The potential for using millimeter-wave (mmWave) frequencies in future 5G wireless cellular communication systems has motivated the study of large-scale antenna arrays to achieve highly directional beamforming. However, the conventional fully digital beamforming (DBF) methods which require one radio frequency (RF) chain per antenna element are not viable for large-scale antenna arrays due to the high cost and large power consumption of high frequency RF chain components. Hybrid precoding can significantly reduce the number of required RF chains and relieve the huge power consumption in mmWave massive multiple-input multiple-output (MIMO) systems, thus attracting much interests from academic and industry. In this paper, we consider the downlink communication of a massive multiuser MIMO (MU-MIMO) system in the mmWave channel, and propose a low complexity hybrid block diagonal geometric mean decomposition (BD-GMD) scheme. More specially, a joint transmit-receive (Tx-Rx) analog beamforming with large-scale arrays is proposed to improve channel gain, and then a low-dimensional BD-GMD approach is implemented at the equivalent baseband channel to mitigate the inter-user interference and equalize different data streams of each user. With the help of successive interference cancellation (SIC) at the receiver, we can decompose each user's MIMO channel into parallel sub-channels with identical higher SNRs/SINRs, thus equal-rate coding can be applied across the sub-channels of each user. Finally, simulation results verify that the proposed hybrid BD-GMD precoding scheme outperforms existing conventional fully digital and hybrid precoding schemes and is able to achieve much better BER performance.

Traffic matrix (TM) estimation has been extensively studied for decades. Although conventional estimation techniques assume that traffic volumes are unchanged between origins and destinations, packets are often lost on a path due to traffic burstiness, silent failures, etc. Counting every path at every link, we could easily get the traffic volumes with their change, but this approach significantly increases the measurement cost since counters are usually implemented using expensive memory structures like a SRAM. This paper proposes a mathematical model to estimate TMs including volume changes. The method is established on a Boolean fault localization technique; the technique requires fewer counters as it simply determines whether each link is lossy. This paper extends the Boolean technique so as to deal with traffic volumes with error bounds that requires only a few counters. In our method, the estimation errors can be controlled through parameter settings, while the minimum-cost counter placement is determined with submodular optimization. Numerical experiments are conducted with real network datasets to evaluate our method.

Smartphones for wireless communication typically consist of a large area frontal liquid crystal display (LCD), which incorporates a metal back plate, and a back cover chassis made from metal. Leveraging this structure a new approach to construct antennas for smartphones is proposed where the complete metal back cover chassis and LCD back plate are used as the radiating element and ground plane. In the design a feedline is connected between the metal back cover chassis and LCD back plate, along with shorts at various locations between the two metal plates, to control the resonance frequency of the resulting antenna. Multiple-band operation is possible without the need for any slots in the plates for radiation. Results show that antenna frequency reconfigurability can be achieved when switching function is added to the shorts so that several wireless communication bands can be covered. This approach is different from existing metallic frame antenna designs currently available in the market. A design example is provided which uses one PIN diode for the switching shorts and the target frequency bands are 740-780MHz and 900-1000MHz & 1700-1900MHz. The optimization of LC matchings and concerns of hand effects and metallic components between the chassis and LCD metal back plate are also addressed.

In this paper, we propose a simple algorithm for detecting a vehicle trapped in flooded urban area by using quad-polarimetric SAR data. The four-component scattering power decomposition and phase difference of HH-VV co-pol ratio are effectively used in the proposed algorithm. Here we carry out polarimetric scattering measurement for a scaled vehicle model surrounded by two buildings model in an anechoic chamber, to acquire the quad-polarimetric SAR data. It is confirmed from the results of the image analysis for the measured SAR data that the proposed algorithm for vehicle detection works well even under severe environment where the vehicle is set in the shadow of the building and/or the alignment of the vehicle or the buildings is obliquely oriented to direction of the radar line of sight.

Dual-rotor machine (DRM) is a multiple input and output electromechanical device with two electrical and two mechanical ports which make it an optimal transmission system for hybrid electric vehicles. In attempt to boost its performance and efficiency, this work presents a dual-rotor permanent magnet (DR-PM) machine system used for continuously variable transmission (CVT) in HEVs. The proposed DR-PM machine is analyzed, and modeled in consideration of vehicle driving requirements. Considering energy conversion modes and torque transfer modes, operation conditions of the DR-PM machine system used for CVT are illustrated in detail. Integrated control model of the system is carried out, besides, intelligent speed ratio control strategy is designed by analyzing the dynamic coupling modes upon the integrated models to satisfy the performance requirements, reasonable energy-split between machine and engine, and optimal fuel economy. Experimental results confirm the validity of the mathematical model of the DR-PM machine system in the application of CVT, and the effectiveness of the intelligent speed ratio control strategy.

Road generalization is a method for thinning out road networks to allow easy viewing according to the size of the map. Most conventional road generalization methods mainly focus on the length of a stroke, which is a chain of links with good continuity based on the principle of perceptual grouping applied to network data such as roads and rivers. However, in the case of facility search in a web map service, for example, a “restaurant guide map,” a road generalization mechanism can be more effective if it depends not only on the stroke length but also on the facility search results. Accordingly, in this study, we implement an on-demand road generalization method that adapts to both the facility search results and the stroke length. Moreover, a sufficiently fast response speed is achieved for practical use in web map services. In particular, this study proposes a fat-stroke model that links facility information to individual strokes and implements a road generalization method that uses this model to improve the response time. In addition, we develop a prototype based on the proposed system. The system evaluation results are based on three indicators, namely, response time of the road generalization system, connectivity between strokes, and connectivity between stroke and facilities. Our experimental results suggest that the proposed method can yield improved response times by a factor of 100 or more while affording higher connectivity.

This paper presents a radio-based real-time moving object tracking method based on Kalman filtering using a phase-difference compensation technique and a non-uniform pulse transmission scheme. Conventional Kalman-based tracking methods often require time, amplitude, phase information and their derivatives for each receiver antenna; however, their location estimation accuracy does not become good even with many transmitting pulses. The presented method employs relative phase-difference information and a non-uniform pulse generation scheme, which can greatly reduce the number of transmitting pulses while preserving the tracking accuracy. Its performance is evaluated in comparison with that of conventional methods.

In order to improve an imaging performance of a sparse array radar system we propose an optimization method to find a new antenna array layout. The method searches for a minimum of the cost function based on a 3D point spread function of the array. We found a solution for the simulated problem in a form of the new layout for the antenna array with more sparse middle-point distribution comparing with initial one.

Head action recognition, as a specific problem in action recognition, has been studied in this paper. Different from most existing researches, our head action recognition problem is specifically defined for the requirement of some practical applications. Based on our definition, we build a corresponding head action dataset which contains many challenging cases. For action recognition, we proposed a real-time head action recognition framework based on HOF and ELM. The framework consists of face detection based ROI determination, HOF feature extraction in ROI, and ELM based action prediction. Experiments show that our method achieves good accuracy and is efficient enough for practical applications.

Location sharing services have recently gained momentum over mobile online social networks (mOSNs), seeing the increasing popularity of GPS-capable mobile devices such as smart phones. Despite the convenience brought by location sharing, there comes severe privacy risks. Though many efforts have been made to protect user privacy during location sharing, many of them rely on the extensive deployment of trusted Cellular Towers (CTs) and some incur excessive time overhead. More importantly, little research so far can support complete privacy including location privacy, identity privacy and social relation privacy. We propose SAM, a new System Architecture for mOSNs, and P3S, a Privacy-Preserving Protocol based on SAM, to address the above issues for privacy-preserving location sharing over mOSNs. SAM and P3S differ from previous work in providing complete privacy for location sharing services over mOSNs. Theoretical analysis and extensive experimental results demonstrate the feasibility and efficiency of the proposed system and protocol.

Frequency-hopping sequence (FHS) sets with low-hit-zone (LHZ) have Hamming correlations maintained at a low level as long as the relative time delay between different sequences are limited in a zone around the origin, and thus can be well applied in quasi-synchronous (QS) frequency-hopping multiple-access (FHMA) systems to reduce the mutual interference between different users. Moreover, the periodic partial Hamming correlation (PPHC) properties of employed LHZ-FHS sets usually act as evaluation criterions for the performances of QS-FHMA systems in practice. In this letter, a new class of LHZ-FHS sets is constructed via interleaving techniques. Furthermore, these new LHZ-FHS sets also possess optimal PPHC properties and parameters not included in the related literature.

State-of-the-art parallel systems employ a huge number of computing nodes that are connected by an interconnection network. An interconnection network (ICN) plays an important role in a parallel system, since it is responsible to communication capability. In general, an ICN shows non-linear phenomena in its communication performance, most of them are caused by congestion. Thus, designing a large-scale parallel system requires sufficient discussions through repetitive simulation runs. This causes another problem in simulating large-scale systems within a reasonable cost. This paper shows a promising solution by introducing the cellular automata concept, which is originated in our prior work. Assuming 2D-torus topologies for simplification of discussion, this paper discusses fundamental design of router functions in terms of cellular automata, data structure of packets, alternative modeling of a router function, and miscellaneous optimization. The proposed models have a good affinity to GPGPU technology and, as representative speed-up results, the GPU-based simulator accelerates simulation upto about 1264 times from sequential execution on a single CPU. Furthermore, since the proposed models are applicable in the shared memory model, multithread implementation of the proposed methods achieve about 162 times speed-ups at the maximum.

We analyze the behaviors of the FXLMS algorithm using a statistical-mechanical method. The cross-correlation between a primary path and an adaptive filter and the autocorrelation of the adaptive filter are treated as macroscopic variables. We obtain simultaneous differential equations that describe the dynamical behaviors of the macroscopic variables under the condition that the tapped-delay line is sufficiently long. The obtained equations are deterministic and closed-form. We analytically solve the equations to obtain the correlations and finally compute the mean-square error. The obtained theory can quantitatively predict the behaviors of computer simulations including the cases of both not only white but also nonwhite reference signals. The theory also gives the upper limit of the step size in the FXLMS algorithm.

We normally hold a lot of confidential information in hard disk drives and solid-state drives. When we want to erase such information to prevent the leakage, we have to overwrite the sequence of information with a sequence of symbols independent of the information. The overwriting is needed only at places where overwritten symbols are different from original symbols. Then, the cost of overwrites such as the number of overwritten symbols to erase information is important. In this paper, we clarify the minimum cost such as the minimum number of overwrites to erase information under weak and strong independence criteria. The former (resp. the latter) criterion represents that the mutual information between the original sequence and the overwritten sequence normalized (resp. not normalized) by the length of the sequences is less than a given desired value.

As energy efficiency has become a major design constraint or objective, heterogeneous manycore architectures have emerged as mainstream target platforms not only in server systems but also in embedded systems. Manycore accelerators such as GPUs are getting also popular in embedded domains, as well as the heterogeneous CPU cores. However, as the number of cores in an embedded GPU is far less than that of a server GPU, it is important to utilize both heterogeneous multi-core CPUs and GPUs to achieve the desired throughput with the minimal energy consumption. In this paper, we present a case study of mapping LBP-based face detection onto a recent CPU-GPU heterogeneous embedded platform, which exploits both task parallelism and data parallelism to achieve maximal energy efficiency with a real-time constraint. We first present the parallelization technique of each task for the GPU execution, then we propose performance and energy models for both task-parallel and data-parallel executions on heterogeneous processors, which are used in design space exploration for the optimal mapping. The design space is huge since not only processor heterogeneity such as CPU-GPU and big.LITTLE, but also various data partitioning ratios for the data-parallel execution on these heterogeneous processors are considered. In our case study of LBP face detection on Exynos 5422, the estimation error of the proposed performance and energy models were on average -2.19% and -3.67% respectively. By systematically finding the optimal mappings with the proposed models, we could achieve 28.6% less energy consumption compared to the manual mapping, while still meeting the real-time constraint.

This study proposes a multiple-output differential-input operational transconductance amplifier-C (MODI OTA-C) filter with an impedance scaler to detect cardiac activity. A ladder-type fifth-orderButterworth low-pass filter with a large time constant and low noise is implemented to reduce coefficient sensitivity and address signal distortion. Moreover, linearized MODI OTA structures with reduced transconductance and impedance scaler circuits for noise reduction are used to achieve a wide dynamic range (DR). The OTA-based circuit is operated in the subthreshold region at a supply voltage of 1 V to reduce the power consumption of the wearable device in long-term use. Experimental results of the filter with a bandwidth of 250 Hz reveal that DR is 57.6 dB, and the harmonic distortion components are below -59 dB. The power consumption of the filter, which is fabricated through a TSMC 0.18 µm CMOS process, is lower than 390 nW, and the active area is 0.135 mm2.

We propose an approach to allocate bandwidth for a satellite communications (SATCOM) system that includes the recent high-throughput satellite (HTS) with frequency flexibility. To efficiently operate the system, we manage the limited bandwidth resources available for SATCOM by employing a control method that allows the allocated bandwidths to exceed the communication demand of user terminals per HTS beam. To this end, we consider bandwidth allocation for SATCOM as an optimal control problem. Then, assuming that the model of communication requests is available, we propose an optimal control method by combining model predictive control and sparse optimization. The resulting control method enables the efficient use of the limited bandwidth and reduces the bandwidth loss and number of control actions for the HTS compared to a setup with conventional frequency allocation and no frequency flexibility. Furthermore, the proposed method allows to allocate bandwidth depending on various control objectives and beam priorities by tuning the corresponding weighting matrices. These findings were verified through numerical simulations by using a simple time variation model of the communication requests and predicted aircraft communication demand obtained from the analysis of actual flight tracking data.

Bit-interleaved coded modulation with iterative decoding (BICM-ID) is suitable for correlated Rayleigh fading channels. Additionally, BICM-ID using differential encoding can avoid the pilot overhead. In this paper, we consider BICM-ID using 16-DAPSK (differential amplitude and phase-shift keying). We first derive the probability of receiving signals conditioned on the transmission of input bits for general differential encoding; then we propose two new 16-DAPSK bit labeling methods. In addition, convolutional codes for the new bit labeling are developed. Both the minimum distance and the simulation results show that the proposed labeling has better error performance than that of the original differential encoding, and the searched new codes can further improve the error performance.

In this paper, we propose a design of reversible adder/subtractor blocks and arithmetic logic units (ALUs). The main concept of our approach is different from that of the existing related studies; we emphasize the function design. Our approach of investigating the reversible functions includes (a) the embedding of irreversible functions into incompletely-specified reversible functions, (b) the operation assignment, and (c) the permutation of function outputs. We give some extensions of these techniques for further improvements in the design of reversible functions. The resulting reversible circuits are smaller than that of the existing design in terms of the number of multiple-control Toffoli gates. To evaluate the quantum cost of the obtained circuits, we convert the circuits to reduced quantum circuits for experiments. The results also show the superiority of our realization of adder/subtractor blocks and ALUs in quantum cost.

Compressed Sensing (CS) is known to provide better channel estimation performance than the Least Square (LS) method for channel estimation. However, multipath delays may not be resolved if they span between the grids. This grid problem of CS is an obstacle to super resolution channel estimation. An Atomic Norm (AN) minimization is one of the methods for estimating continuous parameters. The AN minimization can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. There are studies showing that the AN minimization method has better resolution than conventional CS methods. In this paper, we propose a channel estimation method based on the AN minimization for Spread Spectrum (SS) systems. The accuracy of the proposed channel estimation is compared with the conventional LS method and Dantzig Selector (DS) of the CS. In addition to the application of channel estimation in wireless communication, we also show that the AN minimization can be applied to Global Positioning System (GPS) using Gold sequence.