The Liquid-crystal display (LCD) overdrive technique has been utilized to reduce motion blur on a display via a reduction in the response time. However, to measure the variation of the pixel amplitudes, it is necessary to store the previous frame using a large frame memory. To downscale the frame memory, block truncation coding (BTC) is commonly employed due to the simplicity of its implementation, even if some visual artifacts may occur for image blocks with high frequency components. In this paper, we present a multimode-multilevel BTC (MBTC) technique that improves performance while maintaining simplicity. To improve the visual quality, we uniquely determine the quantization level and coding mode of each block according to the distribution of the luminance and chrominance amplitudes. For a compression ratio of 6:1, the proposed method demonstrates higher coding efficiency and overdrive performance by up to 3.81 dB in the PSNR compared to other methods.

Turbo codes suffer from high decoding latency which hinders their utilization in many communication systems. Parallel decodable turbo codes (PDTCs) are suitable for parallel decoding and hence have low latency. In this article, we analyze the worst case minimum distance of parallel decodable turbo codes with both S-random interleaver and memory collision free Row-Column S-random interleaver. The effect of minimum distance on code performance is determined through computer simulations.

Classification based on predictive association rules (CPAR) is a widely used associative classification method. Despite its efficiency, the analysis results obtained by CPAR will be influenced by missing values in the data sets, and thus it is not always possible to correctly analyze the classification results. In this letter, we improve CPAR to deal with the problem of missing data. The effectiveness of the proposed method is demonstrated using various classification examples.

Clickstreams in users' navigation logs have various data which are related to users' web surfing. Those are visit counts, stay times, product types, etc. When we observe these data, we can divide clickstreams into sub-clickstreams so that the pages in a sub-clickstream share more contexts with each other than with the pages in other sub-clickstreams. In this paper, we propose a method which extracts more informative rules from clickstreams for web page recommendation based on genetic programming and association rules. First, we split clickstreams into sub-clickstreams by contexts for generating more informative rules. In order to split clickstreams in consideration of context, we extract six features from users' navigation logs. A set of split rules is generated by combining those features through genetic programming, and then informative rules for recommendation are extracted with the association rule mining algorithm. Through experiments, we verify that the proposed method is more effective than the other methods in various conditions.

A sub-mW current-reuse CMOS VCO is presented for wireless sensor network applications. In order to break the interdependence between the current consumption and the phase noise performance in the conventional current-reuse structure, a tail current source is added to the switching core in such a way that they are simultaneously switched during operation. With this, the current consumption can be maintained at a minimum level while the FET size can be optimally determined for large swing and good phase noise performances. The proposed VCO's advantage of achieving low phase noise at low current consumption is clearly demonstrated by simulations in comparison to the conventional structure. The proposed VCO is implemented in 0.13 µm CMOS. It dissipates 0.6 mW from 1.2 V supply. The measured phase noise at the output frequency of 2.28 GHz is -121 dBc/Hz at 1 MHz offset.

We propose a novel modular network called the Self-Evolving Modular Network (SEEM). The SEEM has a modular network architecture with a graph structure and these following advantages: (1) new modules are added incrementally to allow the network to adapt in a self-organizing manner, and (2) graph's paths are formed based on the relationships between the models represented by modules. The SEEM is expected to be applicable to evolving functions of an autonomous robot in a self-organizing manner through interaction with the robot's environment and categorizing large-scale information. This paper presents the architecture and an algorithm for the SEEM. Moreover, performance characteristic and effectiveness of the network are shown by simulations using cubic functions and a set of 3D-objects.

Underlay cognitive systems allow secondary users (SUs) to access the licensed band allocated to primary users (PUs) for better spectrum utilization with the power constraint imposed on SUs such that their operation does not harm the normal communication of PUs. This constraint, which limits the coverage range of SUs, can be offset by relaying techniques that take advantage of shorter range communication for lower path loss. Symbol error rate (SER) analysis of underlay cognitive relay systems over fading channel has not been reported in the literature. This paper fills this gap. The derived SER expressions are validated by simulations and show that underlay cognitive relay systems suffer a high error floor for any modulation level.

This paper proposes a video-quality estimation method based on a reduced-reference model for realtime quality monitoring in video streaming services. The proposed method chooses representative-luminance values for individual original-video frames at a server side and transmits those values, along with the pixel-position information of the representative-luminance values in each frame. On the basis of this information, peak signal-to-noise ratio (PSNR) values at client sides can be estimated. This enables realtime monitoring of video-quality degradation by transmission errors. Experimental results show that accurate PSNR estimation can be achieved with additional information at a low bit rate. For SDTV video sequences which are encoded at 1 to 5 Mbps, accurate PSNR estimation (correlation coefficient of 0.92 to 0.95) is achieved with small amount of additional information of 10 to 50 kbps. This enables accurate realtime quality monitoring in video streaming services without average video-quality degradation.

A low-power switching method using a bootstrapping circuit is proposed for a high-speed output driver of transmitter. Compared with a conventional output driver, the proposed scheme employs only nMOSFETs to transmit data. The bootstrapping circuit ensures the proper switching of nMOSFET. The proposed scheme is simulated and fabricated using a 0.18 µm CMOS technology, showing 10.2% lower power consumption than a conventional switching driver at 2.5 Gb/s data rate.

In this letter, a novel association method called ELBA (efficient load balancing association) is proposed for improved load balancing in IEEE 802.15.4-based WSNs (wireless sensor networks). ELBA adds new nodes to the network in an efficient load-balancing manner by exploiting not only RSSI (received signal strength indicator), which is used in the standard, but also traffic-load, the number of allocated GTSs (guaranteed time slots), and the number of parent nodes and child nodes. Simulation results show that ELBA offers better performance in load balancing and preventing congestion.

Since femtocells are deployed in a two tier cellular network, along with macrocells operating on the same channel, interference between them limits the overall performance of the network. Without any control of the femtocell operation, pre-deployed macrocells will experience severe interference, which is not consistent with the current femtocell deployment principle. In this paper, to resolve this problem, a mathematical framework that optimizes the downlink transmission power of femtocells is formulated. Based on the formulated framework, we derive the optimal value of the transmission power so that the transmission affects the pre-deployed macrocell's downlink performance at a minimum scale, while providing sufficient Quality of Service (QoS) to its served users. Furthermore, to reduce the complexity of the power control process, we propose an Interference Estimation scheme which approximates the interference levels between different pairs of macrocell and femtocell base stations. The feasibility of this estimation process is shown by deriving the lower and upper bound of the estimation error. Through simulations, compared to no power control, we show that our proposed method provides a 17.64% reduction in macro user's outage probability, 5.9 dB decrease of interference on cell-edge macrocell users, and a 1.41 times increase in average user throughput.

This paper employs the nature-inspired approach to investigate the ideal architecture of communication networks as large-scale and complex systems. Conventional architectures are hierarchical with respect to the functions of network operations due entirely to implementation concerns and not to any fundamental conceptual benefit. In contrast, the large-scale systems found in nature are hierarchical and demonstrate orderly behavior due to their space/time scale dependencies. In this paper, by examining the fundamental requirements inherent in controlling network operations, we clarify the hierarchical structure of network operations with respect to time scale. We also describe an attempt to build a new network architecture based on the structure. In addition, as an example of the hierarchical structure, we apply the quasi-static approach to describe user-system interaction, and we describe a hierarchy model developed on the renormalization group approach.

We propose a new fiber endface sealing technique for the optical connection of holey fibers (HFs). We experimentally investigate the optimum sealing condition for physical contact using a carbon dioxide (CO2) laser. We use this technique to fabricate an HF connector, and achieve low splice loss and a high return loss when splicing with a conventional SMF connector. With hole-assisted fiber (HAF), the obtained splice and return losses are almost the same as those obtained with the conventional method. In particular, with photonic crystal fiber (PCF), we obtained a minimum splice loss of 0.2 dB and a return loss exceeding 50 dB at wavelengths of 1.31 and 1.55 µm.

Battery-powered wireless sensor networks are prone to premature failures because some nodes deplete their batteries more rapidly than others due to workload variations, the many-to-one traffic pattern, and heterogeneous hardware. Most previous sensor network lifetime enhancement techniques focused on balancing the power distribution, assuming the usage of the identical battery. This paper proposes a novel fine-grained cost-constrained lifetime-aware battery allocation solution for sensor networks with arbitrary topologies and heterogeneous power distributions. Based on an energy–cost battery pack model and optimal node partitioning algorithm, a rapid battery pack selection heuristic is developed and its deviation from optimality is quantified. Furthermore, we investigate the impacts of the power variations on the lifetime extension by battery allocation. We prove a theorem to show that power variations of nodes are more likely to reduce the lifetime than to increase it. Experimental results indicate that the proposed technique achieves network lifetime improvements ranging from 4–13 over the uniform battery allocation, with no more than 10 battery pack levels and 2-5 orders of magnitudes speedup compared with a standard integer nonlinear program solver (INLP).

In parallel computing systems using the master/worker model for distributed grid computing, as the size of handling data grows, the increase in the data transmission time degrades the performance. For divisible workload applications, therefore, multiple-round scheduling algorithms have been being developed to mitigate the adverse effect of longer data transmission time by dividing the data into chunks to be sent out in multiple rounds, thus overlapping the times required for computation and transmission. However, a standard multiple-round scheduling algorithm, Uniform Multi-Round (UMR), adopts a sequential transmission model where the master communicates with one worker at a time, thus the transmission capacity of the link attached to the master cannot be fully utilized due to the limits of worker-side capacity. In the present study, a Parallel Transferable Uniform Multi-Round algorithm (PTUMR) is proposed. It efficiently utilizes the data transmission capacity of network links by allowing chunks to be transmitted in parallel to workers. This algorithm divides workers into groups in a way that fully uses the link bandwidth of the master under some constraints and considers each group of workers as one virtual worker. In particular, introducing a Grouping Threshold effectively deals with very heterogeneous workers in both data transmission and computation capacities. Then, the master schedules sequential data transmissions to the virtual workers in an optimal way like in UMR. The performance evaluations show that the proposed algorithm achieves significantly shorter turnaround times (i.e., makespan) compared with UMR regardless of heterogeneity of workers, which are close to the theoretical lower limits.

This paper proposes an iterative maximum a posteriori (MAP) receiver for orthogonal frequency division multiplexing (OFDM) mobile communications under fast-fading conditions. The previous work in [21] developed a MAP receiver based on the expectation-maximization (EM) algorithm employing the differential model, which can allow correlated time-variation of channel impulse responses. In order to make such a MAP receiver more robust against time-variant channels, this paper proposes two new message-passing algorithms derived from factor graphs; subcarrier removal and partial turbo processing. The subcarrier removal estimates the channel frequency response by using all subcarriers other than the targeted subcarrier. Such channel estimate can be efficiently calculated by removing information on the targeted subcarrier from the estimate of the original EM algorithm that uses all the subcarriers. This modification can avoid the repetitive use of incorrectly detected signals for the channel estimation. On the other hand, the partial turbo processing performs symbol-by-symbol channel decoding by using a symbol interleaver. Owing to this process, the current channel estimate, which is more accurate due to the decoding gain, can be used as the initial channel estimate for the next symbol. Computer simulations under fast multipath fading conditions demonstrate that the subcarrier removal and the partial turbo processing can improve the error floor and the convergence speed, respectively, compared to the conventional MAP receiver.

This paper proposed three channel aggregation schemes for cognitive radio networks, a constant channel aggregation scheme, a probability distribution-based variable channel aggregation scheme, and a residual channel-based variable channel aggregation scheme. A cognitive radio network can have a wide bandwidth if unused channels in the primary networks are aggregated. Channel aggregation schemes involve either constant channel aggregation or variable channel aggregation. In this paper, a Markov chain is used to develop an analytical model of channel aggregation schemes; and the performance of the model is evaluated in terms of the average sojourn time, the average throughput, the forced termination probability, and the blocking probability. Simulation results show that channel aggregation schemes can reduce the average sojourn time of cognitive users by increasing the channel occupation rate of unused channels in a primary network.

A simplified algorithm for check node processing of extended min-sum (EMS) q-ary LDPC decoders is presented in this letter. Compared with the bubble check algorithm, the so-called dynamic bubble-check (DBC) algorithm aims to further reduce the computational complexity for the elementary check node (ECN) processing. By introducing two flag vectors in ECN processing, The DBC algorithm can use the minimum number of comparisons at each step. Simulation results show that, DBC algorithm uses significantly fewer comparison operations than the bubble check algorithm, and presents no performance loss compared with standard EMS algorithm on AWGN channels.

Miniaturized broadband antennas combining a fractal pattern and a self-complementary structure are demonstrated for UWB applications. Using four kinds of fractal patterns generated with an octagon initiator, similar to a self-complementary structure, we investigate the effect of the fractal pattern on broadband performance. The lower band-edge frequency of the broad bandwidth is decreased by the reduced constant input impedance, which is controlled by the vacant area size inside the fractal pattern. The reduced constant input impedance is shown to be produced by the extended current distribution flowing along the vacant areas. Given the results, miniaturized broadband antennas, impedance-matched to 50 Ω, are designed and fabricated. The measured return loss was better than 10 dB between 2.95 and 10.7 GHz with a size of 2712.5 mm. The lower band-edge frequency was reduced by 28% compared with the initiator.

OFDM/offset-QAM (OFDM/OQAM) has been proven to be a promising multi-carrier transmission technique. However, carrier frequency offset (CFO) can lead to severe inter-carrier interference (ICI) and performance degradation. Meanwhile, channel estimation is also an important issue because of the intrinsic characteristics of OFDM/OQAM. In this paper, a novel pilot structure and a frequency-domain cross-correlation algorithm are proposed for the joint CFO and channel estimation. Analysis and simulation results validate the effectiveness of the proposed pilot structure and estimation algorithm.