Delay Tolerant Networks (DTNs) are vulnerable to message flooding attacks in which a very large number of malicious messages are sent so that network resources are depleted. To address this problem, previous studies mainly focused on constraining the number of messages that nodes can generate per time slot by allowing nodes to monitor the other nodes' communication history. Since the adversaries may hide their attacks by claiming a false history, nodes exchange their communication histories and detect an attacker who has presented an inconsistent communication history. However, this approach increases node energy consumption since the number of communication histories increases every time a node communicates with another node. To deal with this problem, in this paper, we propose an energy-efficient defense against such message flooding attacks. The main idea of the proposed scheme is to time limit the communication history exchange so as to reduce the volume while ensuring the effective detection of inconsistencies. The advantage of this approach is that, by removing communication histories after they have revealed such inconsistencies, the energy consumption is reduced. To estimate such expiration time, analytical expressions based upon a Markov chain based message propagation model, are derived for the probability that a communication history reveals such inconsistency in an arbitrary time. Extensive performance evaluation results obtained by means of computer simulations and several performance criteria verify that the proposed scheme successfully improves the overall energy efficiency. For example, these performance results have shown that, as compared to other previously known defenses against message flooding attacks, the proposed scheme extends by at least 22% the battery lifetime of DTN nodes, while maintaining the same levels of protection.

An optical-layer adaptive restoration scheme is validated by a real-time experiment and numerical analyses. In this paper, it is assumed that this scheme can adaptively optimize the bitrate (up to 600Gb/s) and an optical reach with 100Gb/s granularity to maintain high-capacity optical signal transmission. The practicality of 600-Gb/s/carrier optical signal transmission over 101.6-km field-installed fiber is confirmed prior to the adaptive restoration experiment. After modifying the field setup, a real-time experiment on network recovery is demonstrated with bitrate adaptation for 600-Gb/s to 400-Gb/s signals. The results indicate that this scheme can restore failed connections with recovery times comparable to those of conventional restoration scheme; thus 99.9999% system availability can be easily attained even under double-link failures. Numerical analysis clarifies that adaptive restoration can recover >80% of double-link failures on several realistic topologies and improvement amount against conventional scheme is semi-statistically characterized by restoration path length.

Inter-channel crosstalk is one of the limiting factors in multichannel optical systems. This paper presents a theoretical analysis of the bit-error-rate (BER) performance of quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) signals influenced by multiple crosstalk channels. The field distribution of multiple crosstalk channels in the constellation map is calculated. The BER of the QPSK/QAM signal, onto which the crosstalk light is superimposed, is then evaluated for a varying number of crosstalk channels under the condition that the total crosstalk power is constant. The results quantitatively confirm that as the channel number increases, the BER degradation caused by crosstalk light approaches that caused by Gaussian noise light. It is also confirmed that the degradations caused by crosstalk light and Gaussian light are similar for QAM signals of high-level modulation.

This paper proposes an optimization model under uncertain traffic demands to design the backup network to minimize the total capacity of a backup network to protect the primary network from multiple link failures, where the probability of link failure is specified. The hose uncertainty is adopted to express uncertain traffic demands. The probabilistic survivability guarantee is provided by determining both primary and backup network routing, simultaneously. Robust optimization is introduced to provide probabilistic survivability guarantees for different link capacities in the primary network model under the hose uncertainty. Robust optimization in the proposed model handles two uncertain items: uncertain failed primary link with different capacities and uncertain traffic demands. We formulate an optimization problem for the proposed model. Since it is difficult to directly solve it, we introduce a heuristic approach for the proposed model. By using the heuristic approach, we investigate how the probability of link failure affects both primary and backup network routing. Numerical results show that the proposed model yields a backup network with lower total capacity requirements than the conventional model for the link failure probabilities examined in this paper. The results indicate that the proposed model reduces the total capacity of the backup network compared to the conventional model under the hose uncertainty. The proposed model shares more effectively the backup resources to protect primary links by determining routing in both primary and backup networks.

In this paper, we advocate applying the concept of content-based wake-up to distributed estimation in wireless sensor networks employing wake-up receivers. With distributed estimation, where sensing data of multiple nodes are used for estimating a target observation, the energy consumption can be reduced by ensuring that only a subset of nodes in the network transmit their data, such that the collected data can guarantee the required estimation accuracy. In this case, a sink needs to selectively wake up those sensor nodes whose data can contribute to the improvement of estimation accuracy. In this paper, we propose wake-up signaling called estimative sampling (ES) that can selectively activate the desired nodes by using content-based wake-up control. The ES method includes a mechanism that dynamically searches for the desired nodes over a distribution of sensing data. With numerical results obtained by computer simulations, we show that the distributed estimation with ES method achieves lower energy consumption than conventional identity-based wake-up while satisfying the required accuracy. We also show that the proposed dynamic mechanism finely controls the trade-off between delay and energy consumption to complete the distributed estimation.

This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.

Channel modeling is a vital step in designing transceivers for wireless implant communication systems due to the extremely challenging environment of the human body. In this paper, the in-to-on body path loss and group delay were first analyzed using an electric dipole and a current loop in the 10-60MHz human body communication band. A path loss model was derived using finite difference time domain (FDTD) simulation and an anatomical human body model. As a result, it was found that the path loss increases with distance in an exponent of 5.6 for dipole and 3.9 for loop, and the group delay variation is within 1ns for both dipole and loop which suggests a flat phase response. Moreover, the electric and magnetic field distributions revealed that the magnetic field components dominate in-body signal transmission in this frequency band. Based on the analysis results of the implant channel, the link budget was analyzed. An experiment on a prototype transceiver was also performed to validate the path loss model and bit error rate (BER) performance. The experimentally derived path loss exponent was between the electric dipole path loss exponent and the current loop path loss exponent, and the BER measurement showed the feasibility of 20Mbps implant communication up to a body depth of at least 15cm.

In this paper, mixed Gibbs sampling multiple-input multiple-output (MIMO) detection with forcible search is proposed. In conventional Gibbs sampling MIMO detection, the problem of stalling occurs under high signal-to-noise ratios (SNRs) which degrades the detection performance. Mixed Gibbs sampling (MGS) is one solution to this problem. In MGS, random sampling is carried out with a constant probability regardless of whether a current search falls into a local minimum. In the proposed scheme, combined with MGS, multiple candidate symbols are forcibly changed when the search is captured by a local minimum. The search restarts away from the local minimum which effectively enlarges the search area in the solution space. Numerical results obtained through computer simulation show that the proposed scheme achieves better performance in a large scale MIMO system with QPSK signals.

In this paper, user scheduling with beam selection for full-digital massive multi-input multi-output (MIMO) is proposed. Inter-user interference (IUI) can be canceled by precoding such as zero-forcing at a massive MIMO base station if ideal hardware implementation is assumed. However, owing to the non-ideal characteristics of hardware components, IUI occurs among multiple user terminals allocated on the same resource. Thus, in the proposed scheme, the directions of beams for allocated user terminals are adjusted to maximize the total user throughput. User allocation based on the user throughput after the adjustment of beam directivity is then carried out. Numerical results obtained through computer simulation show that when the number of user terminals in the cell is two and the number of user terminals allocated to one resource block (RB) is two, the throughput per subcarrier per subframe improves by about 3.0 bits. On the other hand, the fairness index (FI) is reduced by 0.03. This is because only the probability in the high throughput region increases as shown in the cumulative distribution function (CDF) of throughput per user. Also, as the number of user terminals in the cell increases, the amount of improvement in throughput decreases. As the number of allocated user terminals increases, more user terminals are allocated to the cell-edge, which reduces the average throughput.

This paper presents the physical-layer cell identity (PCID) detection probability using the primary synchronization signal (PSS) and secondary synchronization signal (SSS) for the New Radio (NR) radio interface considering a large frequency offset and high Doppler frequency in multipath Rayleigh fading channels in the 28-GHz band. Simulation results show that cross-correlation based PSS detection after compensating for the frequency offset achieves higher PCID detection probability than autocorrelation based PSS detection at the average received signal-to-noise power ratio (SNR) values below approximately 0dB for the frequency stability of a user equipment (UE) oscillator of ϵ =5ppm. Meanwhile, both methods achieve almost the same PCID detection probability for average received SNR values higher than approximately 0dB. We also show that even with the large frequency offset caused by ϵ =20 ppm, the high PCID detection probability of approximately 90 (97)% and 90 (96)% is achieved for the cross-correlation or autocorrelation based PSS detection method, respectively, at the average received SNR of 0dB for the subcarrier spacing of 120 (240)kHz. We conclude that utilizing the multiplexing scheme for the PSS and SSS and their sequences is effective in achieving a high PCID detection probability considering a large frequency offset even with the frequency deviation of ϵ =20ppm in the 28-GHz band.

We have developed a direct spectrum division transmission (DSDT) technique that can divide a single-carrier signal into multiple sub-spectra and assign them to dispersed frequency resources of the satellite transponder to improve the spectrum efficiency of the whole system. This paper summarizes the satellite experiments on DSDT over a single and/or multiple satellite transponders, while changing various parameters such as modulation schemes, roll-off ratios, and symbol rates. In addition, by considering practical use conditions, we present an evaluation of the performance when the spectral density of each sub-spectrum differed across transponders. The satellite experiments demonstrate that applying the proposal does not degrade the bit error rate (BER) performance. Thus, the DSDT technique is a practical approach to use the scattered unused frequency resources over not only a single transponder but also multiple ones.

After a natural disaster it is critical to urgently find victims buried under collapsed buildings. Most people habitually carry smartphones with them. Smartphones have a feature that periodically transmits Wi-Fi signals called “Probe Requests” to connect with access points. Moreover, smartphones transmit “Clear to Send” when they receive a “Request to Send” alert. This motivated us to develop a hand-held smartphone finder system that integrates a novel method for accurately locating a smartphone using the Wi-Fi signals, to support rescue workers. The system has a unique graphical user interface that tracks target smartphones. Thus, rescue workers can easily reach victims who have their smartphones with them under collapsed buildings. In this paper, after introducing the localization method, the system architecture of the smartphone finder and its prototype system are described, along with some experimental results that demonstrate the effectiveness of the smartphone finder prototype.

We experimentally evaluate the performance of a noncontact system that measures the heartbeat of a sleeping person. The proposed system comprises a pair of radar systems installed at two different positions. We use millimeter-wave ultra-wideband multiple-input multiple-output array radar systems and evaluate the performance attained in measuring the heart inter-beat interval and body movement. The importance of using two radar systems instead of one is demonstrated in this paper. We conduct three types of experiments; the first and second experiments are radar measurements of three participants lying on a bed with and without body movement, while the third experiment is the radar measurement of a participant actually sleeping overnight. The experiments demonstrate that the performance of the radar-based vital measurement strongly depends on the orientation of the person under test. They also show that the proposed system detects 70% of rolling-over movements made overnight.

Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.