The purpose of this work is to reduce the redundant coding process with the tradeoff between the encoding complexity and coding efficiency in HEVC, especially for high resolution applications. Therefore, a CU depth prediction algorithm is proposed for motion estimation process of HEVC. At first, an efficient CTU depth prediction algorithm is proposed to reduce redundant depth. Then, CU size termination and skip algorithm is proposed based on the neighboring block depth and motion consistency. Finally, the overall algorithm, which has excellent complexity reduction performance for high resolution application is proposed. Moreover, the proposed method achieves steady performance, and it can significantly reduce the encoding time in different environment configuration and quantization parameter. The simulation experiment results demonstrate that, in the RA case, the average time saving is about 56% with only 0.79% BD-bitrate loss for the high resolution, and this performance is better than the previous state of the art work.

Satellite-borne or aircraft-borne synthetic aperture radar (SAR) is useful for high resolution imaging analysis for terrain surface monitoring or surveillance, particularly in optically harsh environments. For surveillance application, there are various approaches for automatic target recognition (ATR) of SAR images aiming at monitoring unidentified ships or aircraft. In addition, various types of analyses for full polarimetric data have been developed recently because it can provide significant information to identify structure of targets, such as vegetation, urban, sea surface areas. ATR generally consists of two processes, one is target feature extraction including target area determination, and the other is classification. In this paper, we propose novel methods for these two processes that suit full polarimetric exploitation. As the target area extraction method, we introduce a peak signal-to noise ratio (PSNR) based synthesis with full polarimetric SAR images. As the classification method, the circular polarization basis conversion is adopted to improve the robustness especially to variation of target rotation angles. Experiments on a 1/100 scale model of X-band SAR, demonstrate that our proposed method significantly improves the accuracy of target area extraction and classification, even in noisy or target rotating situations.

A terahertz-wave communication system directly connected to an optical fiber network is promising for application to future mobile backhaul and fronthaul links. The possible broad bandwidth in the terahertz band is useful for high-speed signal transmission as well as radio-space encapsulation to the high-frequency carrier. In both cases, the low-latency feature becomes important to enhance the throughput in mobile communication and is realized by waveform transport technology without any digital-signal-processing-based media conversion. A highly precise optical frequency comb signal generated by optical modulation and the vector signal demodulation technology adopted from advanced optical fiber communication technologies help perform modulation and demodulation with impairment compensation at just the edges of the link. Terahertz wave, radio over fiber, waveform transport, coherent detection, multilevel modulation, radio on radio.

The multiterminal hypothesis testing problem with zero-rate constraint is considered. For this problem, an upper bound on the optimal error exponent is given by Shalaby and Papamarcou, provided that the positivity condition holds. Our contribution is to prove that Shalaby and Papamarcou's upper bound is valid under a weaker condition: (i) two remote observations have a common random variable in the sense of Gácks and Körner, and (ii) when the value of the common random variable is fixed, the conditional distribution of remaining random variables satisfies the positivity condition. Moreover, a generalization of the main result is also given.

ThruChip interface (TCI) is an emerging wireless interface in three-dimensional (3-D) integrated circuit (IC) technology. However, the TCI physical design guidelines remain unclear. In this paper, a ThruChip test chip is designed and fabricated for design guidelines exploration. Three inductive coupling interface physical design scenarios, baseline, power mesh, and dummy metal fill, are deployed in the test chip. In the baseline scenario, the test chip measurement results show that thinning chip or enlarging coil dimension can further reduce TCI power. The power mesh scenario shows that the eddy current on power mesh can dramatically reduce magnetic pulse signal and thus possibly cause TCI to fail. A power mesh splitting method is proposed to effectively suppress eddy current impact while minimizing power mesh structure impact. The simulation results show that the proposed method can recover 77% coupling coefficient loss while only introducing additional 0.5% IR-drop. In dummy metal fill case, dummy metal fill enclosed within TCI coils have no impact on TCI transmission and thus are ignorable.

This report describes an all-digital phase-locked loop (ADPLL) using a temperature compensated settling time reduction technique. The novelty of this work is autonomous oscillation control word estimation without a look-up table or memory circuits. The proposed ADPLL employs a multi-phase digitally controlled oscillator (DCO). In the proposed estimation method, the optimum oscillator tuning word (OTW) is estimated from the DCO frequency characteristic in the setup phase of ADPLL. The proposed ADPLL, which occupies 0.27×0.36mm2, is fabricated by a 65 nm CMOS process. The temperature compensation PLL controller (TCPC) is implemented using an FPGA. Although the proposed method has 20% area overhead, measurement results show that the 47% settling time is reduced. The average settling time at 25°C is 3µs. The average reduction energy is at least 42% from 0°C to 100°C.

Spatial compressive sensing (SCS) has recently been applied to direction-of-arrival (DOA) estimation, owing to its advantages over conventional versions. However the performance of compressive sensing (CS)-based estimation methods degrades when the true DOAs are not exactly on the discretized sampling grid. We solve the off-grid DOA estimation problem using the deterministic maximum likelihood (DML) estimation method. In this letter, on the basis of the convexity of the DML function, we propose a computationally efficient algorithm framework for off-grid DOA estimation. Numerical experiments demonstrate the superior performance of the proposed methods in terms of accuracy, robustness and speed.

Non-volatile memory has many advantages such as high density and low leakage power but it consumes larger writing energy than SRAM. It is quite necessary to reduce writing energy in non-volatile memory design. In this paper, we propose write-reduction codes based on error correcting codes and reduce writing energy in non-volatile memory by decreasing the number of writing bits. When a data is written into a memory cell, we do not write it directly but encode it into a codeword. In our write-reduction codes, every data corresponds to an information vector in an error-correcting code and an information vector corresponds not to a single codeword but a set of write-reduction codewords. Given a writing data and current memory bits, we can deterministically select a particular write-reduction codeword corresponding to the data to be written, where the maximum number of flipped bits are theoretically minimized. Then the number of writing bits into memory cells will also be minimized. Experimental results demonstrate that we have achieved writing-bits reduction by an average of 51% and energy reduction by an average of 33% compared to non-encoded memory.

Microwave ultra-wideband (UWB) radar systems are advantageous for their high-range resolution and ability to penetrate dielectric objects. Internal imaging of dielectric objects by UWB radar is a promising nondestructive method of testing aging roads and bridges and a noninvasive technique for human body examination. For these applications, we have already developed an accurate internal imaging approach based on the range points migration (RPM) method, combined with a method that efficiently estimates the dielectric constant. Although this approach accurately extracts the internal boundary, it is applicable only to highly conductive targets immersed in homogeneous dielectric media. It is not suitable for multi-layered dielectric structures such as human tissues or concrete objects. To remedy this limitation, we here propose a novel dielectric constant and boundary extraction method for double-layered materials. This new approach, which simply extends the Envelope method to boundary extraction of the inner layer, is evaluated in finite difference time domain (FDTD)-based simulations and laboratory experiments, assuming a double-layered concrete cylinder. These tests demonstrate that our proposed method accurately and simultaneously estimates the dielectric constants of both media and the layer boundaries.

In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.

8K Ultra High Definition Television (UHDTV) requires extremely high throughput for video decoding based on H.265. In H.265, intra coding could significantly enhance video compression efficiency, at the expense of an increased computational complexity compared with H.264. For intra prediction of 8K UHDTV real-time H.265 decoding, the joint complexity and throughput issue is more difficult to solve. Therefore, based on the divide-and-conquer strategy, we propose a new VLSI architecture in this paper, including two techniques, in order to achieve 8K UHDTV H.265 intra prediction decoding. The first technique is the LUT based Reference Sample Fetching Scheme (LUT-RSFS), reducing the number of reference samples in the worst case from 99 to 13. It further reduces the circuit area and enhances the performance. The second one is the Hybrid Block Reordering and Data Forwarding (HBRDF), minimizing the idle time and eliminating the dependency between TUs by creating 3 Data Forwarding paths. It achieves the hardware utilization of 94%. Our design is synthesized using Synopsys Design Compiler in 40nm process technology. It achieves an operation frequency of 260MHz, with a gate count of 217.8K for 8-bit design, and 251.1K for 10-bit design. The proposed VLSI architecture can support 4320p@120fps H.265 intra decoding (8-bit or 10-bit), with all 35 intra prediction modes and prediction unit sizes ranging from 4×4 to 64×64.

This paper describes the circuit design and measurement results of a new GaAs-HBT RF power detector proposed for use in WiMAX and wireless LAN transmitter applications. The detector, which is based on a simple current-mirror topology, occupies a small die area. It is, therefore, not only easy to implement together with a GaAs-HBT power amplifier, but can also offer approximately logarithmic (linear-in-dB) characteristics. Because it can also be driven with small voltage amplitudes, it is suitable for base-terminal monitoring at an HBT power stage. When the detector is used as a base-terminal power monitor, an appropriate base resistance added to the detection HBT effectively suppresses frequency dispersion of the detected voltage characteristics. Measurements of a prototype detector incorporated into a single-stage HBT power amplifier fabricated on the same die are as follows. The detector is capable of delivering a detected voltage of 0.35-2.5 V with a slope of less than 0.17 V/dB over a 4-to-24-dBm output power range at 3.5 GHz while drawing a current of less than 1.8 mA from a 2.85-V supply. While satisfying a log conformance error of less than 1 dB over an amplifier output power range from 4 dBm to 24 dBm, it can also suppress the detected power dispersion within 0.18 dB at approximately 15 dBm of output power over a 3.1-3.9-GHz-wide frequency range. This dispersion value is approximately one-tenth that of a conventional collector-terminal-monitor-type diode detector.

Mobile virtual network operators (MVNOs) are mobile operators without their own infrastructure or government issued spectrum licenses. They purchase spectrum resources from primary mobile network operators (MNOs) to provide communication services under their own brands. MVNOs are expected to play an important role in mobile network markets, as this will increase the competition in retail markets and help to meet the demand of niche markets. However, with the rapidly increasing demand of mobile data traffic, efficient utilization of the limited spectrum resources owned by MVNOs has become an important issue. We propose here a resource sharing mechanism between MVNOs against the background of network functions virtualization (NFV). The proposed mechanism enables MVNOs to improve their quality of service (QoS) by sharing spectrum resources with each other. A nash bargaining solution based decision strategy is also devised to ensure the fairness of resource sharing. Extensive numerical evaluation results validate the effectiveness of the proposed models and mechanisms.

An 8-Mbit 0.18-µm CMOS 1T1C ferroelectric RAM (FeRAM) in a planar ferroelectric technology was developed. Even though the cell area of 2.48 µm2 is almost equal to that of a 4-Mbit stacked-capacitor FeRAM (STACK FeRAM) 2.32 µm2[1], the chip size of the developed 8-Mbit FeRAM, including extra 2-Mbit parities for the error correction code (ECC), is just 52.37 mm2, which is about 30% smaller than twice of the 4-Mbit STACK FeRAM device, 37.68mm2×2[1]. This excellent characteristic can be attributed to the large cell matrix architectures of the sectional cyclic word line (WL) that was used to increase the column numbers, and to the 1T1C bit-line GND level sensing (BGS)[2][3] circuit design intended to sense bit lines (BL) that have bit cells 1K long and a large capacitance. An access time of 52 ns and a cycle time of 77 ns in RT at a VDD of 1.8 V were achieved.

The next generation high efficiency video coding (HEVC) standard achieves high performance by extending the encoding block to 64×64. There are some parallel tools to improve the efficiency for encoder and decoder. However, owing to the dependence of the current prediction block and surrounding block, parallel processing at CU level and Sub-CU level are hard to achieve. In this paper, focusing on the spatial motion vector prediction (SMVP) and temporal motion vector prediction (TMVP), parallel improvement for spatio-temporal prediction algorithms are presented, which can remove the dependency between prediction coding units and neighboring coding units. Using this proposal, it is convenient to process motion estimation in parallel, which is suitable for different parallel platforms such as multi-core platform, compute unified device architecture (CUDA) and so on. The simulation experiment results demonstrate that based on HM12.0 test model for different test sequences, the proposed algorithm can improve the advanced motion vector prediction with only 0.01% BD-rate increase that result is better than previous work, and the BDPSNR is almost the same as the HEVC reference software.

This paper studies a privacy-preserving decision tree learning protocol (PPDT) for vertically partitioned datasets. In vertically partitioned datasets, a single class (target) attribute is shared by both parities or carefully treated by either party in existing studies. The proposed scheme allows both parties to have independent class attributes in a secure way and to combine multiple class attributes in arbitrary boolean function, which gives parties some flexibility in data-mining. Our proposed PPDT protocol reduces the CPU-intensive computation of logarithms by approximating with a piecewise linear function defined by light-weight fundamental operations of addition and constant multiplication so that information gain for attributes can be evaluated in a secure function evaluation scheme. Using the UCI Machine Learning dataset and a synthesized dataset, the proposed protocol is evaluated in terms of its accuracy and the sizes of trees*.

The pilot contamination is a serious problem which hinders the capacity increasing in the massive MIMO system. Similar to Fractional Frequency Reuse (FFR) in the OFDMA system, Fractional Pilot Reuse (FPR) is proposed for the massive MIMO system. The FPR can be further classified as the strict FPR and soft FPR. Meanwhile, the detailed FPR schemes with pilot assignment and the mathematical models are provided. With FPR, the capacity and the transmission quality can be improved with metrics such as the higher Signal to Interference and Noise Ratio (SINR) of the pilots, the higher coverage probability, and the higher system capacity.

An L2-in-L3 tunneling technology plays an important role in network virtualization based on the concept of Software-Defined Networking (SDN). VXLAN (Virtual eXtensible LAN) and NVGRE (Network Virtualization using Generic Routing Encapsulation) protocols are being widely used in public cloud datacenters. These protocols resolve traditional VLAN problems such as a limitation of the number of virtual networks, however, their network performances are low without dedicated hardware acceleration. Although STT (Stateless Transport Tunneling) achieves far better performance, it has pragmatic problems in that STT packets can be dropped by network middleboxes like stateful firewalls because of modified TCP header semantics. In this paper, we propose yet another layer 4 protocol (Segment-oriented Connection-less Protocol, SCLP) for existing tunneling protocols. Our previous study revealed that the high-performance of STT mainly comes from 2-level software packet pre-reassembly before decapsulation. The SCLP header is designed to take advantage of such processing without modifying existing protocol semantics. We implement a VXLAN over SCLP tunneling and evaluate its performance by comparing with the original VXLAN (over UDP), NVGRE, Geneve, and STT. The results show that the throughput of the proposed method was comparable to STT and almost 70% higher than that of other protocols.

This paper studies the impact of integrating pricing with connection admission control (CAC) on the congestion management practices in contention-based wireless random access networks. Notably, when the network is free of charge, each self-interested user tries to occupy the channel as much as possible, resulting in the inefficient utilization of network resources. Pricing is therefore adopted as incentive mechanism to encourage users to choose their access probabilities considering the real-time network congestion level. A Stackelberg leader-follower game is formulated to analyze the competitive interaction between the service provider and the users. In particular, each user chooses the access probability that optimizes its payoff, while the self-interested service provider decides whether to admit or to reject the user's connection request in order to optimize its revenue. The stability of the Stackelberg leader-follower game in terms of convergence to the Nash equilibrium is established. The proposed CAC scheme is completely distributed and can be implemented by individual access points using only local information. Compared to the existing schemes, the proposed scheme achieves higher revenue gain, higher user payoff, and higher QoS performance.

Crowd collectiveness, i.e., a quantitative metric for collective motion, has received increasing attention in recent years. Most of existing methods build a collective network by assuming each agent in the crowd interacts with neighbors within fixed radius r region or fixed k nearest neighbors. However, they usually use a universal r or k for different crowded scenes, which may yield inaccurate network topology and lead to lack of adaptivity to varying collective motion scenarios, thereby resulting in poor performance. To overcome these limitations, we propose a compressive sensing (CS) based method for measuring crowd collectiveness. The proposed method uncovers the connections among agents from the motion time series by solving a CS problem, which needs not specify an r or k as a priori. A descriptor based on the average velocity correlations of connected agents is then constructed to compute the collectiveness value. Experimental results demonstrate that the proposed method is effective in measuring crowd collectiveness, and performs on par with or better than the state-of-the-art methods.