In the conventional cellular macrocell implementation strategy, the main base station transmits the radio signals in the omnidirectional manner in order to provide a wide range of cellular transmission to the users. In reality, however, the users move from one place to another depending on their activities, hence, sometimes this creates areas where no user exists inside the macrocell. Nevertheless, the base station continues to transmit the radio signals to all the coverage areas due to its involuntary manner, thus causing waste of energy. In our previous work, an energy efficient LTE macrocell base station scheme based on hourly user location distribution, which utilized opportunistic beamforming, was proposed in order to provide the cellular transmission only to the area where the user density is high. The drawback of this scheme was that there were many users who cannot receive the cellular transmission because of the limitation of the beamforming shape. In this paper, to overcome this difficulty, a new energy efficient macrocell strategy will be proposed. Here, additional low power consumption femtocell access points are deployed inside the macrocell to support the energy efficient opportunistic beamforming based on the hourly user location distribution. Concretely, the femtocell access points are woken up only when the active calling users exist inside its range. The proposed new strategy will be evaluated in terms of the hourly successful calling user ratio, the total power consumption and the hourly average downlink throughput compared with the previously proposed beamforming transmission strategy and the conventional omnidirectional transmission. The results will show the effectiveness of the proposed strategy in providing an energy efficient cellular macrocell system with high quality cellular services.

Recently, multihop wireless sensor networks (WSNs) are widely developed and applied to energy efficient data collections from environments by establishing reliable transmission radio links and employing data aggregation algorithms, which can eliminate redundant transmissions and provide fusion information. In this paper, energy efficiency which consists of not only energy consumptions but also the amount of received data by the base station, as the performance metric to evaluate network utilities is presented for achieving energy efficient data collections. In order to optimize energy efficiency for improvements of network utilization, we firstly establish a graphical game theoretic model for energy efficiency in multihop WSNs, considering message length, practical energy consumptions and packet success probabilities. Afterwards, we propose a graphical protocol for performance optimization from Nash equilibrium of the graphical game theory. The approach also consists of the distributed protocol for generating optimum tree networks in practical WSNs. The experimental results show energy efficient multihop communications can be achieved by optimum tree networks of the approach. The quantitative evaluation and comparisons with related work are presented for the metric with respect to network energy consumptions and the amount of received data by the base station. The performances of our proposal are improved in all experiments. As an example, our proposal can achieve up to about 52% energy efficiency more than collection tree protocol (CTP). The corresponding tree structure is provided for the experiment.

In most existing centralized lighting control systems, the lighting control problem (LCP) is reformulated as a constrained minimization problem and solved by linear programming (LP). However, in real-world applications, LCP is actually discrete and non-linear, which means that more accurate algorithm may be applied to achieve improvements in energy saving. In this paper, particle swarm optimization (PSO) is successfully applied for office lighting control and a linear programming guided particle swarm optimization (LPPSO) algorithm is developed to achieve considerable energy saving while satisfying users' lighting preference. Simulations in DIALux office models (one with small number of lamps and one with large number of lamps) are made and analyzed using the proposed control algorithms. Comparison with other widely used methods including LP shows that LPPSO can always achieve higher energy saving than other lighting control methods.

This paper considers on-demand WiFi wake-up where a wake-up receiver is installed into each WiFi device. The wake-up receiver detects a wake-up call by finding the predefined length of WiFi frames, which corresponds to a wake-up ID, through envelope detection with limited signal processing. Since each wake-up receiver continuously observes the WiFi channel, an adverse event of False Positive (FP), where a WiFi device is falsely turned on without actual wake-up calls, can occur when the length of non-wake-up, background data frames match with predefined length. In this paper, we suggest using the received signal strength (RSS) of WiFi frames to differentiate the real and false wake-up calls. The proposed scheme exploits the correlation among RSSs of WiFi frames received from a single station located in a fixed position. Using measured RSS data obtained under various settings and different degrees of mobility, we investigate not only the FP reduction rate but also its impact on the probability of detecting real wake-up calls. We also present experimental results obtained with our prototype in which the proposed scheme is implemented.

In this paper, we have investigated a new structure which combines dielectric cylinders with air-hole cylinders array, and analyzed the guiding problem for periodically dielectric waveguides by arbitrary shape of dielectric constants in the middle layer. In the numerical analysis, we examined an influence of the dielectric circular cylinder along a middle layer by using the energy distribution and complex propagation constants at the first stop band region compared with hollow dielectric cylinder. In addition, we also investigated the influence of dielectric structure with equivalence cross section compared with dielectric cylinders, and clarified an influence of dielectric structures in the middle layer by energy distribution analysis for TE0 mode.

The problem of power allocation in maximizing the energy efficiency of the secondary user (SU) in a delay quality-of-service (QoS) constrained CR network is investigated in this paper. The average interference power constraint is used to protect the transmission of the primary user (SU). The energy efficiency is expressed as the ratio of the effective capacity to the total power consumption. By using non-linear fractional programming and convex optimization theory, we develop an energy efficiency power allocation scheme based on the Dinkelbach method and the Lagrange multiplier method. Numerical results show that the proposed scheme outperforms the existing schemes, in terms of energy efficiency.

In this paper, by jointly considering power allocation and network selection, we address the energy efficiency maximization problem in dynamic and heterogeneous wireless networks, where user equipments are typically equipped with multi-homing capability. In order to effectively deal with the dynamics of heterogeneous wireless networks, a stochastic optimization problem is formulated that optimizes the long-term energy efficiency under the constraints of system stability, peak power consumption and average transmission rate. By adopting the parametric approach and Lyapunov optimization, we derive an equivalent optimization problem out of the original problem and then investigate its optimal resource allocation. Then, to reduce the computational complexity, a suboptimal resource allocation algorithm is proposed based on relaxed optimization, which adapts to time-varying channels and stochastic traffic without requiring relevant a priori knowledge. The simulation results demonstrate the theoretical analysis and validate the adaptiveness of our proposed algorithm.

Content centric network (CCN) is conceived as a good candidate for a futuristic Internet paradigm due to its simple and robust communication mechanism. By directly applying the CCN paradigm in wireless multihop mobile ad hoc networks, we experience various kind of issues such as packet flooding, data redundancy, packet collisions, and retransmissions etc., due to the broadcast nature of the wireless channel. To cope with the problems, in this study, we propose a novel location-aware forwarding and caching scheme for CCN-based mobile ad hoc networks. Extensive simulations are performed by using simulator, named ndnSIM. Experiment results show that proposed scheme does better as compared to other schemes in terms of content retrieval time and the number of Interest retransmissions triggered in the network.

This paper considers the beamforming design for energy efficiency transmission over multiple-input and single-output (MISO) channels. The energy efficiency maximization problem is non-convex due to the fractional form in its objective function. In this paper, we propose an efficient method to transform the objective function in fractional form into the difference of two concave functions (DC) form, which can be solved by the successive convex approximation (SCA) algorithm. Then we apply the proposed transformation and pricing mechanism to develop a distributed beamforming optimization for multiuser MISO interference channels, where each user solves its optimization problem independently and only limited information exchange is needed. Numerical results show the effectiveness of our proposed algorithm.

Cognitive radio sensor networks (CRSNs) with their dynamic spectrum access capability appear to be a promising solution to address the increasing challenge of spectrum crowding faced by the traditional WSN. In this paper, through maximizing the utility index of the CRSN, a node density-adaptive spectrum access strategy for sensor nodes is proposed that takes account of the node density in a certain event-driven region. For this purpose, considering the burst real-time data traffic, we analyze the energy efficiency (EE) and the packet failure rate (PFR) combining network disconnected rate (NDR) and packet loss rate (PLR) during the channel switching interval (CSI) for both underlay and interweave spectrum access schemes. Numerical results confirm the validity of our theoretical analyses and indicate that the adaptive node density threshold (ANDT) exists for underlay and interweave spectrum access scheme switching.

Out-of-order superscalar processors have high performance but consume a large amount of energy for dynamic instruction scheduling. We propose a front-end execution architecture (FXA) for improving the energy efficiency of out-of-order superscalar processors. FXA has two execution units: an out-of-order execution unit (OXU) and an in-order execution unit (IXU). The OXU is the execution core of a common out-of-order superscalar processor. In contrast, the IXU consists only of functional units and a bypass network only. The IXU is placed at the processor front end and executes instructions in order. The IXU functions as a filter for the OXU. Fetched instructions are first fed to the IXU, and the instructions are executed in order if they are ready to execute. The instructions executed in the IXU are removed from the instruction pipeline and are not executed in the OXU. The IXU does not include dynamic scheduling logic, and thus its energy consumption is low. Evaluation results show that FXA can execute more than 50% of the instructions by using IXU, thereby making it possible to shrink the energy-consuming OXU without incurring performance degradation. As a result, FXA achieves both high performance and low energy consumption. We evaluated FXA and compared it with conventional out-of-order/in-order superscalar processors after ARM big.LITTLE architecture. The results show that FXA achieves performance improvements of 7.4% on geometric mean in SPECCPU INT 2006 benchmark suite relative to a conventional superscalar processor (big), while reducing the energy consumption by 17% in the entire processor. The performance/energy ratio (the inverse of the energy-delay product) of FXA is 25% higher than that of a conventional superscalar processor (big) and 27% higher than that of a conventional in-order superscalar processor (LITTLE).

This paper empirically validates battery-less sensor activation via wireless energy transmission to release sensors from wires and batteries. To seamlessly extend the coverage and activate sensor nodes distributed in any indoor environment, we proposed multi-point wireless energy transmission with carrier shift diversity. In this scheme, multiple transmitters are employed to compensate path-loss attenuation and orthogonal frequencies are allocated to the multiple transmitters to avoid the destructive interference that occurs when the same frequency is used by all transmitters. In our previous works, the effectiveness of the proposed scheme was validated theoretically and also empirically by using just a spectrum analyzer to measure the received power. In this paper, we develop low-energy battery-less sensor nodes whose consumed power and required received power for activation are respectively 142µW and 400µW. In addition, we conduct indoor experiments in which the received power and activation of battery-less sensor node are simultaneously observed by using the developed battery-less sensor node and a spectrum analyzer. The results show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are, respectively, 84.4% and 83.7%, while the coverage of the proposed scheme is 100%. It can be concluded that the effectiveness of the proposed scheme can be verified by our experiments using real battery-less sensor nodes.

Out-of-order superscalar processors rename register numbers to remove false dependencies between instructions. A renaming logic for register renaming is a high-cost module in a superscalar processor, and it consumes considerable energy. A renamed trace cache (RTC) was proposed for reducing the energy consumption of a renaming logic. An RTC caches and reuses renamed operands, and thus, register renaming can be omitted on RTC hits. However, conventional RTCs suffer from several performance, energy consumption, and hardware overhead problems. We propose a semi-global renamed trace cache (SGRTC) that caches only renamed operands that are short distance from producers outside traces, and solves the problems of conventional RTCs. Evaluation results show that SGRTC achieves 64% lower energy consumption for renaming with a 0.2% performance overhead as compared to a conventional processor.

We propose a cooperative spectrum sensing scheme based on sub-Nyquist sampling in cognitive radios. Our main purpose is to understand the uncertainty caused by sub-Nyquist sampling and to present a sensing scheme that operates at low sampling rates. In order to alleviate the aliasing effect of sub-Nyquist sampling, we utilize cooperation among secondary users and the sparsity order of channel occupancy. The simulation results show that the proposed scheme can achieve reasonable sensing performance even at low sampling rates.

This work presents the exact outage performance and throughput of two-way cognitive decode-and-forward relaying wireless sensor networks with realistic transceiver relay. The relay is a self-powered wireless node that harvests radio frequency energy from the transmitted signals. We consider four configurations of a network with formed by combining two bidirectional relaying protocols (multiple access broadcast protocol and time division broadcast protocol), and two power transfer policies (dual-source energy transfer and single-fixed-source energy transfer). Based on our analysis, we provide practical insights into the impact of transceiver hardware impairments on the network performance, such as the fundamental capacity ceiling of the network with various configurations that cannot be exceeded by increasing transmit power given a fixed transmission rate and the transceiver selection strategy for the network nodes that can optimize the implementation cost and performance tradeoff.

In the field of education such as elementary and middle schools, teachers want to take care of schoolchildren during physical trainings and after-school club activities. On the other hand, in the field of sports such as professional and national-level sports, physical or technical trainers want to manage the health, physical and physiological conditions of athletes during exercise trainings in the grounds. In this way, it is required to monitor vital signs for persons during exercises, however, there are several technical problems to be solved in its realization. In this paper, we present the importance and necessity of vital monitoring for persons during exercises, and to make it possible periodically, reliably and in real-time, we present the solutions which we have so far worked out and point out remaining technical challenges in terms of vital/physical sensing, wireless transmission and human interface.

This paper presents a novel low-power decoder architecture for the (36420, 32778) binary LDPC code targeting energy-efficient NAND-flash-based mobile devices. The proposed energy-scalable decoding algorithm reduces the operating bit-width of decoding function units at the early-use stage where the channel condition is good enough to lower the precision of computation. Based on a flexible adder structure, the decoding energy of the proposed LDPC decoder can be reduced by freezing the unnecessary parts of hardware resources. A prototype 4KB LDPC decoder is designed in a 65nm CMOS technology, which achieves an average decoding throughput of 8.13Gb/s with 1.2M equivalent gates. The power consumption of the decoder ranges from 397mW to 563mW depending on operating conditions.

WLAN infrastructure has been deployed densely and extensively in the past few years. Since APs are always kept online, a dense WLAN will waste energy during idle hours. In this paper, we first state some principles for powering on/off APs in order to save energy. Then we design an energy saving mechanism correspondingly. The energy saving mechanism includes three processes: clustering APs, estimating user location, and powering on/off APs, which tries to choose appropriate APs being online according to user location information. Results of trace-driven simulation show that our mechanism could achieve about 42% energy conservation. More importantly, our mechanism can provide better network service for users than previous mechanisms which usually ignore user location information.

In many real-world classification problems, the class balance often changes between training and test datasets, due to sample selection bias or the non-stationarity of the environment. Naive classifier training under such changes of class balance systematically yields a biased solution. It is known that such a systematic bias can be corrected by weighted training according to the test class balance. However, the test class balance is often unknown in practice. In this paper, we consider a semi-supervised learning setup where labeled training samples and unlabeled test samples are available and propose a class balance estimator based on the energy distance. Through experiments, we demonstrate that the proposed method is computationally much more efficient than existing approaches, with comparable accuracy.

Content centric networking (CCN) is a newly proposed futuristic Internet paradigm in which communication depends on the decoupling of content names from their locations. In CCN-based multihop wireless ad hoc networks, the participating nodes show dynamic topology, intermittent connectivity, channels fluctuation, and severe constraints such as limited battery power. In the case of traffic congestion, the affected nodes die early owing to the shortage of battery power. Consequently, all pending request entries are also destroyed, which further degrades the network performance as well as the node working lifetime. In this study, we have proposed a novel energy aware transmission scheme in which the forwarding mechanism is based on a node's residual energy. The proposed scheme is evaluated using official ndnSIM. This scheme enhances performance in terms of content retrieval time and total Interest transmission in the network.