolutional network. We use graph convolutional network to compute the graph embedding vectors, and then we calculate the similarity metric of two graph based on the distance between two graph embedding vectors. Experimental results on the Kaggle dataset show that our method can applied to the graph based malware similarity metric method, and the accuracy of clustering application with our method reaches to 97% with high time efficiency.

Urban area suffers severe multipath effects due to its complex infrastructure environment and sector antenna is a popular choice as a base station antenna in those areas. Within sector antennas, omni cell antenna is utilized as supporting antenna to cover low reception areas between them. This paper proposes a slant 45° dual polarized omnidirectional antenna to operate as the omni cell antenna in those environments. The frequency band covers the IMT band, ranging from 1920MHz to 2170MHz with directivity focusing in horizontal plane. The antenna structure consists of a loop slot antenna array as excitation element which is placed inside a cylindrical slot antenna as parasitic element. Good performance is achieved in both S-parameter and directivity results, with a gain of more than 4 dBi and a gain difference of less than 1.5dB. The measurement results also agree well with the simulation results and the final design confirms that the proposed antenna works effectively as a slant ±45 ° dual polarized omnidirectional antenna.

Refinement-based formal specification is a promising approach to the increasing complexity of software systems, as demonstrated in the formal method Event-B. It allows stepwise modeling and verifying of complex systems with multiple steps at different abstraction levels. However, making changes is more difficult, as caution is necessary to avoid breaking the consistency between the steps. Judging whether a change is valid or not is a non-trivial task, as the logical dependency relationships between the modeling elements (predicates) are implicit and complex. In this paper, we propose a method for analyzing the impact of the changes of Event-B. By attaching labels to modeling elements (predicates), the method helps engineers understand how a model is structured and what needs to be modified to accomplish a change.

This paper proposes a computationally efficient offline semi-supervised algorithm that yields a more accurate prediction than the label propagation algorithm, which is commonly used in online graph-based semi-supervised learning (SSL). Our proposed method is an offline method that is intended to assist online graph-based SSL algorithms. The efficacy of the tool in creating new learning algorithms of this type is demonstrated in numerical experiments.

This paper improves our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems by incorporating the beamspace approach. The constant modulus algorithm (CMA), a known blind adaptive array scheme, can fully exploit the degree of freedom (DoF) offered by massive antenna arrays to suppress inter-user interference (IUI) and inter-cell interference (ICI). Unfortunately, CMA wastes a lot of the benefit of DoF for null-steering even when the number of incoming signal is fewer than that of receiving antenna elements. Our new proposal introduces the beamspace method which degenerates the number of array input for CMA from element-space to beamspace. It can control DoF expended for subsequent interference suppression by CMA. Optimizing the array beamforming gain and null-steering ability, can further improve the output signal-to-interference and noise power ratio (SINR). Computer simulation confirmed that our new proposal reduced the required number of data symbols by 34.6%. In addition, the 5th percentile SINR was also improved by 14.3dB.

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%.

This paper evaluates a variety of key 5G technologies such as base station (BS) massive multiple-input multiple-output (MIMO) antennas, beamforming and tracking, intra-baseband unit (BBU) hand over (HO), and coverage. This is done in different interesting 5G areas with a variety of radio conditions such as an indoor office building lobby, an outdoor parking area, and a realistic urban deployment of a 5G radio access system with BSs installed in buildings to deploy a 5G trial area in the Tokyo Odaiba waterfront area. Experimental results show that throughput exceeding 10Gbps is achieved in a 730MHz bandwidth using 8 component carriers, and distributed MIMO throughput gain is achieved in various transmission point deployments in the indoor office building lobby and outdoor parking area using two radio units (RUs). In particular, in the outdoor parking area, a distinct advantage from distributed MIMO is expected and the distributed MIMO gain in throughput of 60% is achieved. The experimental results also clarify the downlink performance in an urban deployment. The experimental results show that throughput exceeding 1.5Gbps is achieved in the area and approximately 200 Mbps is achieved at 500m away from the BS. We also confirm that the beam tracking and intra-BBU HO work well compensating for high path loss at 28-GHz, and achieve coverage 500m from the BS. On the other hand, line of sight (LoS) and non-line-of sight (N-LoS) conditions are critical to 5G performance in the 28-GHz band, and we observe that 5G connections are sometimes dropped behind trees, buildings, and under footbridges.

We present a seven-bit multilayer true-time delay (TTD) circuit operating from 1 to 7GHz for wideband phased array antennas. By stacking advanced substrates with low dielectric loss, the TTD with PCB process is miniaturized and has low insertion loss. The signal vias with surrounding ground vias are designed to provide impedance matching throughout the band, allowing the overall group delay to be flat. The standard deviation of the TTD for all states is below 19ps, which is 1.87% of the maximum group delay. The maximum delay is 1016ps with resolution of 8ps. The implemented TTD is 36.6×19.4mm2 and consumes 0.65mW at 3.3V supply for all the delay states. The measured input/output return loss is better than 12.1dB for the band of 1-7GHz.

In this paper, a smart dressing system was implemented based on flexible pH sensors that can monitor the infection of a wounded area by tracking the pH value of the area. Motivated by the fabrication process widely used for semiconductors, the flexible pH sensor fabrication process was devised with a polyester (PET) film and a Si wafer, which deposits Au and Ag on a PET film. Because the electrodes are comprised of a working electrode and a reference electrode, the reference electrode was fabricated by synthesizing the Polyaniline (PANI) on Ag/AgCl, while the pH sensor has four channels to evenly measure the pH value in a wide area. The smart dressing system was constructed with four pH sensors, a single temperature sensor, a level shifter, a regulator, an analog-to-digital converter (ADC), and a monitoring PC. The measurement results show that our smart dressing system has a size of 5×5cm2 and can monitor the pH value range found in [3,9] with a sensitivity slope of 50mV/pH.

Hadoop, a distributed processing framework for big-data, is now widely used for multimedia processing. However, when processing video data from a Hadoop distributed file system (HDFS), unnecessary network traffic is generated due to an inefficient HDFS block slice policy for picture frames in video files. We propose a new block replication policy to solve this problem and compare the newly proposed HDFS with the original HDFS via extensive experiments. The proposed HDFS reduces network traffic, and increases locality between processing cores and file locations.

Heat map is an important tool for eye tracking data analysis and visualization. It is very intuitive to express the area watched by observer, but ignores saccade information that expresses gaze shift. Based on conventional heat map generation method, this paper presents a novel heat map generation method for eye tracking data. The proposed method introduces a mixed data structure of fixation points and saccades, and considers heat map deformation for saccade type data. The proposed method has advantages on indicating gaze transition direction while visualizing gaze region.

A variety of all-new systems such as a massive machine type communication (mMTC) system will be supported in 5G and beyond. Although each mMTC device occupies quite narrow bandwidth, the massive number of devices expected will generate a vast array of traffic and consume enormous spectrum resources. Therefore, it is necessary to proactively gather up and exploit fractional spectrum resources including guard bands that are secured but unused by the existing Long Term Evolution (LTE) systems. The guard band is originally secured as a margin for high out-of-band emission (OOBE) caused by the discontinuity between successive symbols in the cyclic prefix-based orthogonal frequency division multiplexing (CP-OFDM), and new-waveforms enabling high OOBE suppression have been widely researched to efficiently allocate narrowband communication to the frequency gap. Time-domain windowing is a well-known signal processing technique for reducing OOBE with low complexity and a universal time-domain windowed OFDM (UTW-OFDM) with a long transition duration exceeding the CP length has demonstrated its ability in WLAN-based systems. In this paper, we apply UTW-OFDM to the LTE downlink system and comprehensively evaluate its performance under the channel models defined by 3GPP. Specifically, we evaluate OOBE reduction and block error rate (BLER) by computer simulation and clarify how far OOBE can be reduced without degrading communication quality. Furthermore, we estimate the implementation complexity of the proposed UTW-OFDM, the conventional CP-OFDM, and the universal filtered-OFDM (UF-OFDM) by calculating the number of required multiplications. These evaluation and estimation results demonstrate that the proposed UTW-OFDM is a practical new-waveform applicable to the 5G and beyond.

Dynamic sharing of limited radio spectrum resources is expected to satisfy the increasing demand for spectrum resources in the upcoming 5th generation mobile communication system (5G) era and beyond. Distributed real-time spectrum sensing is a key enabler of dynamic spectrum sharing, but the costs incurred in observed-data transmission are a critical problem, especially when massive numbers of spectrum sensors are deployed. To cope with this issue, the proposed spectrum sensors learn the ambient radio environment in real-time and create a time-spectral model whose parameters are shared with servers operating in the edge-computing layer. This process makes it possible to significantly reduce the communication cost of the sensors because frequent data transmission is no longer needed while enabling the edge servers to keep up on the current status of the radio environment. On the basis of the created time-spectral model, sharable spectrum resources are dynamically harvested and allocated in terms of geospatial, temporal, and frequency-spectral domains when accepting an application for secondary-spectrum use. A web-based prototype spectrum management system has been implemented using ten servers and dozens of sensors. Measured results show that the proposed approach can reduce data traffic between the sensors and servers by 97%, achieving an average data rate of 10 kilobits per second (kbps). In addition, the basic operation flow of the prototype has been verified through a field experiment conducted at a manufacturing facility and a proof-of-concept experiment of dynamic-spectrum sharing using wireless local-area-network equipment.

In compressive sensing theory (CS), the restricted isometry property (RIP) is commonly used for the measurement matrix to guarantee the reliable recovery of sparse signals from linear measurements. Although many works have indicated that random matrices with excellent recovery performance satisfy the RIP with high probability, Toeplitz-structured matrices arise naturally in real scenarios, such as applications of linear time-invariant systems. Thus, the corresponding measurement matrix can be modeled as a Toeplitz (partial) structured matrix instead of a completely random matrix. The structure characteristics introduce coherence and cause the performance degradation of the measurement matrix. To enhance the recovery performance of the Toeplitz structured measurement matrix in multichannel convolution source separation, an efficient construction of measurement matrix is presented, referred to as sparse random block-banded Toeplitz matrix (SRBT). The sparse signal is pre-randomized by locally scrambling its sample locations. Then, the signal is subsampled using the sparse random banded matrix. Finally, the mixing measurements are obtained. Based on the analysis of eigenvalues, the theoretical results indicate that the SRBT matrix satisfies the RIP with high probability. Simulation results show that the SRBT matrix almost matches the recovery performance of random matrices. Compared with the existing banded block Toeplitz matrix, SRBT significantly improves the probability of successful recovery. Additionally, SRBT has the advantages of low storage requirements and fast computation in reconstruction.

Smart-routers develop greatly in recent years as one of the representative products of IoT and Smart home. Different from traditional routers, they have storage and processing capacity. Actually, smart-routers in the same location or ISP have better link conditions and can provide high quality service to each other. Therefore, for the content required services, how to construct the overlay network and efficiently deploy replications of popular content in smart-routers' network are critical. The performance of existing centralized models is limited by the bottleneck of the single point's performance. In order to improve the stability and scalability of the system through the capability of smart-router, we propose a novel intelligent and decentralized content diffusion system in smart-router network. In the system, the content will be quickly and autonomously diffused in the network which follows the specific requirement of coverage rate in neighbors. Furthermore, we design a heuristic node selection algorithm (MIG) and a replacement algorithm (MCL) to assist the diffusion of content. Specifically, system based MIG will select neighbor with the maximum value of information gain to cache the replication. The replication with the least loss of the coverage rate gain will be replaced in the system based on MCL. Through the simulation experiments, at the same requirement of coverage rate, MIG can reduce the number of replications by at least 20.2% compared with other algorithms. Compared with other replacement algorithms, MCL achieves the best successful service rate which means how much ratio of the service can be provided by neighbors. The system based on the MIG and MCL can provide stable service with the lowest bandwidth and storage cost.

A propagation experiment on an actual channel is conducted to confirm the effectiveness of the 1-tap time domain beamforming (TDBF) technique we proposed in previous work. This technique offers simple beamforming for the millimeter waveband massive multiple-input multiple-output (MIMO) applied wireless backhaul and so supports the rapid deployment of fifth generation mobile communications (5G) small cells. This paper details propagation experiments in the 75GHz band and the characteristics evaluations of 1-tap TDBF as determined from actual channel measurements. The results show that 1-tap TDBF array gain nearly equals the frequency domain maximal ratio combining (MRC) value, which is ideal processing; the difference is within 0.5dB. In addition, 1-tap TDBF can improve on the signal-to-interference power ratio (SIR) by about 13% when space division multiplexing (SDM) is performed assuming existing levels of channel estimation error.

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.

In this paper, we consider network monitoring techniques to estimate communication qualities in wide-area mobile networks, where an enormous number of heterogeneous components such as base stations, routers, and servers are deployed. We assume that average delays of neighboring base stations are comparable, most of servers have small delays, and delays at core routers are negligible. Under these assumptions, we propose Heterogeneous Delay Tomography (HDT) to estimate the average delay at each network component from end-to-end round trip times (RTTs) between mobile terminals and servers. HDT employs a crowdsourcing approach to collecting RTTs, where voluntary mobile users report their empirical RTTs to a data collection center. From the collected RTTs, HDT estimates average delays at base stations in the Graph Fourier Transform (GFT) domain and average delays at servers, by means of Compressed Sensing (CS). In the crowdsourcing approach, the performance of HDT may be degraded when the voluntary mobile users are unevenly distributed. To resolve this problem, we further extend HDT by considering the number of voluntary mobile users. With simulation experiments, we evaluate the performance of HDT.

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.