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.

Fine-grained power gating (FGPG) is a power-saving technique by switching off circuit blocks while the blocks are idle. Although FGPG can reduce power consumption without compromising computational performance, switching the power supply on and off causes energy overhead. To prevent power increase caused by the energy overhead, in our prior research we proposed an FGPG control method of the operating system(OS) based on pre-analyzing applications' power usage. However, modern computing systems have a wide variety of use cases and run many types of application; this makes it difficult to analyze the behavior of all these applications in advance. This paper therefore proposes a new FGPG control method without profiling application programs in advance. In the new proposed method, the OS monitors a circuit's idle interval periodically while application programs are running. The OS enables FGPG only if the interval time is long enough to reduce the power consumption. The experimental results in this paper show that the proposed method reduces power consumption by 9.8% on average and up to 17.2% at 25°C. The results also show that the proposed method achieves almost the same power-saving efficiency as the previous profile-based method.

It is qualitatively considered that emergency information processing by using UTM grids is effective in generating COP (Common Operational Pictures). Here, we conducted a numerical evaluation based on emergency information-processing training to examine the efficiency of the use of UTM grid maps by staff at the Tagajo City Government office. The results of the demonstration experiment were as follows: 1) The time required for information propagation and mapping with UTM coordinates was less than that with address text consisting of area name and block number. 2) There was no measurable difference in subjective estimates of the training performance of participants with or without the use of UTM grids. 3) Fear of real emergency responses decreased among training participants using UTM grids. 4) Many of the negative free answers on a questionnaire evaluation of participants involved requests regarding the reliability and operability of UTM tools.

Energy-efficient resource allocation is considered in sensing-based spectrum sharing for cooperative cognitive radio networks (CCRNs). The secondary user first listens to the spectrum allocated to the primary user (PU) to detect the PU state and then initiates data transmission with two power levels based on the sensing decision (e.g., idle or busy). Under this model, the optimization problem of maximizing energy efficiency (EE) is formulated over the transmission power and sensing time subject to some practical limitations, such as the individual power constraint for secondary source and relay, the quality of service (QoS) for the secondary system, and effective protection for the PU. Given the complexity of this problem, two simplified versions (i.e., perfect and imperfect sensing cases) are studied in this paper. We transform the considered problem in fractional form into an equivalent optimization problem in subtractive form. Then, for perfect sensing, the Lagrange dual decomposition and iterative algorithm are applied to acquire the optimal power allocation policy; for imperfect sensing, an exhaustive search and iterative algorithm are proposed to obtain the optimal sensing time and corresponding power allocation strategy. Finally, numerical results show that the energy-efficient design greatly improves EE compared with the conventional spectrum-efficient design.

In this paper, we propose a multi-cell structure backscatter based wireless-powered communication network (WPCN) where a number of backscatter cells are locally separated, each containing a subset of users around a carrier emitter. The multi-cell structure backscatter based WPCN can be implemented in two ways, namely time-division multiplexing (TDM) and frequency-division multiplexing (FDM). Here users harvest energy from the carrier signal transmitted by the carrier emitter, and then transmit their own information in a passive way via the reflection of the carrier signal using frequency-shift keying modulation. We characterize the energy-free condition and the signal-to-noise ratio (SNR) outage zone in a backscatter based WPCN. Also, a backscatter based harvest-then-transmit protocol is adopted to maximize the sum-throughput of all users by optimally allocating time for energy harvesting and information transmission. Numerical results demonstrate that the backscatter based WPCN ensures an increased long-range coverage and a diminished SNR outage zone compared to conventional radio based WPCNs. Also, comparing the two types of multi-cell structure backscatter based WPCN, TDM within each backscatter cell and FDM across backscatter cells versus FDM within each backscatter cell and TDM across backscatter cells, numerical results confirm that which one yields a better performance.

A demonstration of power enhancement by nonlinear oscillation in a millimeter-sized electrostatic vibrational energy harvester for the future Internet of Things is presented. To enable nonlinearity in microelectromechanical system (MEMS) devices, we selected a gold spring as a component of the MEMS structure for its lower Young's modulus than conventional materials, a ductile characteristic, and an electrical conductivity. The mechanical characteristics of the fabricated MEMS device related to the nonlinear phenomenon were examined. The charging characteristics of an ethylene tetrafluoroethylene copolymer (ETFE) electret film for electrostatic induction were also evaluated. Nonlinear oscillation for the millimeter-sized energy harvester with the ETFE electret was confirmed experimentally by applying external vibration. The oscillation resulted in a bandwidth two times broader than that by linear oscillation. The normalized harvester effectiveness of the nonlinear oscillation was 5.1 times higher than that of the linear one.

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 emergency situations, telecommunication networks become congested due to large numbers of call requests. Also, some infrastructure breaks down, so undamaged communication resources must be utilized more efficiently. Therefore, several lines in telephone exchanges are generally reserved for emergency calls whose users communicate crucial information. The number of lines reserved for emergency calls is determined by a threshold, on a trunk reservation control method. To accept both required emergency calls and more general calls, the traffic intensity of arriving emergency calls should be estimated in advance, and a threshold should be configured so that the number of reserved lines becomes lower than the estimation. Moreover, we propose that the holding time for general calls should be positively limited. By guaranteeing the holding time sufficient for communicating essential information, holding time limitation reduces long-period calls so more general calls are accepted. In this paper, we propose a new CAC method to utilize undamaged communication resources more efficiently during emergencies. Our proposed method accepts more general calls by collaboratively relaxing the threshold of trunk reservation and limiting holding time of general calls. This method is targeted at not only the telephone exchange but also various systems on networks, e.g. base stations of the wireless network or SIP servers. With our method, the threshold is configured in consideration of the ratio of traffic intensities estimated in advance. We modeled the telephone exchange as a queueing loss system and calculated call-blocking rates of both emergency and general calls by using computer simulation. The comparison with the conventional holding time limitation method showed that our proposed method accepts the required number of emergency calls by appropriately relaxing the threshold, while suppressing the increase in call-blocking of general calls.

Shrinkage widely linear recursive least squares (SWL-RLS) and its improved version called structured shrinkage widely linear recursive least squares (SSWL-RLS) algorithms are proposed in this paper. By using the relationship between the noise-free a posterior and a priori error signals, the optimal forgetting factor can be obtained at each snapshot. In the implementation of algorithms, due to the a priori error signal known, we still need the information about the noise-free a priori error which can be estimated with a known formula. Simulation results illustrate that the proposed algorithms have faster convergence and better tracking capability than augmented RLS (A-RLS), augmented least mean square (A-LMS) and SWL-LMS algorithms.

In this letter, an underground facility management system for effective underground facility management is suggested. The present underground facility management system uses a wired and wireless duplex communication method to enable seamless communication, and rapid responses to any failures encountered. In this letter, the architecture and components of underground facility management system supporting heterogeneous duplex communication is suggested, and relevant work flow is presented.

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.

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.

We have developed an automatic network configuration technology for flexible and robust network construction. In this paper, we propose a two-or-more-level hierarchical link-state routing protocol in Hierarchical QoS Link Information Protocol (HQLIP). The hierarchical routing easily scales up the network by combining and stacking configured networks. HQLIP is designed not to recompute shortest-path trees from topology information in order to achieve a high-speed convergence of forwarding information base (FIB), especially when renumbering occurs in the network. In addition, we propose a fixed-midfix renumbering (FMR) method. FMR enables an even faster convergence when HQLIP is synchronized with Hierarchical/Automatic Number Allocation (HANA). Experiments demonstrate that HQLIP incorporating FMR achieves the convergence time within one second in the network where 22 switches and 800 server terminals are placed, and is superior to Open Shortest Path First (OSPF) in terms of a convergence time. This shows that a combination of HQLIP and HANA performs stable renumbering in link-state routing protocol networks.

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.

The likelihood-ratio based score level fusion (LR-based fusion) scheme has attracted much attention, since it maximizes accuracy if a log-likelihood ratio (LLR) is accurately estimated. In reality, it can happen that a user cannot input some query samples due to temporary physical conditions such as injuries and illness. It can also happen that some modalities tend to cause false rejection (i.e. the user is a “goat” for these modalities). The LR-based fusion scheme can handle these situations by setting LLRs corresponding to missing query samples to 0. In this paper, we refer to such a mode as a “modality selection mode”, and address an issue of accuracy in this mode. Specifically, we provide the following contributions: (1) We firstly propose a “modality selection attack”, in which an impostor inputs only query samples whose LLRs are more than 0 (i.e. takes an optimal strategy) to impersonate others. We also show that the impostor can perform this attack against the SPRT (Sequential Probability Ratio Test)-based fusion scheme, which is an extension of the LR-based fusion scheme to a sequential fusion scenario. (2) We secondly consider the case when both genuine users and impostors take this optimal strategy, and show that the overall accuracy in this case is “worse” than the case when they input all query samples. More specifically, we prove that the KL (Kullback-Leibler) divergence between a genuine distribution of integrated scores and an impostor's one, which can be compared with password entropy, is smaller in the former case. We also show to what extent the KL divergence losses for each modality. (3) We finally evaluate to what extent the overall accuracy becomes worse using the NIST BSSR1 Set 2 and Set 3 datasets, and discuss directions of multibiometric applications based on the experimental results.

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.

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.