In this letter, a switching detection scheme based on a channel condition number for the MIMO-OFDM system is proposed. The switching algorithm operates by selecting one of three detection schemes of QRD-M, LR-aided MMSE-DFE, and LR-aided MMSE. The switching detection uses the threshold based on the switching algorithm according to the channel condition number. From the simulation results, the proposed detection scheme shows error detection performance and computational complexity in accordance with the threshold for switching detection.

This letter proposes an extended image-source model to simulate the room transfer function for a rotatable complex source in a three-dimensional reverberant room. The proposed model uses spherical harmonic decomposition to describe the exterior sound field from the complex source. Based on “axis flip” concept, the mirroring relations between the source and images are summarized by a unified mirroring operator that occurs on the soundfield coefficients. The rotation movement of the source is taken into account by exploiting the rotation property of spherical harmonics. The accuracy of our proposed model is verified through the appropriate simulation examples.

Network traffic forecasts, as it is well known, can be useful for network resource optimization. In order to minimize the forecast error by maximizing information utilization with low complexity, this paper concerns the difference of traffic trends at large time scales and fits a dual-related model to predict it. First, by analyzing traffic trends based on user behavior, we find both hour-to-hour and day-to-day patterns, which means that models based on either of the single trends are unable to offer precise predictions. Then, a prediction method with the consideration of both daily and hourly traffic patterns, called the dual-related forecasting method, is proposed. Finally, the correlation for traffic data is analyzed based on model parameters. Simulation results demonstrate the proposed model is more effective in reducing forecasting error than other models.

In this letter, we propose a robust and fast tracking framework by combining local and global appearance models to cope with partial occlusion and pose variations. The global appearance model is represented by a correlation filter to efficiently estimate the movement of the target and the local appearance model is represented by local feature points to handle partial occlusion and scale variations. Then global and local appearance models are unified via the Bayesian inference in our tracking framework. We experimentally demonstrate the effectiveness of the proposed method in both terms of accuracy and time complexity, which takes 12ms per frame on average for benchmark datasets.

We previously proposed a lossless image coding scheme using example-based probability modeling, wherein the probability density function of image signals was dynamically modeled pel-by-pel. To appropriately estimate the peak positions of the probability model, several examples, i.e., sets of pels whose neighborhoods are similar to the local texture of the target pel to be encoded, were collected from the already encoded causal area via template matching. This scheme primarily makes use of non-local information in image signals. In this study, we introduce a prediction technique into the probability modeling to offer a better trade-off between the local and non-local information in the image signals.

This paper describes the background noise estimation technique of the tensor product expansion with absolute error (TPE-AE) to estimate multiple sources. The electroencephalogram (EEG) signal produced by the saccadic eye movement is adopted to analyze relationship between a brain function and a human activity. The electrooculogram (EOG) generated by eye movements yields significant problems for the EEG analysis. The denoising of EOG artifacts is important task to perform an accurate analysis. In this paper, the two types of TPE-AE are proposed to estimates EOG and other components in EEG during eye movement. One technique estimates two outer products using median filter based TPE-AE. The another technique uses a reference signal to separate the two sources. We show that the proposed method is effective to estimate and separate two sources in EEG.

Massive MIMO (mMIMO) is a promising technology for smart multimedia and wireless communication fields. In this paper, we investigate pilot allocation problem in two-tier time division duplex (TDD) heterogeneous network (HetNet) with mMIMO. First, we propose a new pilot allocation scheme for maximizing ergodic downlink sum rate of macro users (MUs) and small cell users (SUs), where the uplink pilot overhead and cross-tier interference are jointly considered. Then, we theoretically analyze the formulated problem and propose a low complexity one-dimensional search algorithm to obtain the optimum pilot allocation. In addition, we propose two suboptimal pilot allocation algorithms to simplify the computational process and improve SUs' fairness, respectively. Finally, simulation results show that the performance of the proposed scheme outperforms that of the traditional schemes.

A joint deployment of base stations (BSs) and RGB-depth (RGB-D) cameras for camera-assisted millimeter-wave (mmWave) access networks is discussed in this paper. For the deployment of a wide variety of devices in heterogeneous networks, it is crucial to consider the synergistic effects among the different types of nodes. A synergy between mmWave networks and cameras reduces the power consumption of mmWave BSs through sleep control. A purpose of this work is to optimize the number of nodes of each type, to maximize the average achievable rate within the constraint of a predefined total power budget. A stochastic deployment problem is formulated as a submodular optimization problem, by assuming that the deployment of BSs and cameras forms two independent Poisson point processes. An approximate algorithm is presented to solve the deployment problem, and it is proved that a (1-e-1)/2-approximate solution can be obtained for submodular optimization, using a modified greedy algorithm. The numerical results reveal the deployment conditions under which the average achievable rate of the camera-assisted mmWave system is higher than that of a conventional system that does not employ RGB-D cameras.

In this paper, we propose a method of embedding and detecting data in printed images with several formats, such as different resolutions and numbers of blocks, using the camera of a tablet device. To specify the resolution of an image and the number of blocks, invisible markers that are embedded in the amplitude domain of the discrete Fourier transform of the target image are used. The proposed method can increase the variety of images suitable for data embedding.

In the scenario of finite sample size, the performance of the generalized sidelobe canceller (GSC) is still affected by the desired signal even if all signal sources are independent with each other. Firstly, the novel expression of weight vector of the auxiliary array is derived under the circumstances of finite sample size. Utilizing this new weight vector and considering the correlative interferences, the general expression for the interference cancellation ratio (CR) is developed. Then, the impacts of the CR performance are further analyzed for the parameters including the input signal-to-noise ratio (SNR), the auxiliary array size, the correlation coefficient between the desired signal and interference as well as the snapshots of the sample data, respectively. Some guidelines can thus be given for the practical application. Numerical simulations demonstrate the agreement between the simulation results and the analytical results.

This paper proposes an iterative cancellation technique for adjacent channel interference (ACI), induced by amplifier nonlinearity in millimeter wave (mmW) communication systems. In mmW communications, a large spectrum leak is expected because of the amplifier nonlinearity, and such a spectrum leak disturbs multichannel utilization. In order to mitigate the ACI, iterative interference cancellation in the receiver side is designed in this paper. Typically, iterative interference cancellation is conducted by generating a soft replica of interference from the feedback of the decoder, and subtracting the replica from the received signals. In this case, the canceller must know the amplifier nonlinearity in order to regenerate a soft replica of ACI. In this paper, amplifier nonlinearity is estimated by subjecting the received pilot signals to polynomial regression. We reveal that using only pilot signals in estimating amplifier nonlinearity is insufficient for guaranteeing replica accuracy. To address this issue, the proposed scheme exploits the detected data sequence in the regression analysis. We demonstrate that the proposed ACI cancellation technique can effectively mitigate ACI in multichannel utilization.

We have proposed a fish farm monitoring system for the efficient farming of tuna. In our system, energy efficient and adaptive control of sensor node is highly important. In addition, since a sensor node is attached to the fish, the transmission range of sensor node is not omni-directional. In this paper, we propose a data gathering mechanism for fish farm monitoring by extending a traditional desyncronization mechanism. In our proposed mechanism, by utilizing acknowledgment packets from the sink node, distributed and adaptive timing control of packet transmission is accomplished. In addition, we apply a reassignment mechanism and a sleep mechanism for improving the performance of our proposed mechanism. Through simulation experiments, we show that the performance of our proposed mechanism is higher than that of comparative mechanisms.

Internet of Things (IoT) devices deployed in urban areas are seen as data sources for urban sensing IoT applications. Since installing cellular interfaces on a huge number of IoT devices is expensive, we propose to use a user equipment (UE) device with a local wireless interface as a mobile IoT gateway for fixed IoT devices. In this paper, we design a new mobile architecture based on cellular networks to accommodate non-cellular fixed IoT devices by UE devices working as IoT gateways. One key feature is that our architecture leverages proximity services (ProSe) to discover relay UE devices with low overhead in terms of discovery messages. Through simulation studies, we clarify the feasibility of our architecture including the relay UE discovery mechanism in urban areas.

Recently, non-orthogonal multiple access (NOMA) has gained a great deal of attention due to its ability to simultaneously transmit multiple streams. Device-to-device (D2D) relaying can increase the spectral efficiency via direct communication between two devices, and extends coverage by relaying signals from the base station. In this letter, we propose applying the NOMA technique for D2D relay where D2D relaying and D2D communication can be done simultaneously in the power domain. The proposed scheme can achieve higher spectral efficiency, and its performance is evaluated through extensive simulations in multiple-cell environments, compared with conventional D2D relay schemes.

The heart of Network Functions Virtualization (NFV) is both the softwarization of existing network middleboxes as Virtual Network Functions (VNFs) and the Service Function Chaining (SFC), also known as Service Chaining of them. Most existing VNFs are realized as VM-based general purpose appliances and shared by multiple user VMs. However, the cover range of VNF can be extended to directly reinforce network functionality of user VMs by introducing VM-specific VNFs. In this study, we propose micro-VNFs (µVNFs) and a VM-specific service chaining framework (vNFChain). Micro-VNFs are VM-specific lightweight VNFs that directly attach to a user VM, and can support not only traditional L2-L4 protocols but also stateful custom L7 protocols. The vNFChain framework constructs local service chains of µVNFs and transparently attaches the chain to the VM. Importantly, our framework achieves zero touch configuration for user VMs as well as no modification for existing system environments, such as virtual switch, hypervisor, and OS. In this paper, we describe architectural design and implementation of the framework. In addition, we evaluate the proposed approach in terms of throughput and CPU usage by comparing it with a DPDK-enabled VM-based µVNF model.

Mobility management is very important in mobile cellular networks, since to connect incoming calls, the network must maintain the locations of the mobiles. This study considers the zone-based registration methods that most mobile cellular networks have adopted. We focus on two special zone-based registration methods, called two-zone registration (2Z), and two-zone registration with implicit registration by outgoing calls (2Zi). Although some mathematical models for their performances have been presented, they still cannot accurately estimate 2Zi performance. We provide a new and simple mathematical model based on Markov chain theory that can accurately analyze the performances of 2Z and 2Zi. We also explain the propositions underlying the explicit expressions adopted by our model. We finally present various numerical results, to compare the performance of 2Zi with those of 2Z and one-zone registration (1Z), and show that in every case, 2Zi is superior to 2Z, and in most practical cases, to 1Z.

In this paper, we propose a relaying strategy for single-carrier relay networks with frequency selective channels, where each relay node delays its received signal before amplify-and-forward processing it. We propose a computationally efficient delay design method which reduces the number of delay candidates. To further reduce computational complexity, we develop a simplified delay design method which reduces the number of weight computations. Also, we extend the design method to the case where only partial channel state information of relay-to-destination channels is available. Simulation results show that the proposed relaying strategy outperforms a conventional amplify-and-forward relaying strategy and achieves the performance close to that of a more complex filter-and-forward relaying strategy. It is also shown that the proposed delay design method achieves near-optimum performance.

This paper reports on the relationships between the performance of retro-reflectors and the sharpness of an aerial image formed with aerial imaging by retro-reflection (AIRR). We have measured the retro-reflector divergence angle and evaluated aerial image sharpness by use of the contrast-transfer function. It is found that the divergence angle of the retro-reflected light is strongly related to the sharpness of the aerial image formed with AIRR.

This study involves proposing a high-speed computer-generated hologram playback by using a digital micromirror device for high-definition spatiotemporal division multiplexing electroholography. Consequently, the results indicated that the study successfully reconstructed a high-definition 3-D movie of 3-D objects that was comprised of approximately 900,000 points at 60 fps when each frame was divided into twelve parts.

This paper aims to support quick and easy page access in digital documents. We tried to use a paper book as a device to navigate pages for digital documents. Our proposed system allows the users to perform the same interaction as a paper book such as inserting fingers among pages or folding an edge of the page as a dog-ear. Three experiments were conducted to confirm the effectiveness of the proposed system. As a result, we confirmed our proposed system was superior to conventional navigation methods especially in moving back and forth among pages.