The adaptive predistorter and the negative feedback system are known as methods to compensate for the nonlinear distortion of a power amplifier. Although the feedback method is a simple technique, its instability impedes the capability of high-feedback gain to achieve a high-compensation effect. On the other hand, the predistorter requires a long time for convergence of the adaptive predistorters. In this paper, we propose a nonlinear distortion compensation method for a narrow-band signal. In this method, an adaptive predistorter and negative feedback are combined. In addition, to shorten the convergence time to minimize nonlinear distortion, a variable step-size (VS) method is also applied to the algorithm to determine the parameters of the adaptive predistorter. Using computer simulations, we show that the proposed scheme achieves both five times faster convergence speed than that of the predistorter and three times higher permissible delay time in the feedback amplifier than that of a negative feedback only amplifier.

In this paper, we introduce a new notion of conditional converge cast (CCC), by adding the conditional property to converge cast. A CCC protocol with predicate Q is a three-party protocol which involves two senders S0 and S1 and a receiver R. S0 owns a secret x and a message m0, so does S1 with y and m1. In a protocol, S0 and S1 send their messages to R in a masked form. R obtains the message depending on the value of Q(x,y), i.e. R obtains m0 if Q(x,y)=0, or m1 otherwise. The secrets, x and y, are not revealed to R or the other sender, and Q(x,y) is not revealed to S0 and S1. In addition to the formulation, we propose a concrete scheme for conditional converge cast with the "equality" predicate.

A useful optimization problem to help solve various base station layout problems in multihop wireless networks is formulated. By solving the proposed generalized formula, the relation between the permissible largest number of hops and the minimum base station density necessary to cover an entire service area while guaranteeing a specified QoS is easily calculated. Our formula is extendable to other allocation problems by replacing parameters. The energy-cost transformation and scope of the multihop effect are also presented.

In this paper, we propose a QoS guaranteed and energy-efficient transmission scheme for Wireless Personal Area Networks (WPANs), which operate in conjunction with contention-based access protocols such as CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance). Energy consumption is one of the most important issues in WPAN systems, because WPAN devices are often required to operate under limited battery capacity. Furthermore, if the WPAN adopts a contention-based medium access protocol, the energy consumption problem becomes even more critical due to the collisions caused by independent channel access attempts. Therefore, in this paper, we propose an algorithm that selects the optimum fragment size, modulation level, and transmission power, in order to minimize the energy consumption and guarantee the QoS (Quality of Service) requirements, simultaneously. From the simulation results, it is shown that the proposed algorithm can achieve the minimum energy consumption, satisfying throughput and delay requirements.

We present an extended MPEG video format for efficient Dynamic Voltage Scaling (DVS). DVS technique has been widely researched, but the execution time variation of a periodic task (i.e. MPEG decoding) is still a challenge to be tackled. Unlike previous works, we focus on the data (video stream) rather than the execution code to overcome such limitation. The proposed video format provides the decoding costs of frames to help the precise prediction of their execution times at client machines. The experimental results show that the extended format only increases the data size less than 1% by adding about 10 bits representing the decoding cost of each frame. Also, a DVS technique adjusted for the proposed format achieves 90% of efficiency compared to the oracle case, while keeping the run time overhead of the technique negligible.

In this letter, we propose a shared adaptive packet loss concealment scheme for the high quality guaranteed Internet telephony service which connects multiple users. In order to recover packet loss efficiently in the all-IP based convergence environment, we provide a robust signal recovery scheme which is based on the shared adaptive both-side information utilization. This scheme is provided according to the average magnitude variation across the frames and the pitch period replication on the 1-port gateway (G/W) system. The simulated performance demonstrates that the proposed scheme has the advantages of low processing times and high recovery rates in the all-IP based ubiquitous environment.

Recently, a method called pipeline stage unification (PSU) has been proposed to reduce energy consumption for mobile processors via inactivating and bypassing some of the pipeline registers and thus adopt shallow pipelines. It is designed to be an energy efficient method especially for the processors under future process technologies. In this paper, we present a mechanism for the PSU controller which can dynamically predict a suitable configuration based on the program phase detection. Our results show that the designed predictor can achieve a PSU degree prediction accuracy of 84.0%, averaged from the SPEC CPU2000 integer benchmarks. With this dynamic control mechanism, we can obtain 11.4% Energy-Delay-Product (EDP) reduction in the processor that adopts a PSU pipeline, compared to the baseline processor, even after the application of complex clock gating.

Energy consumption is a major concern in embedded computing systems. Several studies have shown that cache memories account for 40% or more of the total energy consumed in these systems. Active power used to be the primary contributor to total power dissipation of CMOS designs, but with the technology scaling, the share of leakage in total power consumption of digital systems continues to grow. Moreover, temperature is another factor that exponentially increases the leakage current. In this paper, we show the effect of temperature on the optimal (minimum-energy-consuming) cache configuration for low energy embedded systems. Our results show that for a given application and technology, the optimal cache size moves toward smaller caches at higher temperatures, due to the larger leakage. Consequently, a Temperature-Aware Configurable Cache (TACC) is an effective way to save energy in finer technologies when the embedded system is used in different temperatures. Our results show that using a TACC, up to 61% energy can be saved for instruction cache and 77% for data cache compared to a configurable cache that has been configured for only the corner-case temperature (100). Furthermore, the TACC also enhances the performance by up to 28% for the instruction cache and up to 17% for the data cache.

Sleep-mode operation of a Mobile Subscriber Station (MSS) in IEEE 802.16e effectively saves energy consumption; however, it induces frame response delay. In this letter, we propose an algorithm to quickly find the optimal value of the final sleep interval in sleep-mode in order to minimize energy consumption with respect to a given frame response delay constraint. The validations of our proposed algorithm through analytical results and simulation results suggest that our algorithm provide a potential guidance to energy saving.

Clustering L0 buffers is effective for energy reduction in the instruction memory caches of embedded VLIW processors. However, the efficiency of the clustering depends on the schedule of the target application. For improving the energy efficiency of L0 clusters, an operation shuffling is proposed, which explores assignment of operations for each cycle, generates various schedules, and evaluates them to find an energy efficient schedule. This approach can find energy efficient schedules, however, it takes a long time to obtain the final result. In this paper, we propose a new method to directly generate an energy efficient schedule without iterations of operation shuffling. In the proposed method, a compiler schedules operations using the result of the single operation shuffling as a constraint. We propose some optimization algorithms to generate an energy efficient schedule for a given L0 cluster organization. The proposed method can drastically reduce the computational effort since it performs the operation shuffling only once. The experimental results show that comparable energy reduction is achieved by using the proposed method while the computational effort can be reduced significantly over the conventional operation shuffling.

Combination of mutually complementary features is necessary to cope with various changes in pattern classification between normal and pathological voices. This paper proposes a method to improve pathological/normal voice classification performance by combining heterogeneous features. Different combinations of auditory-based and higher-order features are investigated. Their performances are measured by Gaussian mixture models (GMMs), linear discriminant analysis (LDA), and a classification and regression tree (CART) method. The proposed classification method by using the CART analysis is shown to be an effective method for pathological voice detection, with a 92.7% classification performance rate. This is a noticeable improvement of 54.32% compared to the MFCC-based GMM algorithm in terms of error reduction.

Energy-efficient transmission scheme is very essential for Wireless Personal Area Networks (WPNs) for maximizing the lifetime of energy-constrained wireless devices and assuring the required QoS in the actual physical transmission at each allocated TDMA time slot. We therefore propose the minimum energy (ME) criterion based adaptive transmission scheme which determines the optimum combination of transmit power, physical data rate and fragment size required to simultaneously minimize the energy consumption and satisfy the required QoS in each assigned time duration. The improved performances offered by the proposed algorithm are demonstrated via computer simulation in terms of throughput and energy consumption.

This study has demonstrated that the clock tree construction in an SoC should be expanded to consider the intrinsic delay and skew of each IP's clock sink. A novel algorithm, called GDME, is proposed to combine grey relational clustering and DME approach for solving the problem of clock tree construction. Grey relational analysis can cluster the best pair of clock sinks and that guide a tapping point search for a DME algorithm for constructing a clock tree with zero skew and minimal delay. Experimentally, the proposed algorithm always obtains an RC- or RLC-based clock tree with zero skew and minimal delay for all the test cases and benchmarks. Experimental results demonstrate that the GDME improves up to 3.74% for total average in terms of total wire length compared with other DME algorithms. Furthermore, our results for the zero-skew RLC-based clock trees compared with Hspice are 0.017% and 0.2% lower for absolute average in terms of skew and delay, respectively.

In this paper, we propose a soft decision based cooperative sensing method for cognitive radio (CR) networks for opportunistic frequency usage. To identify unused frequency, CR should exploit sensing technique to detect presence or absence of primary user and use this information to opportunistically provide communication among secondary users while performance of primary user should not be deteriorated by the secondary users. Because of multipath fading or shadowing, the detection of primary users may be significantly difficult. For this problem, cooperative sensing (CS), where gathered observations obtained by multiple secondary users is utilized to achieve higher performance of detection, has been investigated. We design a soft decision based CS analytically and analyze the detector in several situations, i.e., signal model where single-carrier case and multi-carrier case are assumed and two scenarios; in the first scenario, SNR values of secondary users are totally equal and in the second scenario, a certain SNR difference between secondary users is assumed. We present numerical results as follows. The first scenario shows that there is little difference between the signal models in terms of detection performance. The second scenario shows that CS is superior to non-cooperative sensing. In addition, we presents that detection performance of soft decision based CS outperform detection performance of hard decision based CS.

Wireless sensor networks can be used in various fields, e.g., military and civil applications. The technique of saving energy to prolong the life of sensor nodes is one of main challenges to resource-constrained sensor networks. Therefore, in-network aggregation of data has been proposed in resource-constrained environments for energy efficiency. Most previous works on in-network aggregation only support a one-dimensional data (e.g., MIN and MAX). To support a multi-dimensional data, the skyline query is used. The skyline query returns a set of points that are not dominated by any other point on all dimensions. The majority of previous skyline query processing methods (e.g., BNL and BBS) work on centralized storage. Centralized query processing methods do not have merits in terms of energy efficiency in high event rate environments. In this paper, we propose new algorithm of in-network processing for the skyline queries. The proposed algorithm reduces the communication cost and evenly distributes load. The experimental results show the advantages of our algorithm over in-network aggregation in terms of improving energy efficiency.

Ubiquitous sensor networks (USNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient network. We propose a sleep scheduling scheme for balancing energy consumption rates in a single hop cluster based network using Analytical Hierarchy Process (AHP). We consider three factors contributing to the optimal nodes scheduling decision and they are the distance to cluster head (CH), residual energy, and sensing coverage overlapping, respectively. We also propose an integrated sleep scheduling and geographical multi-path routing scheme for USNs by AHP. The sleep scheduling is redesigned to adapt the multi-hop case. For the proposed routing protocol, the distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection. The proposed schemes are observed to improve network lifetime and conserve energy without compromising desired coverage. In the multi-hop case, it can further reduce the packet loss rate and link failure rate since the buffer capacity is considered.

FeedForward (FF-) Blind Source Separation (BSS) systems have some degree of freedom in the solution space. Therefore, signal distortion is likely to occur. First, a criterion for the signal distortion is discussed. Properties of conventional methods proposed to suppress the signal distortion are analyzed. Next, a general condition for complete separation and distortion-free is derived for multi-channel FF-BSS systems. This condition is incorporated in learning algorithms as a distortion-free constraint. Computer simulations using speech signals and stationary colored signals are performed for the conventional methods and for the new learning algorithms employing the proposed distortion-free constraint. The proposed method can well suppress signal distortion, while maintaining a high source separation performance.

We propose LPDD (Lifetime Prediction Directed Diffusion), a novel energy-aware routing protocol for sensor networks that aims at increasing network survivability without a significant increase in latency. The key concept behind the protocol is the adaptive selection of routes by predicting the battery lifetime of the minimum energy nodes along the routes.

The recent progress in sensor and wireless communication technologies has enabled the design and implementation of new applications such as sensor telemetry which is the use of wireless sensors to gather fine-grained information from products, people and places. In this work, we consider a realistic telemetry application in which an area is periodically monitored by a sensor network which gathers data from equally spaced sample points. The objective is to maximize the lifetime of the network by jointly selecting the sensing nodes, the node transmission powers and the route to the base station from each sensing node. We develop an optimization-based algorithm OPT-RE and a low complexity algorithm SP-RE for this purpose and analyze their dynamics through extensive numerical studies. Our results indicate that SP-RE is a promising algorithm which has comparable performance to that of the more computationally intensive OPT-RE algorithm. The energy consumption is significantly affected by the channel access method, and in this paper, we also compare the effects of the collision free TDMA and contention based CSMA/CA methods. We propose practical enhancements to CSMA/CA so that the energy consumption due to collisions is reduced. Our simulation results indicate that with the proposed enhancements contention based channel access can provide comparable performance to that of the collision free methods.

An energy management circuit is proposed for self-powered ubiquitous sensor modules using vibration-based energy. With the proposed circuit, the sensor modules work with low duty cycle operation. Moreover, a two-tank circuit as a part of the energy management circuit is utilized to solve the problem that the average power density of ambient energy always varies with time while the power consumption of the sensor modules is constant and larger than it. In addition, the long start-up time problem is also avoided with the timing control of the proposed energy management circuit. The CMOS implementation and silicon verification results of the proposed circuit are also presented. Its validity is further confirmed with a vibration-based energy generation. The sensor module is used to supervise the vibration of machines and transfer the vibration signal discontinuously. A piezoelectric element acts as the vibration-to-electricity converter to realize battery-free operation.