Femtocell has been considered as a key promising technology to improve the capacity of a cellular system. However, the femtocells deployed inside a macrocell coverage are potentially suffered from excessive interference. This paper proposes a novel radio resource optimization in closed access femtocell networks based on bat algorithm. Bat algorithm is inspired by the behavior of bats in their echolocation process. While the original bat algorithm is designed to solve the complex optimization problem in continuous search space, the proposed modified bat algorithm extends the search optimization in a discrete search space which is suitable for radio resource allocation problem. The simulation results verify the convergence of the proposed optimization scheme to the global optimal solution and reveal that the proposed scheme based on modified bat algorithm facilitates the improvement of the femtocell network capacity.

To minimize the damage caused by landslides resulting from torrential rain, residents must quickly evacuate to a place of refuge. To make the decision to evacuate, residents must be able to collect and share disaster information. Firstly, this paper introduces the Grass-roots Information Distribution System and a fixed type monitoring system which our research group has been developing. The fixed type monitoring system is deployed at the location of apparent danger, whereas the Grass-roots Information Distribution System distributes disaster information acquired from the fixed type monitoring system through a mobile ad hoc network (MANET) to residents. The MANET is configured using mobile terminals of residents. Next, in this paper, an information dissemination scheme utilizing a MANET and cellular networks to communicate among mobile terminals is proposed and simulated in the area where our research group has been deploying the distribution system. The MANET topology and information distribution obtained from the simulation results for further field experiments are then discussed.

The methods proposed in this paper enable resynchronization when a synchronization deviation occurs in a sensor node without a beacon or an ack in a wireless sensor network under ultra-limited but stable resources such as the energy generated from tiny solar cell batteries. The method for a single-hop network is straightforward; when a receiver does not receive data, it is simply placed in recovery mode, in which the receiver sets its cycle length T_B to (b±γ)T, where b is non-negative integer, 0 < γ < 1, and T is its cycle length in normal mode, and in which the receiver sets its active interval W_B to a value that satisfies W_B ≥ W + γT, where W is its active interval in normal mode. In contrast, a sender stays in normal mode. Resynchronization methods for linear multi-hop and tree-based multi-hop sensor networks are constructed using the method for a single-hop network. All the methods proposed here are complete because they are always able to resynchronize networks. The results of simulations based on the resynchronization methods are given and those of an experiment using actual sensor nodes with wireless modules are also presented, which show that the methods are feasible.

Most wireless networks are specified as using the data link protocol, i.e. layer 2 (L2). Recently, IoT and big data processing have promoted the use of wireless sensor networks to connect and send data to data center applications over the Internet. To do so, the implementation of an IP stack on the wireless node, or the gateway of the IP and wireless L2 network, has been proposed. Both approaches were developed to allow applications on the IP network to access L2 wireless network nodes. However, since wireless sensor networks do not require any network protocol, an IP is not essential for collecting data. Therefore, we propose a novel bridging VPN for connecting wireless networks, in which the application and wireless end nodes are not required to acknowledge an IP address or network protocol. In this way, the IP network merely serves to transport the data link frames of wireless networks. We believe that this is another style of IoT and recommend that this VPN be used as a test bed for small IoT businesses and institutions before they start to implement an IP stack on their systems.

The IEEE 802.11p Enhanced Distributed Channel Access (EDCA) is a standardization for vehicle-to-vehicle and road-to-vehicle communications. The saturated throughputs of the IEEE 802.11p EDCA obtained from previous analytical expressions differ from those of simulations. The purpose of this paper is to explain the reason why the differences appear in the previous analytical model of the EDCA. It is clarified that there is a special state wherein the Backoff Timer (BT) is decremented in the first time slot of after a frame transmission, which cannot be expressed in the previous Markov model. In addition, this paper proposes modified Markov models, which allow the IEEE 802.11p EDCA to be correctly analyzed. The proposed models describe BT-decrement procedure in the first time slot accurately by adding new states to the previous model. As a result, the proposed models provide accurate transmission probabilities of network nodes. The validity of the proposed models is confirmed by the quantitative agreements between analytical predictions and simulation results.

The arrival of the era of the Internet of Things (IoT) has ensured the ubiquity of human-sensing technologies. Cameras have become inexpensive instruments for human sensing and have been increasingly used for this purpose. Because cameras produce large quantities of information, they are powerful tools for sensing; however, because camera images contain information allowing individuals to be personally identified, their use poses risks of personal privacy violations. In addition, because IoT-ready home appliances are connected to the Internet, camera-captured images of individual users may be unintentionally leaked. In developing our human-detection method [33], [34], we proposed techniques for detecting humans from unclear images in which individuals cannot be identified; however, a drawback of this method was its inability to detect moving humans. Thus, to enable tracking of humans even through the images are blurred to protect privacy, we introduce a particle-filter framework and propose a human-tracking method based on motion detection and heart-rate detection. We also show how the use of integral images [32] can accelerate the execution of our algorithms. In performance tests involving unclear images, the proposed method yields results superior to those obtained with the existing mean-shift method or with a face-detection method based on Haar-like features. We confirm the acceleration afforded by the use of integral images and show that the speed of our method is sufficient to enable real-time operation. Moreover, we demonstrate that the proposed method allows successful tracking even in cases where the posture of the individual changes, such as when the person lies down, a situation that arises in real-world usage environments. We discuss the reasons behind the superior behavior of our method in performance tests compared to those of other methods.

Chipless RFID tags that use the higher-mode resonances of a transmission line resonator are presented in this paper. We have proposed multimode stepped impedance resonators (SIRs) for this application and reported the fundamental characteristics of an experimental system composed of multimode SIRs with open-circuited ends and a near-field electromagnetic detector using capacitive coupling (electric field) probes for the detector. To improve the frequency response and widen the detection range, we introduced multimode SIRs with short-circuited ends and inductive coupling (magnetic field) probes and measured their properties. To reduce the size of the tag and reader, we examined the frequency responses and found that the optimal configuration consisted of C-shaped tags and detector probes with a spatially orthogonal arrangement. The experimental tag system showed good frequency responses, detection range, and frequency detection accuracy. In particular, the spacing between the tag resonator and the transmission line of the probe, which corresponds to the detection distance, was 5mm or more, and was at least 10 times greater than that of previously reported RFID tag systems using near-field electromagnetic coupling.

This paper focuses on on-demand wireless sensor networks (WSNs) where a wake-up receiver is installed into each node. In on-demand WSNs, each node sends a wake-up signal including a wake-up ID assigned to a specific destination node in order to remotely activate its main radio interface. This wake-up control helps each node to reduce energy consumed during idle periods, however, the wake-up signal transmitted before every data transmission results in overhead, which degrades communication quality and increases energy consumption at each sender node. In order to reduce the overhead for wake-up control, in this paper, we propose three schemes. First, we propose a scheme called Double Modulation (DM), where each node embeds the sensing data to be transmitted into the payload field of a wake-up signal. The destination interprets the wake-up message differently depending on its wake-up state: if it is in a sleep state, it treats the message as a wake-up signal, otherwise it extracts the sensing data from the detected message. Second, we propose a scheme called Overhearing (OH), where each node observes the frames transmitted by a destination node and suppresses the transmission of wake-up signal when detecting the active state of their destination. Finally, we propose a hybrid scheme that combines OH and DM schemes. Our simulation results show that the proposed schemes can effectively reduce the negative impact of wake-up overhead, and significantly improve data collection rate and energy-efficiency in comparison to on-demand WSN without the proposed schemes.

To recognize transportation modes without any additional sensor devices, we demonstrate that the transportation modes can be recognized from communication quality factors. In the demonstration, instead of using global positioning system (GPS) and accelerometer sensors, we collect mobile TCP throughputs, received-signal strength indicators (RSSIs), and cellular base-station IDs (Cell IDs) through in-line network measurement when the user enjoys mobile services, such as video streaming. In accuracy evaluations, we conduct two different field experiments to collect the data in six typical transportation modes (static, walking, riding a bicycle, riding a bus, riding a train and riding a subway), and then construct the classifiers by applying a support-vector machine (SVM), k-nearest neighbor (k-NN), random forest (RF), and convolutional neural network (CNN). Our results show that these transportation modes can be recognized with high accuracy by using communication quality factors as well as the use of accelerometer sensors.

Recent works on enhancing the comfort and convenience of vehicles have revealed the advantage of various wireless sensor nodes for information collection. For the highly required reliability in vehicles, Reliable Wireless Communication based on Substitute Forwarding (RWCSF) has been proposed. It ensures that 99.999% of communications can finish within 20ms, which is the quality of communication equivalent to wired links. However, the performance was evaluated in very limited situations, where two or more communications never occurred simultaneously and no noise was present. In this paper, we enhance RWCSF to achieve the target communication quality even if two or more communications occur simultaneously. In addition, we evaluate the enhanced method in various types of vehicles that create internal noise.

Biometric authentication, namely using biometric features for authentication is gaining popularity in recent years as further modalities, such as fingerprint, iris, face, voice, gait, and others are exploited. We explore the effectiveness of three simple Electroencephalography (EEG) related biometric authentication tasks, namely resting, thinking about a picture, and moving a single finger. We present details of the data processing steps we exploit for authentication, including extracting features from the frequency power spectrum and MFCC, and training a multilayer perceptron classifier for authentication. For evaluation purposes, we record an EEG dataset of 27 test subjects. We use three setups, baseline, task-agnostic, and task-specific, to investigate whether person-specific features can be detected across different tasks for authentication. We further evaluate, whether different tasks can be distinguished. Our results suggest that tasks are distinguishable, as well as that our authentication approach can work both exploiting features from a specific, fixed, task as well as using features across different tasks.

Cooperative communication can reduce energy consumption effectively due to its superior diversity gain. To further prolong network lifetime and improve the energy efficiency, this paper studies energy-efficient packet transmission in wireless ad-hoc networks and proposes a novel cluster-based cooperative packet transmission (CCPT) protocol to mitigate the packet loss and balance the energy consumption of networks. The proposed CCPT protocol first constructs a highly energy-efficient initial routing path based on the required energy cost of non-cooperative transmission. Then an iterative cluster recruitment algorithm is proposed that selects cooperative nodes and organizing them into clusters, which can create transmit diversity in each hop of communication. Finally, a novel two-step cluster-to-cluster cooperative transmission scheme is designed, where all cluster members cooperatively forward the packet to the next-hop cluster. Simulation results show that the CCPT protocol effectively reduces the energy cost and prolongs the network lifetime compared with the previous CwR and noC schemes. The results also have shown that the proposed CCPT protocol outperforms the traditional CwR protocol in terms of transmit efficiency per energy, which indicates that CCPT protocol has achieved a better trade-off between energy and packet arrival ratio.

In this paper, a scramble phase assisting weighted-type fractional Fourier transform (SPA-WFRFT) based system is proposed to guarantee the communication's security. The original transmitting signal is divided into two parts. The first part is modulated by WFRFT and subsequently makes up the constellation beguiling. The other part is used to generate the scramble phase and also to assist in the encryption of the WFRFT modulated signal dynamically. The novel constellation optimal model is built and solved through the genetic algorithm (GA) for the constellation beguiling. And the double pseudo scheme is implemented for the scramble phase generation. Theoretical analyses show that excellent security performances and high spectral efficiency can be attained. Final simulations are carried out to evaluate the performances of the SPA-WFRFT based system, and demonstrate that the proposed system can effectively degrade the unauthorized receivers' bit error rate (BER) performance while maintaining its own communication quality.

In this paper, we propose a CTRIL (Common Trend and Regression with Independent Loss) model to infer latent traffic demand in overloaded links as well as how much it is reduced due to QoS (Quality of Service) degradation. To appropriately provision link bandwidth for such overloaded links, we need to infer how much traffic will increase without QoS degradation. Because original latent traffic demand cannot be observed, we propose a method that compares the other traffic time series of an underloaded link, and by assuming that the latent traffic demands in both overloaded and underloaded are common, and actualized traffic demand in the overloaded link is decreased from common pattern due to the effect of QoS degradation. To realize the method, we developed a CTRIL model on the basis of a state-space model where observed traffic is generated from a latent trend but is decreased by the QoS degradation. By applying the CTRIL model to actual HTTP (Hypertext transfer protocol) traffic and QoS time series data, we reveal that 1% packet loss decreases traffic demand by 12.3%, and the estimated latent traffic demand is larger than the observed one by 23.0%.

Spectral graph theory, based on the adjacency matrix or the Laplacian matrix that represents the network topology and link weights, provides a useful approach for analyzing network structure. However, in large scale and complex social networks, since it is difficult to completely know the network topology and link weights, we cannot determine the components of these matrices directly. To solve this problem, we propose a method for indirectly determining the Laplacian matrix by estimating its eigenvalues and eigenvectors using the resonance of oscillation dynamics on networks.

The influence of pump phase error on phase-sensitive optical amplifier (PSA) repeaters and the waveform degradation due to chromatic dispersion and fiber nonlinearities in the optical multi-relay transmission of quadrature phase-shift keying phase-conjugated twin waves are considered theoretically. First, the influence of noise from the pump phase error, optical local oscillator, receiver, and the amplified spontaneous-emission (ASE) in PSA repeaters is investigated with the assumption that transmission fibers are linear lossy channels. The bit-error rate (BER) is estimated as a function of the signal-to-noise ratio, and the relationship between the number of transmission relays and the fiber launch power is clarified. Waveform degradation due to chromatic dispersion and the optical fiber nonlinearities in transmission fibers are investigated with the noiseless condition, and the maximum repeatable number as a function of the fiber launch power is calculated. Finally, we show the relationship among the maximum repeatable number, standard deviation of pump phase error in PSA repeaters, and the fiber launch power to clarify the optimum transmission condition with consideration of the noise and the waveform degradation.

In super-Nyquist wavelength division multiplexed systems, performance of forward error correction (FEC) can be improved by an iterative decoder between a maximum likelihood decoder for polybinary shaping and an FEC decoder. The typical iterative decoder includes not only the iteration between the first and second decoders but also the internal iteration within the FEC decoder. Such two-fold loop configuration would increase the computational complexity for decoding. In this paper, we propose the simplified iterative decoder, where the internal iteration in the FEC decoder is not performed, reducing the computational complexity. We numerically evaluate the bit-error rate performance of polybinary-shaped QPSK signals in the simplified iterative decoder. The numerical results show that the FEC performance can be improved in the simplified scheme, compared with the typical iterative decoder. In addition, the performance of the simplified iterative decoder has been investigated by the extrinsic information transfer (EXIT) chart.

In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.

The recent widespread use of high-performance terminals has resulted in a rapid increase in mobile data traffic. Therefore, public wireless local area networks (WLANs) are being used often to supplement the cellular networks. Capacity improvement through the dense deployment of access points (APs) is being considered. However, the effective throughput degrades significantly when many users connect to a single AP. In this paper, users are classified into guaranteed bit rate (GBR) users and best effort (BE) users, and we propose a network model to provide those services. In the proposed model, physical APs and the bandwidths are assigned to each service class dynamically using a virtual AP configuration and a virtualized backhaul network, for reducing the call-blocking probability of GBR users and improving the satisfaction degree of BE users. Finally, we evaluate the performance of the proposed model through simulation experiments and discuss its feasibility.

In this paper, we first evaluate Breadcrumbs in wireless multi-hop networks and reveal that they brings throughput improvement of not only popular content but also less popular content. Breadcrumbs can distribute popular content traffic towards edges of a wireless network, which enables low-popularity content to be downloaded from the gateway node. We also propose a new caching decision, called receiver caching. In receiver caching, only the receiver node caches the transmitted content. Our simulation results show that receiver caching prevents frequent replacement of cached content, which reduces invalid Breadcrumbs trails to be remained. And they also show that receiver caching significantly improves the total throughput performance of Breadcrumbs.

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.

In this paper, a parallel flow monitoring technique that achieves accurate measurement of end-to-end delay of networks is proposed. In network monitoring tasks, network researchers and practitioners usually monitor multiple probe flows to measure delays on multiple paths in parallel. However, when they measure an end-to-end delay on a path, information of flows except for the flow along the path is not utilized in the conventional method. Generally, paths of flows share common parts in parallel monitoring. In the proposed method, information of flows on paths that share common parts, utilizes to measure delay on a path by partially converting the observation results of a flow to those of another flow. We perform simulations to confirm that the observation results of 72 parallel flows of active measurement are appropriately converted between each other. When the 99th-percentile of the end-to-end delay for each flow are measured, the accuracy of the proposed method is doubled compared with the conventional method.

This paper presents a numerical study of the wireless channel characteristics of liver implants in a frequency range of 4.5-6.5GHz, considering different digital human phantoms by employing two inhomogeneous male and female models. Path loss data for in-body to on-body and in-body to off-body communication scenarios are provided. The influence of respiration-induced organ movement on signal attenuation is demonstrated. A narrower range of attenuation deviation is observed in the female model as compared to the male model. The path loss data in the female body is between 40-80dB which is around 5-10dB lower than the male model. Path loss data for the in-body to off-body scenario in both models suggest that in-body propagation is the main component of total path loss in the channel. The results demonstrate that channel characteristics are subject dependent, and thus indicate the need to take subject dependencies into consideration when investigating in-body communication channels.

This paper proposes a low-profile unidirectional supergain antenna applicable to wireless communication devices such as mobile terminals, the Internet of Things and so on. The antennas used for such systems are required to be not only electrically low-profile but also unsusceptible to surrounding objects such as human body and/or electrical equipment. The proposed antenna achieves both requirements due to its supergain property using planar elements and a closely placed planar reflector. The primary antenna is an asymmetric dipole type, and consists of a monopole element mounted on an edge of a rectangular conducting plane. Both elements are placed on a dielectric substrate backed by the planar reflector. It is numerically and experimentally shown that the supergain property is achieved by optimizing the geometrical parameters of the antenna. It is also shown that the impedance characteristics can be successfully adjusted by changing the lengths of the ground plane element and the monopole element. Thus, no additional impedance matching circuit is necessary. Furthermore, it is shown that surrounding objects have insignificant impact on the antenna performance.

A novel algorithm is proposed for estimating the direction of arrival (DOA) of linear frequency modulated (LFM) signals for the uniform circular array (UCA). Firstly, the UCA is transformed into an equivalent virtual uniform linear array (ULA) using the mode-space algorithm. Then, the short time Fourier transform (STFT) of each element's output is worked out. We can obtain the spatial time-frequency distribution matrix of the virtual ULA by selecting the single-source time-frequency (t-f) points in the t-f plane and then get the signal subspace of the array. The characteristics nature of the Bessel function allow us to obtain the multiple invariance (MI) of the virtual ULA. So the multiple rotational invariant equation of the array can be obtained and its closed-form solution can be worked out using the multi-least-squares (MLS) criterion. Finally, the two dimensional (2-D) DOA estimation of LFM signals for UCA can be obtained. Numerical simulation results illustrate that the UCA-STFT-MI-ESPRIT algorithm proposed in this paper can improve the estimation precision greatly compared with the traditional ESPRIT-like algorithms and has much lower computational complexity than the MUSIC-like algorithms.

This paper analyzes the performance of single-cell massive multiple-input multiple-output (MIMO) systems with non-orthogonal pilots. Specifically, closed-form expressions of the normalized channel estimation error and achievable uplink capacity are derived for both least squares (LS) and minimum mean square error (MMSE) estimation. Then a pilot reconstruction scheme based on orthogonal Procrustes principle (OPP) is provided to reduce the total normalized mean square error (NMSE) of channel estimations. With these reconstructed pilots, a two-step pilot assignment method is formulated by considering the correlation coefficient among pilots to reduce the maximum NMSE. Based on this assignment method, a step-by-step pilot power allocation scheme is further proposed to improve the average uplink signal-to-interference and noise ratio (SINR). At last, simulation results demonstrate the superiority of the proposed approaches.

Massive multiple-input multiple-output (MIMO) realizes simultaneous transmission to a large number of mobile stations (MSs) and improves frequency utilization efficiency. It is drawing attention as the key technology of the fifth-generation (5G) mobile communication systems. The 5G system is going to be implemented in a high frequency band and massive MIMO beamforming (BF) is applied to compensate propagation loss. In the conventional BF scheme, a transmit beam is selected based on the power of received signals over subcarriers. The signal on a different subcarrier is transmitted with a different directivity. To improve the accuracy of beam selection, this paper proposes a transmit beam selection scheme for massive MIMO. The proposed scheme calculates the expected responses of the signals over the subcarriers based on the relative directivity between a base station (BS) and a MS. The MS calculates the correlation between the received signals and each of the expected response sequences. It then selects the beam with the highest correlation value. It is shown in this paper that the proposed scheme can improve the average signal-to-noise ratio of a received signal by about 1.5dB as compared with that of the power based search scheme. It is also shown that the proposed scheme with limited response coefficients can reduce the computational complexity by a factor of 1/100 while it still increases the average SNR by about 1.0dB.

Index modulation (IM) is receiving attention because of its high energy efficiency. In precoding index modulation (PIM), some of the data bits are used for the modulation of symbols and the rest are used for the selection of precoding coefficients. In conventional PIM, the precoding matrices are orthogonal and unitary. In the proposed PIM, the number of the columns of the precoding matrix is expanded more than that of the rows. Because of the expanded precoding matrices, the number of data bits used for the selection of precoding coefficients is increased. As a result, a code rate can be reduced compared to that of the conventional PIM and the number of candidate constellation points for demodulation can be decreased as compared to that of a multiple-input multiple-output MIMO system under the same throughput. Numerical results obtained through computer simulation show that the proposed PIM with QPSK symbols improves the performance by about 2.5dB at a bit error rate of 10^-3 as compared to overloaded MIMO with 16QAM symbols for two transmit antennas and one receive antenna. It also achieves about 3.5dB better performance than the conventional PIM under the same antenna condition. Furthermore, the optimum number of index modulation bits is found by the simulation for the proposed PIM. In addition, the PIM scheme reduces demodulation complexity by a factor of 32 as compared to that of the MIMO under specific modulation parameters.

In this paper, we propose a periodic reactance time function for 2-element electronically steerable passive array radiator (ESPAR) antennas applicable to the receivers of both single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) systems with 2 outputs. Based on the proposed function, we evaluate the power patterns of the antenna for various distances between two antenna elements. Moreover, for the distances, we discuss the correlation properties and the strength of the two outputs to find the appropriate distance for the receiver. From the discussions, we can conclude that distances from 0.1 to 0.35 times the wavelength are effective in terms of receive diversity.

For Advanced Television Systems Committee (ATSC) digital terrestrial broadcasting systems, a transmitter identification (TxID) technique is introduced to analyze interference among broadcasting transmitters in single frequency networks (SFN). Based on the TxID analysis results, the transmit power and emission time delay of each broadcasting transmitter can be adjusted to minimize the effects of co- and adjacent- channel interference. For this reason, TxID has been recognized as an important feature in SFN configurations for ATSC 1.0 and 3.0 standards. Recently, there has been increasing interest in employing TxID for data transmission. This paper proposes a TxID based data transmission method for use with ATSC 1.0 and 3.0 standards. The major advantage of this data transmission method is its robustness while maintaining TxID properties. Simulations and laboratory tests demonstrate that the proposed technique can achieve a robust data transmission with backward compatibility to legacy ATSC 1.0 and 3.0 receivers.

All digital phased arrays generate multiple beams concurrently through the digital beam forming technique, which features digital processing with multiple identical receiving/transmitting channels in RF or microwave frequencies. However, the performance of this process strongly depends on accurately matching the amplitude and phase of the channels, as mismatching is likely to degrade radar performance. In this paper, we present a method to calibrate receiving array by using NCO phase increasing algorithm, which simplifies array system by removing the external far-field calibration signals often needed in array systems. Both analysis and simulation results suggest that the proposed method attains better calibration performance than existing approaches, even with a low SNR input signal. Experiments also varify that the proposed calibration method is effective and achieves a desired radiation pattern. We can further boost calibration accuracy and reduce calibration time by programming NCO phase width and NCO phase resolution.