A high energy-efficiency and area-reduction switching scheme for a low-power successive approximation register (SAR) analog-to-digital converter (ADC) is presented. Based on the sequence initialization, monotonic capacitor switching procedure and multiple reference voltages, the average switching energy and total capacitance of the proposed scheme are reduced by 99.4% and 87.5% respectively, compared to the conventional architecture.

The problem of power allocation for the secondary user (SU) in a cognitive radio (CR) network is investigated in this paper. The primary user (PU) is protected by the average interference power constraint. Besides the average interference power constraint at the PU, the transmit power of the SU is also subject to the peak or average transmit power constraint. The aim is to balance between the goal of maximizing the ergodic capacity and the goal of minimizing the outage probability of the SU. Power allocation schemes are then proposed under the aforementioned setups. It is shown that the proposed power allocation schemes can achieve high ergodic capacity while maintaining low outage probability, whereas existing schemes achieve either high ergodic capacity with high outage probability or low outage probability with low ergodic capacity.

This letter introduces an Energy-Aware LED Light System (EA-LLS) that provides adequate illumination to users according to the analysis of the sun's position, the user's movement, and various environmental factors, without sun illumination detection sensors. This letter presents research using algorithms and scenarios. We propose an EA-LLS that offers not only On/Off and dimming control, but dimming control through daylight, space, and user behavior analysis.

Sparse Matrix-Vector Multiplication (SpMxV) is widely used in many high-performance computing applications, including information retrieval, medical imaging, and economic modeling. To eliminate the overhead of zero padding in SpMxV, prior works have focused on partitioning a sparse matrix into row vectors sets (RVS's) or sub-matrices. However, performance was still degraded due to the sparsity pattern of a sparse matrix. In this letter, we propose a heuristics, called recursive merging, which uses a greedy approach to recursively merge those row vectors of nonzeros in a matrix into the RVS's, such that each set included is ensured a local optimal solution. For ten uneven benchmark matrices from the University of Florida Sparse Matrix Collection, our proposed partitioning algorithm is always identified as the method with the highest mean density (over 96%), but with the lowest average relative difference (below 0.07%) over computing powers.

Real-time high-quality reverberation simulation plays an important role in many modern applications, such as computer games and virtual reality. Traditional physically and perceptually-based reverberation simulation techniques, however, suffer from the high computational cost and lack of the specific characteristics of the enclosure. In this paper, a hybrid reverberation simulation approach is proposed in which early reflections are reproduced by convolving with the impulse response modeled by the image-source method and late reverberation is reproduced by the feedback delay network. A parametric predictor of energy decay relief is presented for the modeled early reflections and then exploited to compute the parameters of the feedback delay network. This ensures the smooth transition in the time-frequency domain from early to late reflections. Numerical simulation and listening tests validate the effectiveness of this proposed hybrid reverberation simulation approach.

In a previous paper, we proposed a rescue support system for victims buried in an earthquake disaster by constructing an ad-hoc network using home-server based smart homes. However, this system has the following two problems: i) it cannot ensure sufficient density of home servers to realize adequate WLAN coverage, ii) the system does not consider areas in which home servers cannot be used such as parks and factories, for example. In this paper, we propose a new method using a delay tolerant network (DTN) technique. In this method, rescuers (such as rescue teams) with mobile devices relay information between disconnected networks by walking around during rescue activities. For a performance evaluation, we performed simulation experiments using a map of Abeno-ku, Osaka. From our results, we show that the proposed method increases the information acquisition rate, and that the network can be maintained. We also quantitatively show the penetration rate of smart homes needed for our system. In addition, we show that the rescue request system is more effective than other systems, and the method with the mobile device relay is better than without this method.

This paper proposes a novel approach to generate stereo video in which the zoom magnification is not constant. Although this has been achieved mechanically in a conventional way, it is necessary for this approach to develop a mechanically complex system for each stereo camera system. Instead of a mechanical solution, we employ an approach from the software side: by using a pair of zoomed and non-zoomed video, a part of the non-zoomed video image is cut out and super-resolved for generating stereo video without a special hardware. To achieve this, (1) the zoom magnification parameter is automatically determined by using distributions of intensities, and (2) the cutout image is super-resolved by using optically zoomed images as exemplars. The effectiveness of the proposed method is quantitatively and qualitatively validated through experiments.

A simple robust finite-time convergent observer is presented in the presence of unknown input disturbance and measurement noise. In order to achieve the robust estimation and ensure the finite-time convergence, the proposed observer is constructed by using a multiple integral observer scheme in a hybrid system framework. Comparative computer simulations and laboratory experiments have been performed to test the effectiveness of the proposed observer.

We propose an energy-efficient real-time scheduling algorithm based on T-L Plane abstraction. The algorithm is designed to exploit Dynamic Power Management and generates a new event called event-s to render longer idle intervals, which increases the chances of switching a processor to the sleep mode. We compare the proposed algorithm with previous work and show that it is effective for energy management.

This paper investigates the detection performance of an improved energy detector for a secondary user with spatially correlated multiple antennas. In an improved energy detector, an arbitrary positive power operation p replaces the squaring operation in a conventional energy detector, and the optimum value of p that gives the best detection performance may be different from 2. Firstly, for a given value of p, we derive closed-form expressions for the probability of detection and the probability of false alarm when antennas at the secondary user are exponentially correlated. We then find the optimum value of p for two different detection criteria-maximizing the probability of detection for a target probability of false alarm, and minimizing the probability of false alarm for a target probability of detection. We show that the optimum p is strongly dependent on system parameters like number of antennas, antenna correlation coefficient among multiple antennas, and average received signal-to-noise ratio (SNR). From results, we infer that, in low SNR regime, the effect of antenna correlation is less pronounced on the optimum p. Finally, we find the optimum values of p and threshold jointly that minimize the total error rate.

The Satellite/Terrestrial Integrated mobile Communication System (STICS), which allows terrestrial mobile phones to communicate directly through a satellite, has been studied [1]. Satellites are unaffected by the seismic activity that causes terrestrial damage, and therefore, the STICS can be expected to be a measure that ensures emergency call connection. This paper first describes the basic characteristics of call blocking rates of terrestrial mobile phone systems in areas where non-functional base stations are geographically clustered, as investigated through computer simulations that showed an increased call blocking rate as the number of non-functional base stations increased. Further simulations showed that restricting the use of the satellite system for emergency calls only ensures the STICS's capacity to transmit emergency communications; however, these simulations also revealed a weakness in the low channel utilization rate of the satellite system [2]. Therefore, in this paper, we propose increasing the channel utilization rate with a priority channel framework that divides the satellite channels between priority channels for emergency calls and non-priority channels that can be available for emergency or general use. Simulations of this priority channel framework showed that it increased the satellite system's channel utilization rate, while continuing to ensure emergency call connection [3]. These simulations showed that the STICS with a priority channel framework can provide efficient channel utilization and still be expected to provide a valuable secondary measure to ensure emergency communications in areas with clustered non-functional base stations during large-scale disasters.

Considering worse-case channel uncertainties, we investigate the robust energy efficient (EE) beamforming design problem in a K-user multiple-input-single-output (MISO) interference channel. Our objective is to maximize the worse-case sum EE under individual transmit power constraints. In general, this fractional programming problem is NP-hard for the optimal solution. To obtain an insight into the problem, we first transform the original problem into its lower bound problem with max-min and fractional form by exploiting the relationship between the user rate and the minimum mean square error (MMSE) and using the min-max inequality. To make it tractable, we transform the problem of fractional form into a subtractive form by using the Dinkelbach transformation, and then propose an iterative algorithm using Lagrangian duality, which leads to the locally optimal solution. Simulation results demonstrate that our proposed robust EE beamforming scheme outperforms the conventional algorithm.

In this paper, we propose a flexible and high-capacity front-haul link for the uplink transmission of high-speed mobile signals using a cascade of radio-on-radio (RoR) and radio-over-fiber (RoF) systems. To emulate the cases that may occur in the uplink direction, we experimentally investigate the performance of superposing an uplink bursty LTE-A signal on the cascaded system using optical packet signal transmission. The performance of systems using different types of erbium-doped fiber amplifiers (EDFAs), including a high-transient EDFA, an automatic-gain-control EDFA, and a burst-mode (BM) EDFA is evaluated and compared. We confirm that the dynamic transience of the EDFAs has a significant influence on the signal performance. By using a BM-EDFA, we confirm successful transmission of the uplink packetized LTE-A signal on the cascaded system. Both the measured error vector magnitude and the received optical power range metrics exceed the requirements. We also estimate the maximum transmission range of the RoR link, and it is confirmed that a sufficiently long range could be achieved for the applications in mobile front-haul networks.

In emerging wearable sensor systems, it is crucial to save energy because these systems are severely energy-constrained. For making the sensors in these systems energy efficient, transmission power control (TPC) is widely used, and thus far, many TPC algorithms have been proposed in the literature. However, these TPC algorithms do not always work well in all wireless body channel conditions, which are capriciously varied due to diverse sensor environments such as sensor placements, body movements, and body locations. In this paper, we propose a simple TPC algorithm that quickly and stably approaches the optimal transmission power level and works well in all wearable sensor environments. We experimentally evaluated the proposed TPC algorithm and proved that it works well under all wireless body channel conditions.

It is not easy to provide energy supply based on renewable energy enough to satisfy energy demand anytime and anywhere because the amount of renewable energy depends on geographical conditions and the time of day. In order to maximize the satisfaction of energy demand by renewable energy, surplus energy generated with renewable energy should be stored in batteries, and transmitted to electric loads with high demand somewhere in the electricity system. This paper proposes a novel autonomous decentralized mechanism of energy interchanges between distributed batteries on the basis of the diffusion equation and MCMC (Markov Chain Monte Carlo) for realizing energy supply appropriately for energy demand. Experimental results show that the proposed mechanism effectively works under several situations. Moreover, we discuss a method to easily estimate the behavior of the entire system by each node with the proposed mechanism, and the application potentiality of this estimating method to an efficient method working with non-renewable generators while minimizing the dependence of non-renewable energy, and an incentive mechanism to prevent monopolizing energy in systems.

Modern processors use Branch Target Buffer (BTB)[1] to relax control dependence. Unfortunately, the energy consumption of the BTB is high. In order to effectively fetch instructions, it is necessary to perform a branch prediction at the fetch stage, regardless of whether the fetched instruction is a branch or a nonbranch. Therefore, the number of accesses to the BTB is large, and the energy consumption of the BTB is high. However, accesses from nonbranches to the BTB waste energy. In this paper, we focus on accesses from nonbranches to the BTB, which we call useless accesses from a viewpoint of power. For reducing energy consumption without performance loss, we present a method that reduces useless accesses by using information that indicates whether a fetched instruction is a branch or not. To realize the above approach, we propose a branch bit called B-Bit. A B-Bit is associated with an instruction and indicates whether it is a branch or not. A B-Bit is available at the beginning of the fetch stage. If a B-Bit is “1” signifying a branch, the BTB is accessed. If a B-Bit is “0” signifying a nonbranch, the BTB is not accessed. The experimental results show that the total energy consumption can be reduced by 54.3% without performance loss.

The authors have been researching on reducing the power consumption of microprocessors, and developed a low-power processor called “Geyser” by applying power gating (PG) function to the individual functional units of the processor. PG function on Geyser reduces the power consumption of functional units by shutting off the power voltage of idle units. However, the energy overhead of switching the supply voltage for units on and off causes power increases. The amount of the energy overhead varies with the behavior of each functional unit which is influenced by running application, and also with the core temperature. It is therefore necessary to switch the PG function itself on or off according to the state of the processor at runtime to reduce power consumption more effectively. In this paper, the authors propose a PG control method to take the power overhead into account by the operating system (OS). In the proposed method, for achieving much power reduction, the OS calculates the power consumption of each functional unit periodically and inhibits the PG function of the unit whose energy overhead is judged too high. The method was implemented in the Linux process scheduler and evaluated. The results show that the average power consumption of the functional units is reduced by up to 17.2%.

To eliminate CAMs from the load/store queues, several techniques to detect memory access order violation with hash filters composed of RAMs have been proposed. This paper proposes a technique with parallel counting Bloom filters (PCBF). A Bloom filter has extremely low false positive rates owing to multiple hash functions. Although some existing researches claim the use of Bloom filters, none of them make mention to multiple hash functions. This paper also addresses the problem relevant to the variety of access sizes of load/store instructions. The evaluation results show that our technique, with only 2720-bit Bloom filters, achieves a relative IPC of 99.0% while the area and power consumption are greatly reduced to 14.3% and 22.0% compared to a conventional model with CAMs. The filter is much smaller than usual branch predictors.

This work addresses two key topics in the field of energy harvesting and wireless power transfer. The first is the optimum signal design for improved RF-DC conversion efficiency in rectifier circuits by using time varying envelope signals. The second is the design of rectifiers that present reduced sensitivity to input power and output load variations by introducing resistance compression network (RCN) structures.

As energy consumption of cache memories increases, an energy-efficient cache management mechanism is required. While a dynamic cache resizing mechanism is one promising approach to the energy reduction of microprocessors, one problem is that its effect is limited by the existence of dead-on-fill blocks, which are not used until their evictions from the cache memory. To solve this problem, this paper proposes a cache management policy named FLEXII, which can reduce the number of dead-on-fill blocks and help dynamic cache resizing mechanisms further reduce the energy consumption of the cache memories.