We demonstrate the characterization of a horn antenna in the full F-band (90 ∼ 140 GHz) based on far-field transformation from near-field electro-optic (EO) measurement. Our nonpolarimetric self-heterodyne EO sensing system enables us to simultaneously measure the spatial distribution of the amplitude and phase of the RF signal. Because free-running lasers are used to generate and detect the RF signal, our EO sensing system has wide frequency tunability. Owing to the stable and reliable amplitude and phase measurements with minimal field perturbation, the estimated far-field patterns agree well with those of the simulated results. We have evaluated the estimation errors of the 3-dB beamwidth and position of the first sidelobe. The largest standard error of the measurements was 1.1° for 3-dB beamwidth and 3.5° for the position of first sidelobe at frequency 90 GHz. Our EO sensing system can be used to characterize and evaluate terahertz antennas for indoor communication applications such as small-size slot array antennas.

We investigate a quantization error improvement technique using a dual rail configuration for optical quantization. Our proposed optical quantization uses intensity-to-wavelength conversion based on soliton self-frequency shift and spectral compression based on self-phase modulation. However, some unfavorable input peak power regions exist due to stagnations of wavelength shift or distortions of spectral compression. These phenomena could induce a serious quantization error and degrade the effective number of bit (ENOB). In this work, we propose a quantization error improvement technique which can make up for the unfavorable input peak power regions. We experimentally verify the quantization error improvement effect by the proposed technique in 6 bit optical quantization. The estimated ENOB is improved from 5.35 bit to 5.66 bit. In addition, we examine the XPM influence between counter-propagating pulses at high sampling rate. Experimental results and numerical simulation show that the XPM influence is negligible under ∼40 GS/s conditions.

This paper presents a particle swarm optimization network (PSON) to improve the search capability of PSO. In PSON, multi-PSOs are connected for the purpose of communication. A variety of network topology can be realized by varying the number of connected PSOs of each PSO. The solving performance and convergence speed can be controlled by changing the network topology. Furthermore, high parallelism is can be realized by assigning PSO to single processor. The stability condition analysis and performance of PSON are shown.

Risk-aware Data Replication (RDR), which replicates data at primary sites to nearby safe backup sites, has been proposed to mitigate service disruption in a disaster area even after a widespread disaster that damages a network and a primary site. RDR assigns a safe backup site to a primary site while considering damage risk for both the primary site and the backup candidate site. To minimize the damage risk of all site-pairs the Integer Programing Problem (IPP), which is a mathematical optimization problem, is applied. A challenge for RDR is to choose safe backup sites within a short computation time even for a huge number of sites. As described in this paper, we propose a Discreet method for RDR to surmount this hurdle. The Discreet method first judges the backup sites of a potentially unsafe primary site and avoids assigning a very safe primary site with a very safe backup site. We evaluated the computation time for site-paring and the data availability in the cases of Earthquake and Tsunami using basic disaster simulations. We confirmed that the computation rate of the proposed method is more than 1000 times faster than the existing method when the number of sites is greater than 1000. We also confirmed the data availability of the proposed method; it provides almost equal rates to existing methods of strict optimization. These results mean that the proposed method makes RDR more practical for massively multiple sites.

With recent developments in machine learning technology, the predictions by systems incorporating machine learning can now have a significant impact on the lives and activities of individuals. In some cases, predictions made by machine learning can result unexpectedly in unfair treatments to individuals. For example, if the results are highly dependent on personal attributes, such as gender or ethnicity, hiring decisions might be discriminatory. This paper investigates the neutralization of a probabilistic model with respect to another probabilistic model, referred to as a viewpoint. We present a novel definition of neutrality for probabilistic models, η-neutrality, and introduce a systematic method that uses the maximum likelihood estimation to enforce the neutrality of a prediction model. Our method can be applied to various machine learning algorithms, as demonstrated by η-neutral logistic regression and η-neutral linear regression.

Physical layer security is effective in wireless communications because it makes a transmission secure from the beginning of protocols. We have proposed a chaos multiple-input multiple-output (C-MIMO) transmission scheme that achieves both physical layer security and channel coding gain using chaos signals. C-MIMO is a type of encryption modulation and it obtains the coding gain in conjunction with encryption without a decrease in the transmission efficiency. Thus, the error rate performance is improved in C-MIMO. However, decoding complexity increases exponentially with code length because of the use of maximum likelihood sequence estimation (MLSE), which restricts the code length of C-MIMO and thus the channel coding gain. Therefore, in this paper, we consider outer channel code concatenation instead of code length expansion for C-MIMO, and propose an iterative turbo decoding scheme for performance improvement by introducing a log-likelihood ratio (LLR) into C-MIMO and by utilizing turbo principle. The improved performances of the proposed scheme, compared to the conventional scheme when the outer channel codes are convolutional code and low-density parity check (LDPC) code, are shown by computer simulations.

In this paper, we propose an analytical approach for adaptive decode-and-forward (ADF) relaying schemes consisting of burst data transmission based on pilot symbol assisted-channel estimation (PSA-CE) methods over quasi-static Rayleigh fading channels. At first, we focus on the error-event at relay nodes in which the transmission mode switching is carried out burst by burst, whereas previous studies assumed the transmission mode switching symbol-by-symbol, thus showing lower error rate bound. Under consideration of burst transmission for ADF relay systems, we derive exact error rate expressions which better estimate the performance of actual systems. Then, the average bit and burst error rates are derived in approximated expressions for an arbitrary link signal-to-noise ratio (SNR) related with channel estimation errors. Their accuracy is confirmed by comparison with simulation results. Furthermore, ADF relay systems with PSA-CE schemes are confirmed to select correctly decoded relay nodes without additional signaling between relay nodes and the destination node and it is verified to achieve the performance at a cost of negligible SNR loss.

This paper extends our previously proposed non-orthogonal multiple access (NOMA) scheme to the base station (BS) cooperative multiple-input multiple-output (MIMO) cellular downlink for future radio access. The proposed NOMA scheme employs intra-beam superposition coding of a multiuser signal at the transmitter and the spatial filtering of inter-beam interference followed by the intra-beam successive interference canceller (SIC) at the user terminal receiver. The intra-beam SIC cancels out the inter-user interference within a beam. This configuration achieves reduced overhead for the downlink reference signaling for channel estimation at the user terminal in the case of non-orthogonal user multiplexing and enables the use of the SIC receiver in the MIMO downlink. The transmitter beamforming (precoding) matrix is controlled based on open loop-type random beamforming using a block-diagonalized beamforming matrix, which is very efficient in terms of the amount of feedback information from the user terminal. Simulation results show that the proposed NOMA scheme with block-diagonalized random beamforming in BS cooperative multiuser MIMO and the intra-beam SIC achieves better system-level throughput than orthogonal multiple access (OMA), which is assumed in LTE-Advanced. We also show that BS cooperative operation along with the proposed NOMA further enhances the cell-edge user throughput gain which implies better user fairness and universal connectivity.

We demonstrated that load balancing using actual subscriber extension numbers was practical and effective against traffic congestion after a disaster based on actual data. We investigated the ratios of the same subscriber extension numbers in each prefecture and found that most of them were located almost evenly all over the country without being concentrated in a particular area. The ratio of every number except for the fourth-last digit in the last group of four numbers in a telephone number was used almost equally and located almost evenly all over the country. Tolerance against overload in the last, second-, and third-last single digits stays close to that in the ideal situation if we assume that each session initiation protocol server has a capacity in accordance with the ratio of each number on every single digit in the last group of four numbers in Japan. Although tolerance against overload in double-, triple-, and quadruple-digit numbers does not stay close to that in the ideal situation, it still remains sufficiently high in the case of double- and triple-digit numbers. Although tolerance against overload in the quadruple-digit numbers becomes low, disaster congestion is still not likely to occur in almost half of the area of Japan (23 out of 47 prefectures).

Much research which has shown the usage of social ties could improve the location predictive performance, but as the strength of social ties is varying constantly with time, using the movement data of user's close friends at different times could obtain a better predictive performance. A hybrid Markov location prediction algorithm based on dynamic social ties is presented. The time is divided by the absolute time (week) to mine the long-term changing trend of users' social ties, and then the movements of each week are projected to the workdays and weekends to find the changes of the social circle in different time slices. The segmented friends' movements are compared to the history of the user with our modified cross-sample entropy to discover the individuals who have the relatively high similarity with the user in different time intervals. Finally, the user's historical movement data and his friends' movements at different times which are assigned with the similarity weights are combined to build the hybrid Markov model. The experiments based on a real location-based social network dataset show the hybrid Markov location prediction algorithm could improve 15% predictive accuracy compared with the location prediction algorithms that consider the global strength of social ties.

In this letter, a local pattern coding scheme is proposed to reduce the dimensionality of feature vectors in the local ternary pattern. The proposed method encodes the ternary patterns into a binary pattern by clustering similar ternary patterns. The experimental results show that the proposed method outperforms the previous methods.

Information Centric Networking (ICN) had merits in terms of mobility, security, power consumption and network traffic. When a large-scale disaster occurred, the current communication system might be fragile and the server based network service might be unavailable due to the damages, network congestions, and power failure, etc. In this paper, we proposed an ICN based Disaster Information Sharing Service (DISS) [1], [2] system. DISS could provide robust information sharing service. Users could publish disaster information as a content message with the help of our DISS. In addition, by utilizing DISS's message naming strategy, users could retrieve disaster information even without a server connection. The ICN based DISS could reduce the probability of network congestion when a large number of simultaneous connections occurring. It could provide server-less service in poor network condition. DISS allows users retrieve disaster information from terminals or ICN nodes. During disasters, sharing information timely and effective could protect people from disaster, ensure people's safety.

Ultra high definition (UHD) imaging systems have attracted much attention as a next generation television (TV) broadcasting service and video streaming service. However, the state of the art video coding standards including H.265/HEVC has not enough compression rate for streaming, broadcasting and storing UHD. Existing coding standard such as H.265/HEVC normaly use RGB-YCbCr color transform before compressing RGB color image since that procedure can decorrelate color components well. However, there is room for improvement on the coding efficiency for color image based on an observation that the luminance and chrominance components changes in same locations. This observation inspired us to propose a new post-processing method for compressed images by using weighted least square (WLS) filter with coded luminance component as a guide image, for refining the edges of chrominance components. Since the computational cost of WLS tends to superlinearly increase with increasing image size, it is difficult to apply it to UHD images. To overcome this problem, we propose slightly overlapped block partitioning and a new variant of WLS (constrained WLS, CWLS). Experimental results of objective quality comparison and subjective assessment test using 4K images show that our proposed method can outperform the conventional method and reduce the bit amount for chrominance component drastically with preserving the subjective quality.

The present study proposes a method for estimation of subjective image quality, for combinations of display physical factors, based on the Mahalanobis-Taguchi system in the field of quality engineering. The proposed method estimates subjective image quality by the estimated equation based on the Mahalanobis-Taguchi System and subjective evaluation experiments using the method of successive categories for images of which parameters are combinations of gamma, maximum luminance and minimum luminance. The estimated image quality is in good agreement with the experimental subjective image quality.

Multi-hop networks have been proposed to increase the data transmission rate in wireless mobile networks, and consequently improve the quality of experience of cell-edge users. A successive resource allocation scheme (SAS) has been proposed for a 2-hop virtual cellular network (VCN). In a multi-cell environment, the performance of SAS degrades because of intra-cell and inter-cell interference. In order to alleviate the effect of intra-cell and inter-cell interference and consequently increase the channel capacity of the VCN, this paper proposes the sequential iterative allocation scheme (SIS). Computer simulation results show that, compared to SAS, SIS can improve the fairness, the ergodic, and the outage channel capacity per mobile terminal (MT) of the VCN in a multi-cell environment. This paper also analyzes the performance of the VCN compared to that of the single hop network (SHN) when SIS is applied in a multi-cell environment. Using SIS, VCN can provide higher ergodic channel capacity, and better degree of fairness than SHN in a multi-cell environment. The effect of the number of wireless ports (WPs) in the VCN is also investigated, and the results suggest that adding more WPs per virtual cell in the VCN can enhance the outage channel capacity per MT and the degree of fairness of the VCN.

Compressive sensing (CS)-based channel estimation considerably reduces pilot symbols usage by exploiting the sparsity of the propagation channel in the delay-Doppler domain. In this paper, we consider the application of Bayesian approaches to the sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Taking advantage of the block-sparse structure and statistical properties of time-frequency selective channels, the proposed Bayesian method provides a more efficient and accurate estimation of the channel status information (CSI) than do conventional CS-based methods. Moreover, our estimation scheme is not limited to the Gaussian scenario but is also available for channels that have non-Gaussian priors or unknown probability density functions. This characteristic is notably useful when the prior statistics of channel coefficients cannot be precisely estimated. We also design a combo pilot pattern to improve the performance of the proposed estimation scheme. Simulation results demonstrate that our method performs well at high Doppler frequencies.

Track mis-registration (TMR) is one of the major problems in high-density magnetic recording systems such as bit-patterned media recording (BPMR). In general, TMR results from the misalignment between the center of the read head and that of the main track, which can deteriorate the system performance. Although TMR can be handled by a servo system, this paper proposes a novel method to alleviate the TMR effect, based on the readback signal. Specifically, the readback signal is directly used to estimate a TMR level and is then further processed by the suitable target and equalizer designed for such a TMR level. Simulation results indicate that the proposed method can sufficiently estimate the TMR level and then helps improve the system performance if compared to the conventional receiver that does not employ a TMR mitigation method, especially when an areal density is high and/or a TMR level is large.

The network operations center of a communication carrier play an important and critical role in the early stage of disaster response because its function is the maintenance of communication services, which includes traffic control and restoration of services. This paper describes traffic control and restoration of services affected by the Great East Japan Earthquake. This paper discusses challenges on traffic congestion and restoration for future large-scale disasters.

Directional communications have been considered as a feasible alternative to improve spatial division and throughput in mobile communication environments. In general, directional MAC protocols proposed in the literature rely on channel reservation based on control frames, such as RTS/CTS. Notwithstanding, channel reservation based on control frames increases latency and has an impact on the network throughput. The main contribution of this paper is to propose a channel reservation technique based on pulse/tone signals. The proposed scheme, termed directional pulse/tone channel reservation (DPTCR), allows for efficient channel reservation without resorting to control frames such as RTS and CTS. Theoretical and empirical results show that the proposed scheme has a low probability of failure while providing significant throughput gains. The results show that DPTCR is able to provide throughput improvement up to 158% higher as compared to traditional channel reservation employing RTS/CTS frames.

In this paper, we present a new electro-optic (EO) probing system based on heterodyne detection. The use of a recirculating frequency shifter allows to expand the bandwidth of the system far beyond what is attainable with a conventional heterodyne EO set-up. The performance for the frequencies up to 50GHz is analysed to forecast the viability of the system up to the THz range.