Recently, cooperative spectrum sensing is being studied to greatly improve the sensing performance of cognitive radio networks. To develop an adaptable cooperative sensing algorithm, an important issue is how to properly induce selfish users to participate in spectrum sensing work. In this paper, a new cognitive radio spectrum sharing scheme is developed by employing the trust-based bargaining model. The proposed scheme dynamically adjusts bargaining powers and adaptively shares the available spectrum in real-time online manner. Under widely different and diversified network situations, this approach is so dynamic and flexible that it can adaptively respond to current network conditions. Simulation results demonstrate that the proposed scheme can obtain better network performance and bandwidth efficiency than existing schemes.

In this paper, we propose Local Curvelet Binary Patterns (LCBP) and Learned Local Curvelet Patterns (LLCP) for presenting the local features of facial images. The proposed methods are based on Curvelet transform which can overcome the weakness of traditional Gabor wavelets in higher dimensions, and better capture the curve singularities and hyperplane singularities of facial images. LCBP can be regarded as a combination of Curvelet features and LBP operator while LLCP designs several learned codebooks from patch sets, which are constructed by sampling patches from Curvelet filtered facial images. Each facial image can be encoded into multiple pattern maps and block-based histograms of these patterns are concatenated into an histogram sequence to be used as a face descriptor. During the face representation phase, one input patch is encoded by one pattern in LCBP while multi-patterns in LLCP. Finally, an effective classifier called Weighted Histogram Spatially constrained Earth Mover's Distance (WHSEMD) which utilizes the discriminative powers of different facial parts, the different patterns and the spatial information of face is proposed. Performance assessment in face recognition and gender estimation under different challenges shows that the proposed approaches are superior than traditional ones.

This paper presents the feasibility of a wireless network coding prototype system based on time division multiple access using the global positioning system to facilitate the time synchronization of wireless nodes. We evaluate the system throughput of the prototype system with wireless network coding and Ethernet frame aggregation in the full buffer traffic environment assuming web browsing and voice over Internet protocol. The experimental results show that the prototype system improves the system throughput by approximately 1.85-fold compared to a system without wireless network coding or aggregation even in a multipath Rician fading environment.

This paper evaluates the impact of Through-Silicon Via (TSV) on the performance and power consumption of 3D circuitry. The physical and electrical model of TSV which considers the coupling effects with adjacent TSVs is exploited in our investigation. Simulation results show that the overall performance of 3D IC infused with TSV can be improved noticeably. The frequency of the ring oscillator in 4-tier stacking layout soars up to two times compared with one in 2D planar. Furthermore, TSV process variations are examined by Monte Carlo simulations to figure out the geometrical factor having more impact in manufacturing. An in-depth research on repeater associated with TSV offers a metric to compute the optimization of 3D systems integration in terms of performance and energy dissipation. By such optimization metric with 45 nm MOSFET used in our circuit layout, it is found that the optimal number of tiers in both performance and power consumption approaches 4 since the substantial TSV-TSV coupling effect in the worst case of interference is expected in 3D IC.

In this paper, we present Greedy Routing for Maximum Lifetime (GRMax) [1],[2] which can use the limited energy available to nodes in a Wireless Sensor Network (WSN) in order to delay the dropping of packets, thus extend the network lifetime. We define network lifetime as the time period until a source node starts to drop packets because it has no more paths to the destination [3]. We introduce the new concept of Network Connectivity Aiming (NCA) node. The primary goal of NCA nodes is to maintain network connectivity and avoid network partition. To evaluate GRMax, we compare its performance with Geographic and Energy Aware Routing (GEAR) [4], which is an energy efficient geographic routing protocol and Greedy Perimeter Stateless Routing (GPSR) [5], which is a milestone among geographic routing protocol. We evaluate and compare the performance of GPSR, GEAR, and GRMax using OPNET Modeler version 15. The results show that GRMax performs better than GEAR and GPSR with respect to the number of successfully delivered packets and the time period before the nodes begin to drop packets. Moreover, with GRMax, there are fewer dead nodes in the system and less energy is required to deliver packets to destination node (sink).

Permutation polynomial based interleavers over integer rings, in particular quadratic permutation polynomials have been widely studied. In this letter, higher degree permutation polynomials for interleavers are considered for interleavers and permutation polynomials superior to quadratic permutation polynomials are found for some lengths.

To clarify the characteristics of high-speed electrostatic discharge (ESD) events, we use two kinds of discharge electrodes: sphere- and cylinder-shape ones. We measure the energy level of ESD waveforms with charging voltages of 0.25, 0.5, and 1.0 kV. We find that the cylindrical electrode yields higher high-speed ESD energies, especially when the charging voltage is high; this indicates that the discharge gap shape is an important factor in ESD events.

In this letter, we propose a fast dynamic slot assignment (F-DSA) protocol to reduce timeslot access delay of a newly arrived node in ad hoc networks. As there is no central coordinator, a newly arrived node needs separate negotiation with all the neighboring nodes for assigning slots to itself. Thus, it may result in network join delay and this becomes an obstacle for nodes to dynamically join and leave networks. In order to deal with this issue better, F-DSA simplifies the slot assignment process. It provides frequent opportunities to assign slots by using mini-slots to share control packets in a short time. Numerical analysis and extensive simulation show that F-DSA can significantly reduce the timeslot access delay compared with other existing slot assignment protocols. In addition, we investigate the effect of the mini-slot overhead on the performance.

Reed-Solomon (RS) codes are widely used in digital communication and storage systems. Unlike usual VLSI approaches, this paper presents a high throughput fully programmable Reed-Solomon decoder on a multi-core processor. The multi-core processor platform is a 2-Dimension mesh array of Single Instruction Multiple Data (SIMD) cores, and it is well suited for digital communication applications. By fully extracting the parallelizable operations of the RS decoding process, we propose multiple optimization techniques to improve system throughput, including: task level parallelism on different cores, data level parallelism on each SIMD core, minimizing memory access, and route length minimized task mapping techniques. For RS(255, 239, 8), experimental results show that our 12-core implementation achieve a throughput of 4.35 Gbps, which is much better than several other published implementations. From the results, it is predictable that the throughput is linear with the number of cores by our approach.

This paper proposes applying intra-subframe frequency hopping (FH) to closed-loop (CL) type transmit diversity using codebook based precoding for a shared channel carrying user traffic data in discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). In the paper, we present two types of precoding schemes associated with intra-subframe FH: individual precoding vector selection between 2 slots where a 1-ms subframe comprises 2 slots among the reduced precoding codebooks, and common precoding vector selection between 2 slots. We investigate the effect of intra-subframe FH on the codebook based transmit diversity in terms of the average block error rate (BLER) performance while maintaining the same number of feedback bits required for notification of the selected precoding vector as that for the conventional CL transmit diversity without FH. Computer simulation results show that the codebook based transmit diversity with intra-subframe FH is very effective in decreasing the required average received signal-to-noise power ratio (SNR) when the fading maximum Doppler frequency, fD, is higher than approximately 50 Hz both for 2- and 4-antenna transmission in the DFT-precoded OFDMA.

Accurate modeling of sea clutter and detection of low observable targets within sea clutter are the major goals of radar signal processing applications. Recently, fractal geometry has been applied to the analysis of high range resolution radar sea clutters. The box-counting method is widely used to estimate fractal dimension but it has some drawbacks. We explain the drawbacks and propose a new fractal dimension based detector to increase detection performance in comparison with traditional detectors. Both statistically generated and real data samples are used to compare detector performance.

Wireless capsule endoscopy (WCE) is now one of most important applications in implant body area networks (BANs). WCE requires high throughput performance due to its real-time data transmission, whereas the communication performance depends much on the transmit power, which is strictly regulated in order to satisfy a safety guideline in terms of specific absorption rate (SAR). Spatial diversity reception is well known to improve the wireless performance without any temporal and spectral resource expansion. Additionally, applying spatial diversity reception to WCE systems can be expected to not only improve the wireless communication performance but also to reduce SAR. Therefore, this paper investigates the impact of spatial diversity reception on SAR levels for the 400 MHz medical implant communication service (MICS) band. To begin with, based on finite-difference time-domain (FDTD) simulations for implant BAN propagation with a numerical human body model, we first calculate the BER performance and derive the required transmit power to secure a permissible BER. Then, this paper calculates the local peak SAR under the required transmit power when the implant transmitter moves through the digestive organs. Finally, our simulation results demonstrate that applying spatial diversity reception can significantly reduce SAR in implant BANs.

Based on a proposed frame structure with an unequal sensing slot duration for each channel, and two sensing scenarios (with or without cooperation), a joint channel and sensing time assignment is suggested to maximize the uplink throughput of the centralized multi-band cognitive radio network with the consideration of the mutual interference among the secondary users (SUs). Firstly, the channel assignment is performed by using the proposed Delta Non-square Hungarian (DNH), which is a modified iterative Hungarian algorithm distinguished by throughput increment maximization and non-square weight matrix. Simulation results illustrate that DNH has significant advantages in enhancing the throughput and reducing the computational complexity. Moreover, a hybrid channel assignment, also performed by DNH, is improved based on the two sensing scenarios to maximize the throughput while efficiently limiting the interference power to primary users. Secondly, the convexity of the throughput functions within the range of sensing time is proved under the proposed frame structure, and then the maximum throughput is achieved through the steepest descent method-based sensing time assignment. Both of these results are corroborated by simulations.

Yield-driven clock skew scheduling was previously formulated as a minimum cost-to-time ratio cycle problem, by assuming that variational path delays are in Gaussian distributions. However in today's nanometer technology, process variations show growing impacts on this assumption, as variational delays with non-Gaussian distributions have been observed on these paths. In this paper, we propose a novel yield-driven clock skew scheduling method for arbitrary distributions of critical path delays. Firstly, a general problem formulation is proposed. By integrating the cumulative distribution function (CDF) of critical path delays, the formulation is able to handle path delays with any distributions. It also generalizes the previous formulations on yield-driven clock skew scheduling and indicates their statistical interpretations. Generalized Howard algorithm is derived for finding the critical cycles of the underlying timing constraint graphs. Moreover, an effective algorithm based on minimum balancing is proposed for the overall yield improvement. Experimental results on ISCAS89 benchmarks show that, compared with two representative existing methods, our method remarkably improves the yield by 10.25% on average (up to 14.66%).

This study examines the robustness of image quality factors in various types of environment illumination using a parameter design in the field of quality engineering. Experimental results revealed that image quality factors are influenced by environment illuminations in the following order: minimum luminance, maximum luminance and gamma.

Ranking the encrypted documents stored on secure cloud computing servers is becoming prominent with the expansion of the encrypted data collection. In our work, order preserving encryption is employed to pre-rank the encrypted documents. Paillier's additive homomorphic encryption is used to re-rank the top pre-ranked documents of some considerate scale.

We propose a chip identification (ID) generating scheme with random variation of transistor characteristics in SRAM bitcells. In the proposed scheme, a unique fingerprint is generated by grounding both bitlines in write operations. Through minor modifications, this scheme can be implemented for existing SRAMs. It has high speed, and it can be implemented in a very small area overhead. The generated fingerprint mainly reflects threshold voltages of load transistors in the bitcells. We fabricated test chips in a 65-nm process and obtained 12,288 sets of unique 128-bit fingerprints, which are evaluated in this paper. The failure rate of the IDs is found to be 2.110-12.

We investigate a design strategy for subthreshold circuits focusing on energy-consumption minimization and yield maximization under process variations. The design strategy is based on the following findings related to the operation of low-power CMOS circuits: (1) The minimum operation voltage (VDDmin) of a circuit is dominated by flip-flops (FFs), and VDDmin of an FF can be improved by upsizing a few key transistors, (2) VDDmin of an FF is stochastically modeled by a log-normal distribution, (3) VDDmin of a large circuit can be efficiently estimated by using the above model, which eliminates extensive Monte Carlo simulations, and (4) improving VDDmin may substantially contribute to decreasing energy consumption. The effectiveness of the proposed design strategy has been verified through circuit simulations on various circuits, which clearly show the design tradeoff between voltage scaling and transistor sizing.

Many learning machines such as normal mixtures and layered neural networks are not regular but singular statistical models, because the map from a parameter to a probability distribution is not one-to-one. The conventional statistical asymptotic theory can not be applied to such learning machines because the likelihood function can not be approximated by any normal distribution. Recently, new statistical theory has been established based on algebraic geometry and it was clarified that the generalization and training errors are determined by two birational invariants, the real log canonical threshold and the singular fluctuation. However, their concrete values are left unknown. In the present paper, we propose a new concept, a quasi-regular case in statistical learning theory. A quasi-regular case is not a regular case but a singular case, however, it has the same property as a regular case. In fact, we prove that, in a quasi-regular case, two birational invariants are equal to each other, resulting that the symmetry of the generalization and training errors holds. Moreover, the concrete values of two birational invariants are explicitly obtained, hence the quasi-regular case is useful to study statistical learning theory.