Overlapped FFT based energy detection has been proposed as a signal detection scheme in dynamic spectrum access. The overlapped FFT scheme increases the number of FFT frames to reduce the variance of squared noise and improves the detection performance. As the FFT frames are overlapped, correlation values between the frames affect to the detection performance. This paper proposes the window functions which decrease the correlation values between adjacent FFT bins. Numerical results obtained through computer simulation show that novel window functions generated by upsampling a Hamming window improves the detection performance by 0.09. However, this window function suffers more from adjacent channel interference than a conventional window. Therefore, this paper also proposes a two step detection scheme to achieve higher detection performance and to avoid the influence of the adjacent channel signal. Numerical results also indicate that the proposed scheme improves the detection performance and reduces the effect from the adjacent channel signal.

It is widely known that decoding problems for random linear codes are computationally hard in general. Surprisingly, Kopparty and Saraf proved query-efficient list-decodability of sparse random linear codes by showing a reduction from a decoding problem for sparse random linear codes to that for the Hadamard code with small number of queries even under high error rate [11]. In this paper, we show a more direct list-decoding algorithm for sparse random linear codes with small number of queries from a Fourier-analytic approach.

Secure sets and defensive alliances in graphs are studied. They are sets of vertices that are safe in some senses. In this paper, we first present a fixed-parameter algorithm for finding a small secure set, whose running time is much faster than the previously known one. We then present improved bound on the smallest sizes of defensive alliances and secure sets for hypercubes. These results settle some open problems paused recently.

Face recognition under variable illumination conditions is a challenging task. Numbers of approaches have been developed for solving the illumination problem. In this paper, we summarize and analyze some noteworthy issues in illumination processing for face recognition by reviewing various representative approaches. These issues include a principle that associates various approaches with a commonly used reflectance model and the shared considerations like contribution of basic processing methods, processing domain, feature scale, and a common problem. We also address a more essential question-what to actually normalize. Through the discussion on these issues, we also provide suggestions on potential directions for future research. In addition, we conduct evaluation experiments on 1) contribution of fundamental illumination correction to illumination insensitive face recognition and 2) comparative performance of various approaches. Experimental results show that the approaches with fundamental illumination correction methods are more insensitive to extreme illumination than without them. Tan and Triggs' method (TT) using L1 norm achieves the best results among nine tested approaches.

A narrowband interference (NBI) estimation and mitigation method based on compressive sensing (CS) for communication systems with repeated training sequences is investigated in this letter. The proposed CS-based differential measuring method is performed through the differential operation on the inter-block-interference-free regions of the received adjacent training sequences. The sparse NBI signal can be accurately recovered from a time-domain measurement vector of small size under the CS framework, without requiring channel information or dedicated resources. Theoretical analysis and simulation results show that the proposed method is robust to NBI under multi-path fading channels.

SAFER block cipher family consists of SAFER K, SAFER SK, SAFER+ and SAFER++. As the first proposed block cipher of them, SAFER K is strengthened by SAFER SK with improved key schedule. SAFER+ is designed as an AES candidate and Bluetooth uses a customized version of it for security. SAFER++, a variant of SAFER+, is among the cryptographic primitives selected for the second phase of the NESSIE project. In this paper, we take advantage of properties of the linear transformation and S-boxes to identify new impossible differentials for SAFER SK, SAFER+, and SAFER++. Moreover, we give the impossible differential attacks on 4-round SAFER SK/128 and 4-round SAFER+/128(256), 5-round SAFER++/128 and 5.5-round SAFER++/256. Our attacks significantly improve previously known impossible differential attacks on them. Specifically, our attacks on SAFER+ are the best attack in terms of number of rounds.

This paper presents our investigation of non-orthogonal multiple access (NOMA) as a novel and promising power-domain user multiplexing scheme for future radio access. Based on information theory, we can expect that NOMA with a successive interference canceller (SIC) applied to the receiver side will offer a better tradeoff between system efficiency and user fairness than orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems. This improvement becomes especially significant when the channel conditions among the non-orthogonally multiplexed users are significantly different. Thus, NOMA can be expected to efficiently exploit the near-far effect experienced in cellular environments. In this paper, we describe the basic principle of NOMA in both the downlink and uplink and then present our proposed NOMA scheme for the scenario where the base station is equipped with multiple antennas. Simulation results show the potential system-level throughput gains of NOMA relative to OMA.

We present a time-to-digital converter (TDC) achieving sub-picosecond resolution and high precision for all-digital phase-locked-loops (ADPLLs). The basic idea is using a charge pump to translate time interval into charge, and a successive-approximation-register-analog-to-digital converter (SAR-ADC) to quantize the charge. With this less complex configuration, high resolution, high precision, low power, and small area can be achieved all together. We analyzed the noise contribution from the charge pump and describe detailed design and implementation for sizing the capacitor and transistors, with the awareness of noise and linearity. The analysis demonstrates the proposed TDC capable of sub-picosecond resolution and high precision. Two prototype chips were fabricated in 65nm CMOS with 0.06mm2, and 0.018mm2 core areas, respectively. The achieved resolutions are 0.84ps and 0.80ps, in 8-bit and 10-bit range, respectively. The measured single-shot-precisions range from 0.22 to 0.6ps, and from 0.66 to 1.04ps, respectively, showing consistent trends with the analysis. Compared with state-of-the-arts, best performance balance has been achieved.

A multicode transmission (MC) system can transmit multiple data streams at one time. However, the amplitude of the transmission signal has sharp fluctuations. To avoid this problem, constant amplitude (CA) signaling schemes were studied, and some MC systems were developed such as the MC system with CA signaling (MC-CA) and the parallel combinatory MC system with CA signaling (PCMC-CA). In this paper, extension systems of PCMC-CA system are developed. In particular, two demodulation methods are discussed for the extension systems. Then, the bit error rate (BER) and data transmission rate are theoretically analyzed. The results shows that the extension systems has a better performance than the MC-CA system in both of the BER and data transmission rate.

Up until now, the best public key encryption with multi-dimensional range query (PKMDRQ) scheme has two problems which need to be resolved. One is that the scheme is selectively secure. The other is that the time of decryption is long. To address these problems, we present a method of converting a predicate encryption supporting inner product (IPE) scheme into a PKMDRQ scheme. By taking advantage of this approach, an instance is also proposed. The comparison between the previous work and ours shows that our scheme is more efficient over the time complexity. Moreover, our scheme is adaptively secure.

In this paper, resource-efficient multiple description coding (MDC) multicast is investigated in cognitive radio networks with the consideration of imperfect spectrum sensing and imperfect channel feedback. Our objective is to maximize the system goodput, which is defined as the total successfully received data rate of all multicast users, while guaranteeing the maximum transmit power budget and the maximum average received interference constraint. Owing to the uncertainty of the spectrum state and the non-closed-form expression of the objective function, it is difficult to solve the problem directly. To circumvent this problem, a pretreatment is performed, in which we first estimate the real spectrum state of primary users and then propose a Gaussian approximation for the probability density functions of transmission channel gains to simplify the computation of the objective function. Thereafter, a two-stage resource allocation algorithm is presented to accomplish the subcarrier assignment, the optimal transmit channel gain to interference plus noise ratio (T-CINR) setting, and the transmit power allocation separately. Simulation results show that the proposed scheme is able to offset more than 80% of the performance loss caused by imperfect channel feedback when the feedback error is not high, while keeping the average interference on primary users below the prescribed threshold.

This paper proposes a graph-theory-based Euler number computing algorithm. According to the graph theory and the analysis of a mask's configuration, the Euler number of a binary image in our algorithm is calculated by counting four patterns of the mask. Unlike most conventional Euler number computing algorithms, we do not need to do any processing of the background pixels. Experimental results demonstrated that our algorithm is much more efficient than conventional Euler number computing algorithms.

Robust yet efficient techniques for detecting and tracking targets in infrared (IR) images are a significant component of automatic target recognition (ATR) systems. In our previous works, we have proposed infrared target detection and tracking systems based on sparse representation method. The proposed infrared target detection and tracking algorithms are based on sparse representation and Bayesian probabilistic techniques, respectively. In this paper, we adopt Naïve Bayes Nearest Neighbor (NBNN) that is an extremely simple, efficient algorithm that requires no training phase. State-of-the-art image classification techniques need a comprehensive learning and training step (e.g., using Boosting, SVM, etc.) In contrast, non-parametric Nearest Neighbor based image classifiers need no training time and they also have other more advantageous properties. Results of tracking in infrared sequences demonstrated that our algorithm is robust to illumination changes, and the tracking algorithm is found to be suitable for real-time tracking of a moving target in infrared sequences and its performance was quite good.

In this paper, we present a new method for diagnosis of stochastic discrete event system. The method is based on anomaly detection for sequences. We call the method sequence profiling (SP). SP does not require any system models and any system-specific knowledge. The only information necessary for SP is event logs from the target system. Using event logs from the system in the normal situation, N-gram models are learned, where the N-gram model is used as approximation of the system behavior. Based on the N-gram model, the diagnoser estimates what kind of faults has occurred in the system, or may conclude that no faults occurs. Effectiveness of the proposed method is demonstrated by application to diagnosis of a multi-processor system.

We proposed a hard-wired CPG hardware network to reproduce the gaits of four-legged animals. It should reproduce walking and bounding, and they should be switchable with each other by changing the value of only one voltage.

Providing images captured by an on-board camera to surrounding vehicles is an effective method to achieve smooth road traffic and to avoid traffic accidents. We consider providing images using WiFi technology based on the IEEE802.11p standard for vehicle-to-vehicle (V2V) communication media. We want to compress images to suppress communication traffic, because the communication capacity of the V2V system is strictly limited. However, there are difficulties in image compression and transmission using wireless communication especially in a vehicular broadcast environment, due to transmission errors caused by fading, packet collision, etc. In this letter, we propose an image transmission technique based on compressed sensing. Through computer simulations, we show that our proposed technique can achieve stable image reconstruction despite frequent packet error.

This paper presents a synchronization mechanism to effectively implement the lock and barrier protocols in a decentralized manner through explicit message passing. In the proposed solution, a simple and efficient synchronization control mechanism is proposed to support queued synchronization without contention. By using state-of-the-art Application-Specific Instruction-set Processor (ASIP) technology, we embed the synchronization functionality into a baseline processor, making the proposed mechanism feature ultra-low overhead. Experimental results show the proposed synchronization achieves ultra-low latency and almost ideal scalability when the number of processors increases.

For low-density parity-check codes, spatial coupling was proved to boost the performance of iterative decoding up to the optimal performance. As an application of spatial coupling, in this paper, bit-interleaved coded modulation (BICM) with spatially coupled (SC) interleaving — called SC-BICM — is considered to improve the performance of iterative channel estimation and decoding for block-fading channels. In the iterative receiver, feedback from the soft-in soft-out decoder is utilized to refine the initial channel estimates in linear minimum mean-squared error (LMMSE) channel estimation. Density evolution in the infinite-code-length limit implies that the SC-BICM allows the receiver to attain accurate channel estimates even when the pilot overhead for training is negligibly small. Furthermore, numerical simulations show that the SC-BICM can provide a steeper reduction in bit error rate than conventional BICM, as well as a significant improvement in the so-called waterfall performance for high rate systems.

This paper investigates the system-level throughput of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) in the cellular downlink assuming proportional fair (PF)-based radio resource (bandwidth and transmission power) allocation. The purpose of this study is to examine the possibility of applying NOMA with a SIC to the systems beyond the 4G cellular system. Both the mean and cell-edge user throughput are important in a real system. PF-based scheduling is known to achieve a good tradeoff between them by maximizing the product of the user throughput among users within a cell. In NOMA with a SIC, the scheduler allocates the same frequency to multiple users simultaneously, which necessitates multiuser scheduling. To achieve a better tradeoff between the mean and cell-edge user throughput, we propose and compare three power allocation strategies among users, which are jointly implemented with multiuser scheduling. Extensive simulation results show that NOMA with a SIC with a moderate number of non-orthogonally multiplexed users significantly enhances the system-level throughput performance compared to orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems.

In this paper, we discuss performance modeling of 3-D stencil computing on an FPGA accelerator with a high-level synthesis environment, aiming for efficient exploration of user-space design parameters. First, we analyze resource utilization and performance to formulate these relationships as mathematical models. Then, in order to evaluate our proposed models, we implement heat conduction simulations as a benchmark application, by using MaxCompiler, which is a high-level synthesis tool for FPGAs, and MaxGenFD, which is a domain specific framework of the MaxCompiler for finite-difference equation solvers. The experimental results with various settings of architectural design parameters show the best combination of design parameters for pipeline structure can be systematically found by using our models. The effects of changing arithmetic accuracy and using data stream compression are also discussed.