Network life time and hence device life time is one of the fundamental metrics in wireless body area networks (WBAN). To prolong it, especially those of implanted sensors, each node must conserve its energy as much as possible. While a variety of wake-up/sleep mechanisms have been proposed, the wake-up radio potentially serves as a vehicle to introduce vulnerabilities and attacks to WBAN, eventually resulting in its malfunctions. In this paper, we propose a novel secure wake-up scheme, in which a wake-up authentication code (WAC) is employed to ensure that a BAN Node (BN) is woken up by the correct BAN Network Controller (BNC) rather than unintended users or malicious attackers. The scheme is thus particularly implemented by a two-radio architecture. We show that our scheme provides higher security while consuming less energy than the existing schemes.

In wireless networks, sleep mode based power saving mechanisms can reduce the energy consumption at the expense of additional packet delay. This letter analyzes its packet queueing delay and wireless terminals' energy efficiency. Based on the analysis, optimal sleep window size can be derived to optimize terminal energy efficiency with delay constraint.

In this letter, we propose an energy efficient hybrid architecture, the Hybrid MAC-based Robust Architecture (HMR), for wireless sensor networks focusing on MAC layer's scheduling and adaptive security suite as a security sub layer. A hybrid MAC layer with TDMA and CSMA scheduling is designed to prolong network life time, and the multi-channel TDMA based active/sleep scheduling is presented. We also present the security related functionalities needed to employ a flexible security suite to packets dynamically. Implementation and testbed of the proposed framework based on IEEE 802.15.4 are shown as well.

Due to the low complexity and cost characteristics of ultra-wideband (UWB) systems, a weighted acquisition algorithm based on energy detection is proposed in this paper. This method is divided into two steps to acquire the direct path (DP) component. Firstly, weighted energy detection is applied to determine which energy block the DP lies in by generalized likelihood ratio test (GLRT). A sub-optimal weighted vector is obtained, by which the closed form of detection performance is proposed. In the second step, the precise position of DP within the detected energy block is obtained by the statistical characteristics of the channel energy distributions. Key parameters that affect acquisition performance are studied by analytical and numerical methods. Simulations and experiments are carried out for performance and complexity comparison with traditional ones. The results show that weighted acquisition achieves better performance under relative low complexity conditions.

The usage of light-weight mobile devices is increasing rapidly, leading to demand for more telecommunication services. Consequently, mobile ad hoc networks and their applications have become feasible with the proliferation of light-weight mobile devices. Many protocols have been developed to handle service discovery and routing in ad hoc networks. However, the majority of them did not consider one critical aspect of this type of network, which is the limited of available energy in each node. Cluster Based Routing Protocol (CBRP) is a robust/scalable routing protocol for Mobile Ad hoc Networks (MANETs) and superior to existing protocols such as Ad hoc On-demand Distance Vector (AODV) in terms of throughput and overhead. Therefore, based on this strength, methods to increase the efficiency of energy usage are incorporated into CBRP in this work. In order to increase the stability (in term of life-time) of the network and to decrease the energy consumption of inter-cluster gateway nodes, an Enhanced Gateway Cluster Based Routing Protocol (EGCBRP) is proposed. Three methods have been introduced by EGCBRP as enhancements to the CBRP: improving the election of cluster Heads (CHs) in CBRP which is based on the maximum available energy level, implementing load balancing for inter-cluster traffic using multiple gateways, and implementing sleep state for gateway nodes to further save the energy. Furthermore, we propose an Energy Efficient Cluster Based Routing Protocol (EECBRP) which extends the EGCBRP sleep state concept into all idle member nodes, excluding the active nodes in all clusters. The experiment results show that the EGCBRP decreases the overall energy consumption of the gateway nodes up to 10% and the EECBRP reduces the energy consumption of the member nodes up to 60%, both of which in turn contribute to stabilizing the network.

Fast Fourier Transform (FFT) is an important algorithm in many digital signal processing applications, and it often requires parallel implementation for high throughput. In this paper, we first present the SmartCell coarse-grained reconfigurable architecture targeted for stream processing. A SmartCell prototype integrates 64 processing elements, configurable interconnections, and dedicated instruction and data memories into a single chip, which is able to provide high performance parallel processing while maintaining post-fabrication flexibility. Subsequently, we present a parallel FFT architecture targeted for multi-core platforms computing systems. This algorithm provides an optimized data flow pattern that reduces both communication and configuration overheads. The proposed parallel FFT algorithm is then mapped onto the SmartCell prototype device. Results show that the parallel FFT implementation on SmartCell is about 14.9 and 2.7 times faster than network-on-chip (NoC) and MorphoSys implementations, respectively. SmartCell also achieves the energy efficiency gains of 2.1 and 28.9 when compared with FPGA and DSP implementations.

This paper analyzes the ergodic capacity of the MIMO multi-keyhole channel, assuming that the channel state information (CSI) is available only at the receiver. We first derive new closed-form expressions for marginal probability density function (pdf) of the single unordered eigenvalue as well as joint pdf of ordered eigenvalues of the channel matrix in a simple and general framework. With these statistical results, we then present an exact closed-form expression for the ergodic capacity. We analyze tight bounds on the exact capacity and propose a new tight lower bound. We also investigate the asymptotic capacity performances in low-signal-to-noise-ratio (SNR) and high-SNR regimes to gain further insights. All our results apply for arbitrary number of keyholes and antennas. Numerical simulations are presented to validate our theoretical analysis.

In this paper, we obtain some refinement of representation theorems for context-free languages by using Dyck languages, insertion systems, strictly locally testable languages, and morphisms. For instance, we improved the Chomsky-Schützenberger representation theorem and show that each context-free language L can be represented in the form L=h(D ∪ R), where D is a Dyck language, R is a strictly 3-testable language, and h is a morphism. A similar representation for context-free languages can be obtained, using insertion systems of weight (3,0) and strictly 4-testable languages.

Energy efficient routing is one of the key design issues to prolong the lifetime of wireless sensor networks (WSNs) since sensor nodes can not be easily re-charged once they are deployed. During routing process, the routes with only few hops or with too many hops are not energy efficient. Hop-based routing algorithms can largely improve the energy efficiency of multi-hop routing in WSNs because they can determine the optimal hop number as well as the corresponding intermediate nodes during multi-hop routing process under medium or high density network. In this paper, we not only focus on studying the relationship between energy consumption and hop number from theoretical point of view but also provide a practical selection criterion of the sub-optimal hop number under practical sensor network so as to minimize the energy consumption. We extend the theoretical deduction of optimal hop number and propose our Hop-based Energy Aware Routing (HEAR) algorithm which is totally distributed and localized. Simulation results show that our HEAR algorithm can reduce the average energy consumption about 10 times compared to the direct transmission algorithm and 2 to 10 times than other algorithms like LEACH and HEED under various network topologies.

This paper presents unconditionally stable and conformal FDTD schemes which are based on the alternating-direction implicit finite difference time domain (ADI-FDTD) method for accurate modeling of perfectly electric conducting (PEC) objects. The proposed schemes are formulated within the framework of the matrix-vector notation of the finite integration technique (FIT), which allows a systematic and consistent extension of finite difference solution of Maxwell's equations on dual grids. As possible choices of second-order convergent conformal method, we apply the partially filled cell (PFC) and the uniformly stable conformal (USC) schemes for the ADI-FDTD method. The unconditional stability and the rates of convergence of the proposed conformal ADI-FDTD (CADI-FDTD) schemes are verified by means of numerical examples of waveguide problems.

A generalized formulation of the instantaneous frequency based on the symmetric higher order differential energy operator is proposed. The motivation for the formulation is that there is some frequency misalignment in time when the ordinary higher order differential energy operator is used for the instantaneous frequency estimator. The special cases of the generalized formulation are also presented. The proposed instantaneous frequency estimators are compared with existing methods in terms of error performance measured in the mean absolute error. In terms of the estimation error performance, the third order instantaneous frequency estimator with the symmetrical structure shows the best result under noise free condition. Under noisy situation, the fourth order instantaneous frequency estimator with the symmetrical structure produces the best results. Application examples are provided to show the usefulness of the estimator.

Power consumption is one of the most important factors in successfully designing of wireless sensor networks since it directly affects network lifetime. We propose a topology control scheme that reduces power consumption by minimizing, as much as possible, the number of active nodes, in a highly dense region as well as to decrease packet transmission delay. Simulation results show that our scheme can effectively solve the energy inefficiency problem caused by unbalanced power consumption, and can significantly reduce packet transmission delay.

We propose a novel epidemic routing policy, named energy optimal epidemic routing, for delay tolerant networks (DTNs). By investigating the tradeoff between delay and energy, we found the optimal transmission range as well as the optimal number of infected nodes for the minimal energy consumption, given a delivery requirement, specifically delay bound and delivery probability to the destination. We derive an analytic model of the Binary Spraying routing to find the optimal values, describing the delay distributions with respect to the number of infected nodes.

To realize dynamic spectrum access (DSA), spectrum sensing is performed to detect the presence or absence of primary users (PUs). This paper proposes a sensing architecture. This architecture enables use cases such as DSA with PU detection using a single spectrum sensor and DSA with distributed sensing, such as cooperative sensing, collaborative sensing, and selective sensing. In this paper we focus on distributed sensing. These sensing schemes employ distributed spectrum sensors (DSSs) where each sensor uses energy detection (ED) in Rayleigh fading environment. To theoretically analyze the performance of the three sensing schemes, a closed-form expression for the probability of detection by ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, we obtain analytical models of the three sensing schemes. Analysis shows that at 5-dB signal-to-noise ratio (SNR) and with a false alarm rate of 0.004, the probability of detection is increased from 0.02 to 0.3 and 0.4, respectively, by cooperative sensing and collaborative sensing schemes using using three DSSs. Results also show that the selected sensing scheme matches the performance of the collaborative sensing scheme. Moreover, it provides a low false alarm rate.

This letter proposes a new adaptive filtering method that uses the last L desired signal samples as an extra input vector, besides the existing input data, to reduce mean square error. We have improved the convergence rate by adopting the squared norm of the past error samples, in addition to the modified cost function. The modified variable error-data normalized step-size least mean square algorithm provides fast convergence, ensuring a small final misadjustment. Simulation results indicate its superior mean square error performance, while its convergence rate equals that of existing methods. In addition, the proposed algorithm shows superior tracking capability when the system is subjected to an abrupt disturbance.

Many signal processing systems, particularly in the multimedia and telecommunication domains, are synthesized to execute data-intensive applications: their cost related aspects -- namely power consumption and chip area -- are heavily influenced, if not dominated, by the data access and storage aspects. This paper presents an energy-aware memory allocation methodology. Starting from the high-level behavioral specification of a given application, this framework performs the assignment of the multidimensional signals to the memory layers -- the on-chip scratch-pad memory and the off-chip main memory -- the goal being the reduction of the dynamic energy consumption in the memory subsystem. Based on the assignment results, the framework subsequently performs the mapping of signals into both memory layers such that the overall amount of data storage be reduced. This software system yields a complete allocation solution: the exact storage amount on each memory layer, the mapping functions that determine the exact locations for any array element (scalar signal) in the specification, and an estimation of the dynamic energy consumption in the memory subsystem.

The self-organized microwrinkles can serve as a surface alignment layer to align nematic liquid crystals, which is primarily based on the groove mechanism. The azimuthal anchoring energy is discussed and estimated from the groove topography and the actual twist angle in the twisted nematic cell.

Cognitive radio systems offer the opportunity to improve the spectrum utilization by detecting unused frequency bands while avoiding interference to primary users. This paper proposes a new algorithm for spectrum sensing, which is an energy detector using a hybrid (adaptive and fixed) threshold, in order to compensate the weak points of the existing energy detector in the distorted communication channel environment. Simulation results are presented which show that the performance of the new proposed scheme is better than the existing scheme using a fixed threshold or an adaptive threshold. Additionally, the performance is investigated in terms of several parameters such as the mobile speed and the probability of false alarms. The simulation results also show that the proposed algorithm makes the detector highly robust against fading, shadowing, and interference.

This letter investigates an ADILC (Iterative Learning Control with Advanced Output Data) scheme for nonminimum phase systems using a partially known impulse response. ADILC has a simple learning structure that can be applied to both minimum phase and nonminimum phase systems. However, in the latter case, the overall control time horizon must be considered in the input update law, which makes the dimension of the matrices in the convergence condition very large. Also, this makes it difficult to find a proper learning gain matrix. In this letter, a new sufficient condition is derived from the convergence condition, which can be used to find the learning gain matrix for nonminimum phase systems if we know the first part of the impulse response up to a sufficient order. Based on this, an iterative learning control scheme is proposed using the estimation of the first part of the impulse response for nonminimum phase systems.

IEEE 802.15.4 is a new standard, uniquely designed for low rate wireless personal area networks (LR-WPANs). It targets ultra-low complexity, cost, and power, for low-data-rate wireless connectivity. However, one of the main problems of this new standard is its insufficient, and inefficient, media access control (MAC) for priority data. This paper introduces an extended contention access period (XCAP) concept for priority packets, also an traffic adaptive contention differentiation utilizing the XCAP (TACDX). The TACDX determines appropriate transmission policy alternatively according to the traffic conditions and type of packet. TACDX achieves not only enhanced transmission for priority packets but it also has a high energy efficiency for the overall network. The proposed TACDX is verified with simulations to measure the performances.