This letter deals with noncooperative localization of a single target using censored binary observations acquired by spatially distributed sensors. An ideal, noise-free setting is considered whereby each sensor can perfectly detect if the target is in its close proximity or not. Only those detecting sensors communicate their decisions and locations to a fusion center (FC), which subsequently forms the desired location estimator based on censored observations. Because a maximum-likelihood estimator (MLE) does not exist in this setting, current approaches have relied on heuristic, centrality-based geometric estimators such as the center of a minimum enclosing circle (CMEC). A smooth surrogate to the likelihood function is proposed here, whose maximizer is shown to approach the CMEC asymptotically as the likelihood approximation error vanishes. This provides rigorous analytical justification as to why the CMEC estimator outperforms other heuristics for this problem, as empirically observed in prior studies. Since the Cramér-Rao Bound does not exist either, an upshot of the results in this letter is that the CMEC performance can be adopted as a benchmark in this ideal setting and also for comparison with other more pragmatic binary localization methods in the presence of uncertainty.

This paper investigates the statistical properties of human motion-based harvested power, and provides models for the distribution, auto-correlation and cross-correlation of harvested power at different body locations, namely left wrist, right wrist, left ankle and waist. The models are developed based on empirical acceleration measurements while the subjects perform unscripted daily tasks. The measured accelerations are converted to harvestable power by assuming a velocity-damped resonant harvesting generator. The provided models enable realistic analysis and simulation of wearable communication systems with motion-based energy harvesting.

Localization of a non-cooperative target with binary detectors is considered. A general expression for the Fisher information for estimation of target location and power is developed. This general expression is then used to derive closed-form approximations for the Cramér-Rao bound for the case of non-coherent detectors. Simulations show that the approximations are quite consistent with the exact bounds.

We study the problem of joint optimization of Slepian-Wolf (SW) source coding and transmission rates over a Gaussian multiple access channel with the considerations of circuit power consumption and average transmit power constraint. The goal is to maximize the sample rate at the source nodes. We first derive a criterion to determine the optimality of different multiple access schemes such that the highest sample rate can be achieved at the source nodes when SW coding is used. Based on the derived optimality criterion, we propose a rate allocation procedure to determine the jointly optimal SW coding and transmission rates corresponding to orthogonal code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA) and superposition coding with successive interference cancellation (SCSIC) schemes. Several demonstrative numerical examples are provided to show the performance gain of the proposed joint rate allocation scheme.

Energy harvesting is one of the promising solutions to the problem of limited battery capacity in many wireless devices. This paper addresses the problem of system design of energy harvesting capable wireless devices in terms of the required sizes for energy and data buffers, as well as the size of the harvester, for given delay and loss requirements. We analyze the performance of an energy harvesting node, considering a stochastic model that takes into account energy harvesting and event arrival processes. We derive closed-form expressions for the probability of event loss and the average queueing delay. Our event-driven continuous time simulations validate our analytical results. Employing these results, we provide a near-optimal approach to the design of the system in terms of sizing the energy harvesting device, the energy storage, and the event queue capacity.

We investigate the statistical properties of harvested power from a human motion based harvesting device. Based on empirical measurements, during normal daily activities, we provide models for the probability density function and the autocorrelation coefficient of the harvested power. The empirical measurements are collected from an accelerometer attached to the subject's ankle. The measured acceleration is converted to the harvested power assuming a velocity-damped resonant generator harvester architecture before statistical modeling.

We consider an energy constrained wireless sensor network, with arbitrary number of nodes, where source nodes utilize Slepian-Wolf (SW) coding before transmission to a joint decoder. We investigate optimal and near-optimal SW coding rates, transmit powers, and transmit durations that maximize the number of collected samples during the network lifetime, subject to channel capacity, SW rate region, and residual energy constraints. We find optimal (near-optimal) closed-form solutions in the absence (presence) of an energy constraint at the joint decoder. We take into account the energy consumption of SW encoding and decoding and communication circuitry. Numerical results demonstrate the effectiveness of the proposed optimization, especially when the joint decoder is not energy constrained.

We investigate the problem of maximizing the sample rate at the transmitters in a wireless network using distributed source coding (DSC) and lossless transmission. With the consideration of circuit power consumption, average power constraints and DSC rate constraints, we study different orthogonal multiple access channels (MACs) and prove that the optimal orthogonal MAC is either TDMA or CDMA, depending on the joint entropy of the correlated sources, average power constraints, circuit power consumption, noise power and path loss.

An energy harvesting sensor network with a linear topology is investigated. The probability of packet loss in the network due to lack of energy in the nodes is derived. Based on this result, a near-optimal design for sizing the storage and the harvesting components of sensors is obtained. A more practical design guideline assuming identical sensors is also provided. Simulations validate the analysis and demonstrate the near optimal performance of the proposed theoretical designs.

The problem of localization of an uncooperative target with binary detectors is considered. The effect of neglecting data from (censoring) non-detecting sensors, assumed in most existing algorithms, is studied. A general analysis of the percentage of Fisher information lost due to censoring is presented. This provides a quantitative measure for deterioration of the Cramer-Rao bound due to this censoring strategy. The results are then used to quantify this loss for the case of Rayleigh fading.

As wireless sensor networks utilize battery-operated nodes, energy efficiency is of paramount importance at all levels of system design. In order to save energy in the transfer of data from the sensor nodes to one or more sinks, the data may be routed through other nodes rather than transmitting it directly to the sink(s). In this article, we investigate the problem of energy-efficient transmission of data over a noisy channel, focusing on the setting of physical-layer parameters. We derive a metric called the energy per successfully received bit, which specifies the expected energy required to transmit a bit successfully over a particular distance given a channel noise model. By minimizing this metric, we can find, for different modulation schemes, the energy-optimal relay distance and the optimal transmit energy as a function of channel noise level and path loss exponent. These results enable network designers to select the hop distance, transmit power, and/or modulation scheme that maximize network lifetime.

In this paper, we investigate the maximization of the amount of gathered data in a clustered wireless sensor network (WSN). The amount of gathered data is maximized by (1) choosing the optimal transmit power, and (2) selecting the optimal cluster head. For problem (1), we find closed-form solutions for the optimal or near optimal transmit power of cluster members (CM). For problem (2), we propose a near optimal cluster head selection (CHS) algorithm. The communication burden and computational complexity of CHS only grow linearly with the size of the cluster. In the proposed algorithms, iterations have been avoided in order to significantly lower the complexity of the algorithms compared with traditional iteration-based numerical optimization algorithms, making these approaches suitable for use in energy-constrained wireless sensor networks. The optimization gain is shown to be significant.

In this paper, we propose an iteration-free algorithm to find the optimal configuration, including transmit power and source coding rates, to maximize the lifetime of a cluster utilizing Slepian-Wolf source coding of data sent to a fusion center. Exact closed form solutions are derived when the fusion center is not energy constrained. When the fusion center is energy constrained, a near optimum solution is provided. Numerical results demonstrating the performance of the proposed algorithms are also provided.

Energy harvesting is one of the most promising solutions for the enhancing the lifetime of sensor networks by overcoming the limitations of current batter technology. This paper investigates the performance of scheduling strategies for sensor networks with energy harvesting. The problem of selecting the power level at which a sensor should transmit is formulated as a Markov Decision Process (MDP) and the performance of the transmission policy thus derived is compared with that of an energy balancing policy as well as an aggressive policy. Our results show that the quality of coverage associated with the MDP formulation outperforms the other policies.

This paper addresses the problem of developing energy efficient transmission strategies for Body Sensor Networks (BSNs) with energy harvesting. It is assumed that multiple transmission modes that allow a tradeoff between the energy consumption and packet error probability are available to the sensor nodes. Taking into account the energy harvesting capabilities of the nodes, decision policies are developed to determine the transmission mode to use at a given instant of time in order to maximize the quality of coverage. The problem is formulated as a Markov Decision Process (MDP) and the performance of the transmission policy thus derived is compared with that of energy balancing as well as aggressive policies. An upper bound on the performance of arbitrary policies, and lower bounds specific to energy balancing and aggressive policies are derived.

Impulse Radio Ultra WideBand (IR-UWB) communication has proven to be an important technique for supporting high-rate, short-range, and low-power communication. In this paper, using detailed models of typical IR-UWB transmitter and receiver structures, we model the energy consumption per information bit in a single link of an IR-UWB system, considering packet overhead, retransmissions, and a Nakagami-m fading channel. Using this model, we minimize the energy consumption per information bit by finding the optimum packet length and the optimum number of RAKE fingers at the receiver for different transmission distances, using Differential Phase-shift keying (DBPSK), Differential Pulse-position Modulation (DPPM) and On-off Keying (OOK), with coherent and non-coherent detection. Symbol repetition schemes with hard decision (HD) combining and soft decision (SD) combining are also compared in this paper. Our results show that at very short distances, it is optimum to use large packets, OOK with non-coherent detection, and HD combining, while at longer distances, it is optimum to use small packets, DBPSK with coherent detection, and SD combining. The optimum number of RAKE fingers are also found for given transmission schemes.

Impulse radio ultra-wideband (IR-UWB) communication has proven an important technique for supporting high-rate, short-range, low-power communication. These are necessary criteria for emerging sensor networks, which oftentimes have very short distance communication requirements, necessitate low power operation and may require high data rates (e.g., for supporting the transmission of images or video). In this paper, using detailed models of typical IR-UWB transmitter/receiver structures, we minimize the energy consumption per information bit in a single link of an IR-UWB system, considering packet retransmissions and overhead. This minimization is realized by finding the optimum packet length and the optimum number of RAKE fingers at the receiver for different transmission distances, using differential BPSK (DBPSK) and OOK with coherent and non-coherent detection. Our results show that at very short distances, it is optimum to use OOK with non-coherent detection and large packets, and at longer distances, it is optimum to use DBPSK with coherent detection and small packets.

In this paper we take a practical look at the design of the physical layer for multi-gigabit communication systems in the 60GHz band. We consider and compare different modulation options, while considering the regulatory as well as practical design aspects, such as the complexity of equalization and coding, requirements on the performance of the Power Amplifier (PA) and the Digital to Analog Converter (DAC) and Analog to Digital Converter (ADC).

Currently the 60 GHz band is being considered as the most attractive option for the design of very high rate (multi Gbps) short range communication systems. These systems will use antenna directionality to offset the high path loss and to achieve a higher degree of spatial reuse. Besides providing a power gain, directional antennas change the observed multipath. In this paper, we study different effects of the antenna directionality on the capacity of the 60GHz channel.

In this paper, we design Multi-Band OFDM (MB-OFDM) UWB systems, with two transmit and two receive antennas, with the goal of achieving 1 Gbps data rate. We study the performance of these systems with different modulation schemes. The Packet Error Rate (PERs) and the operating range of these systems are obtained using frequency domain baseband simulations as well as more realistic full-system simulations, and are compared to those of single antenna systems. Simulation results show that the MHVIO MB-OFDM systems provide significant gains for 1 Gbps transmission over single antenna MB- OFDM UWB systems.

Cognitive and spectrum agile radios are being considered as future wireless communication systems. These systems will have the capability of sensing their environment for active primary users and adapt their transmit signal such that any harmful interference to primary users is avoided. This paper proposes the use of a wideband windowed OFDM (WOFDM) system for the physical layer of spectrum agile radios. It is shown that by properly choosing the window the system can create very deep notches in its spectrum and, hence, avoid creating interference for the narrowband primary systems in its band. The performance of such WOFDM systems are also studied.

To exploit channel diversity without loss in transmission rate, a signal space diversity method can be used. Most existing signal space diversity techniques either require very high degree of computational complexity or have sub-optimal performance. We propose a signal space diversity technique, called Multi-QAM modulation, where data bits are directly modulated over multiple QAM constellations. We design constellation sets that not only can achieve full degree of diversity at full rate, but also allow implementation of receivers that can achieve near optimal performance with low computational complexity.

Performance of a multi-band OFDM UWB system employing two receive antennas is studied. Different antenna selection and combining methods, such as simple antenna selection, antenna selection per sub-carrier, equal gain combining and maximal ratio combining are considered. The packet error rate (PER) and the operating range of such systems is obtained using detailed realistic full-system Monte Carlo simulations, and are compared to those of a single antenna system. Simulation results show that the dual receive antenna systems provide significant gains for the higher data rate modes and moderate gains for the lower data rate modes of the multi-band OFDM UWB system

The self-cancellation scheme (SCS) has been previously proposed as an intercarrier interference (ICI) mitigation technique for OFDM systems. In this paper, we propose a more general approach called the general self-cancellation scheme (GSCS). In this technique, windowing is used to reduce the ICI resulting from the frequency shifts. After describing the system, we use a numerical method to calculate the bit error rate of the system in presence of a fixed frequency shift. We also study the performance of the system when ICI is generated as a result of channel fading. The results demonstrate that the proposed system performs better than the conventional and SCS systems, both in the presence of an oscillator frequency offset and when ICI is created as a result of channel fading.

We obtain an analytical result for the symbol-error rate of a wireless orthogonal frequency-division multiplexing system employing Fischer's bit-loading algorithm. First we assume that the subchannel coefficients are statistically independent, then we extend the results to the case with dependent subchannel coefficients. Throughout the analysis, we assume that the number of subchannels is large, and that subchannels have Rayleigh-distributed coefficients. The comparison of analytical and simulated results shows that the approximation error is small, especially at low noise and high bit rate.

A novel reception method for OFDM systems, based on the use of multiple local oscillators at the receiver is proposed. In this method the received signal is down-converted using multiple oscillators with slightly different frequencies. The down-converted signals are then combined before the OFDM demodulation takes place. The signal-to-inference ratio and bit error rate performance of the proposed system has been obtained and compared to those of the existing systems. It has been shown that a higher frequency offsets the proposed method can provide better performance.

In this paper, we investigate the effect of varying the processing gain in place of power control in a CDMA packet radio network. The classic CDMA protocol is modified to accommodate the variable processing gain, allowing for variable packet durations due to variable processing gain. The performance of the variable processing gain system is measured in terms of the network throughput and is compared to the performance of conventional fixed rate CDMA systems in which perfect power control is assumed. Results are first generated for a terrestrial CDMA network and extended to a low Earth orbit satellite (LEOS) communication topology. In the interference limited CDMA network, we have demonstrated that processing gain control can be used in place of power control and, depending on the details of the implementation, can achieve the same or nearly the same throughput performance.