This PDF file contains the front matter associated with SPIE Proceedings Volume 7706, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

The metrics of quality of service (QoS) for each sensor type in a wireless sensor network can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, etc. These QoS metrics are typically set at the highest, or application, layer of the protocol stack to ensure that performance requirements for each type of sensor data are satisfied. Application-layer metrics, in turn, depend on the support of the lower protocol layers: session, transport, network, data link (MAC), and physical. The dependencies of the QoS metrics on the performance of the higher layers of the Open System Interconnection (OSI) reference model of the WSN protocol, together with that of the lower three layers, are the basis for a comprehensive approach to QoS optimization for multiple sensor types in a general WSN model. The cross-layer design accounts for the distributed power consumption along energy-constrained routes and their constituent nodes. Following the author's previous work, the cross-layer interactions in the WSN protocol are represented by a set of concatenated protocol parameters and enabling resource levels. The "best" cross-layer designs to achieve optimal QoS are established by applying the general theory of martingale representations to the parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of network behavior through the cross-layer design is realized through the parametric factorization of the stochastic conditional rates of the MVPPs. The cross-layer protocol parameters for optimal QoS are determined in terms of solutions to stochastic dynamic programming conditions derived from models of transient flows for heterogeneous sensor data and aggregate information over a finite time horizon. Markov state processes, embedded within the complex combinatorial history of WSN events, are more computationally tractable and lead to simplifications for any simulated or analytical performance evaluations of the cross-layer designs.

We describe a low-cost, low-power wireless sensor network we are developing for high time-resolution (ns-scale) characterization of particle showers produced by ultra-high-energy (UHE) cosmic rays, to infer shower direction at sites where hard-wired data connections may be inconvenient to install. The front-end particle detector is a scintillator block monitored by a photomultiplier tube (PMT). We keep the sensor nodes synchronized to within 1 ns using periodic highintensity optical pulses from a light-emitting-diode (LED) overdriven at very high current (~30 A) in short (4 ns) bursts. With minimal optics, this signal is resolvable under free-space transmission in ambient light conditions at multi-meter distances using a high-speed avalanche photodiode (APD) receiver at each node. PMT pulse waveforms are digitized relative to this precise time reference on a Field Programmable Gate Array (FPGA) using a Time-over-Threshold (ToT)/Time-to-Digital Converter (TDC) digitizer developed at BNL. A central server receives timestamped, digitized PMT pulse waveforms from the sensor nodes via Wi-Fi and performs real-time data visualization & analysis. Total cost per sensor node is a few thousand dollars, with total power consumption per sensor node under 1 Watt, suitable for, e.g., solar-powered installations at remote field locations.

The large-scale wireless sensing data collected from wireless networks can be used for detecting intruders (e.g., enemies in tactical fields), and further facilitating real-time situation awareness in Army's networkcentric warfare applications such as intrusion detection, battlefield protection and emergency evacuation. In this work, we focus on exploiting Received Signal Strength (RSS) obtained from the existing wireless infrastructures for performing intrusion detection when the intruders or objects do not carry any radio devices. This is also known as passive intrusion detection. Passive intrusion detection based on the RSS data is an attractive approach as it reuses the existing wireless environmental data without requiring a specialized infrastructure. We propose a clustering-based learning mechanism for passive intrusion detection in wireless networks. Specifically, our detection scheme utilizes the clustering method to analyze the changes of RSS, caused by intrusions, at multiple devices to diagnose the presence of intrusions collaboratively. Our experimental results using an IEEE 802.15.4 (Zigbee) network in a real office environment show that our clustering-based learning can effectively detect the presence of intrusions.

Medical sensor network consist of heterogeneous nodes, wireless, mobile and wired with varied functionality. The resources at each sensor require to be exploited minimally while sensitive information is sensed and communicated to its access points using secure data mules. In this paper, we analyze the flat architecture, where different functionality and priority information require varied resources forms a non-deterministic polynomial-time hard problem. Hence, a bio-inspired data mule that helps to obtain dynamic multi-objective solution with minimal resource and secure path is applied. The performance of the proposed approach is based on reduced latency, data delivery rate and resource cost.

The next Generation IEEE 802.11n is designed to improve the throughput of the existing standard 802.11. It aims to achieve this by increasing the data rate from 54 Mbps to 600 Mbps with the help of physical layer enhancements. Therefore, the Medium Access Layer (MAC) requires improvements to fully utilize the capabilities of the enhanced 802.11n physical layer. In this paper, we present the performance evaluation results of two frame aggregation schemes viz., MAC Protocol Data Unit Aggregation (A-MPDU) and MAC Service Data Unit Aggregation (A-MSDU) and study their performance impact when the two schemes are incorporated in a p-persistent based 802.11n. The simulation results have shown that the two schemes achieve consistent performance improvement over the standard non-aggregation scheme.

In this paper, a new space-time signaling scheme is proposed for Orthogonal Frequency Division Multiplexing (OFDM) using complementary sequences derived from the rows of the DFT matrix. The autocorrelative properties of the complementary sequences allows multiple complex data signals at the transmitter with an arbitrary number of antennas to be perfectly separated and reconstructed at the receiver without prior channel knowledge while achieving full-rate. This new method is proposed and derived for multiple MIMO-OFDM systems with multipath fading; at the receiver, symbol estimation is effected via maximum likelihood estimation (ML).

Power Amplifiers (PAs) are typically used to convert low-power Radio Frequency (RF) signals into high-power RF signals. Most wireless communications systems employ power amplifiers in order to increase the operating range of the system. However, this conversion process can have some undesired effects on the underlying physical layer waveforms which are used to communicate the digital information. This paper will investigate the effects of power amplifiers on the two most popular waveform design techniques used for the transmission of digital data over wireless channels: singlecarrier and multi-carrier. Of main interest will be the effects caused by PAs to each waveform's out-of-band emissions, average and peak transmit power, received signal-to-noise ratio (SNR) and Bit Error Rate (BER) performance.

A radio frequency communication wireless system can be localized using received signal strength measurements for indoor applications. Collaborative techniques such as multidimensional scaling have been shown to overcome significant ranging errors on a single floor. However, such techniques are highly sensitive to modeling mismatches including transmit power variation and path loss exponent especially when the signal goes through additional attenuation through floors indoors. In this paper, we examine an iterative joint estimator which jointly estimates location and path loss exponent for different users. Numerical results show superior performance in three dimensions when multiple floors are considered.

Over the past few years, several wireless location detection algorithms have been proposed in the literature. However, an effective solution for CDMA-based wireless communication system is yet to be found. In this paper, a position location estimation technique for CDMA wireless communications system is proposed. The proposed technique utilizes the Chan-Ho method for solving the hyperbolic model, which provides faster solution to the hyperbolic model and does not suffer from the convergence problem. The performance of the proposed position location technique has been tested by considering different system parameters, such as channel noise and variable position of the user. Test results show that the proposed position location technique can successfully determine the position of a wireless user under various challenging scenarios.

Moving radar platforms form synthetic apertures for effective target localization. One of the important target localization techniques is to multilaterate the position of a target based on the own positions of the radar and the range estimates obtained at each radar position. In practical applications, the radar positions as well as the range estimates are subject to error due to maneuvering, timing error, as well as measurement noise. Previous works have shown that, by incorporating the semidefinite relaxation techniques which permit the use of convex optimization approaches to solve a large class of nonconvex estimation problems, improved target location estimates can be achieved over those obtained from conventional techniques, such as least square methods. In some radar applications, on the other hand, it may be advantageous to incorporate the Doppler measurements. Doppler frequency information is often complementary to range measurements in target localization and is particularly helpful when range information alone does not provide satisfactory target localization performance. In this paper, we consider the problem of target localization based on both range and Doppler estimates obtained at multiple radar locations, where such information as well as the radar locations are subject to certain random errors. Semidefinite relaxation is applied to formulate convex solutions for this problem. Simulation results are provided to demonstrate performance improvement by utilizing both range and Doppler estimates.

We propose and study an iterative minimum-mean-square-error (MMSE) cooperative localization algorithm, which achieves better root-mean-square-error (RMSE) performance than existing classical estimators. Using the received signal strength (RSS) measurements, we first derive the formulas for estimating the coordinates of position-unknown nodes. Then, we investigate the practical solutions to calculate the complicated multiple integrals involved in the formulas and propose an adaptive and iterative algorithm to circumvent the intense computation burden incurred by the numerical multiple integral computation methods. We further study the proposed MMSE cooperative localization algorithm in the scenario where pair-wise range measurements are incomplete, that is, pair-wise range measurements between certain pairs of nodes are missing. It is observed that the performance degrades at a slower speed than the reduction of the available range measurements. In other words, not much performance degradation is caused by comparatively large number of missing measurements. Therefore, we can improve the efficiency of the iterative MMSE algorithm by intentionally throwing away certain pair-wise range measurements.

In this paper, an extensive set of propagation path loss measurements within multi-floored buildings at 433 MHz, 869 MHz and 1249 MHz are presented. Parameter for use in two indoor path loss prediction models, Distance-Dependant Model (DD) and Floor Attenuation Floor Model (FAF), are derived from measurement data of three multi-floored buildings. Buildings were chosen with typical features such as rectangle footprint, square footprint and existence of an atrium within the building, respectively. Comparison of model parameters has concluded that higher attenuation is experienced by the signal within a square footprint building than rectangle footprint. Building with an indoor atrium is found to have lower path losses than buildings without atrium, when considering multi-floor transmission. 869 MHz signal attenuated at slowest rate in most of the considered environments. 433 MHz signal is found to have better floor penetration compared to other frequencies. 1249 MHz is found to attenuate at slowest rate within a straight corridor with waveguiding and line-of-sight propagation path between the transmitter and the receiver. Path loss prediction within multi-floored buildings with indoor atrium is refined by considering type of propagation path between trnamsitter and receiver. It is found that path loss of areas with line-of-sight propagation path could be modelled using parameters of same floor environment. An attenuation factor is derived and added for areas with non line-of-sight propagation path. It is shown that using this refinement, better prediction accuracy is obtained. Standard deviations of path loss prediction error are reduced as a result.

Correlative interferometric imaging relies on reconstructing object intensity by using the cross-correlation across distant sensor measurements. While Fourier inversion is commonly used, the problem can also be cast as a constrained optimization problem involving positivity and boundary constraints. This paper replaces the boundary constraint with a 1 norm constraint that is known to induce sparsity under certain conditions. An experimental example demonstrates that such constrained optimization can potentially provide reconstruction whose extent conforms closely to that of the source.

Wireless mesh networked (WMN) radios have been applied to unattended ground sensor (UGS) applications for a number of years. However, adapting commercial off-the-shelf (COTS) WMN protocols and hardware for UGS applications has not yielded the desired performance because of compromises inherent to these existing radios. As a leading provider of UGS systems, McQ Inc. has been developing custom WMN protocols and radio hardware that are adapted specifically for the unique scenarios of the UGS situation. This paper presents the McQ designs, the tradeoffs made in developing the designs, and test and performance results.

Small military units operate under stressful conditions with limited resources. A lightweight mobile surveillance system could reduce the effort to conduct sentry duties, and could help prevent ambushes or other types of attacks. We explore the use of built-in sensors and networking abilities of modern "smartphones" to fill this gap. Current smartphones use accelerometers to sense changes in orientation of the phone. This same capability can be used to detect vibrations in the ground produced by approaching footsteps or vehicles. We discuss the sensitivity of the phone, the filtering techniques, and the footstep signatures registered by the phone. We then discuss the possible deployment configurations of single and multiple sensors to create a sensor grid that can be networked together. Key concerns are ground noise, sensitivity of the phone, and distance between networked phones.

For radio communication systems powerful error correction codes are necessary to operate in noisy and fading channel conditions. Iterative forward error correction schemes like Turbo codes can achieve near Shannon capacity performance on memory-less channels and also perform well on correlated fading channels. The key to the excellent decoding performance of the Turbo coding systems is the BCJR algorithm in conjunction with the iterative processing of the soft decision information. A very popular modulation technique is Differential Phase Shift Key (DPSK) which is not only a simple non-coherent modulation and demodulation technique, it is also a recursive rate one code. Combining DPSK with a single convolutional code structure as an iterative inner outer forward error correction system can provide excellent Turbo like performance. Monte Carlo simulation results will be shown for the Additive White Gaussian Noise (AWGN) and Rayleigh fading channels for 1, 2, 3 and 4 bits per symbol DPSK.

An arbitrarily accurate approach is used to determine the bit-error rate (BER) performance for generalized asynchronous DS-CDMA systems, in Gaussian noise with Raleigh fading. In this paper, and the sequel, new theoretical work has been contributed which substantially enhances existing performance analysis formulations. Major contributions include: substantial computational complexity reduction, including a priori BER accuracy bounding; an analytical approach that facilitates performance evaluation for systems with arbitrary spectral spreading distributions, with non-uniform transmission delay distributions. Using prior results, augmented by these enhancements, a generalized DS-CDMA system model is constructed and used to evaluated the BER performance, in a variety of scenarios. In this paper, the generalized system modeling was used to evaluate the performance of both Walsh- Hadamard (WH) and Walsh-Hadamard-seeded zero-correlation-zone (WH-ZCZ) coding. The selection of these codes was informed by the observation that WH codes contain N spectral spreading values (0 to N - 1), one for each code sequence; while WH-ZCZ codes contain only two spectral spreading values (N/2 - 1,N/2); where N is the sequence length in chips. Since these codes span the spectral spreading range for DS-CDMA coding, by invoking an induction argument, the generalization of the system model is sufficiently supported. The results in this paper, and the sequel, support the claim that an arbitrary accurate performance analysis for DS-CDMA systems can be evaluated over the full range of binary coding, with minimal computational complexity.

In this paper, we develop an adaptive sphere decoding technique for space-time coding of wireless MIMO communications. This technique makes use of the statistics of previous decoding results to reduce the decoding complexity of subsequent decoding process. Specially, we propose a method for the determination of the initial sphere radius for the decoding process of future time-frame based on a queue of records of minimum sphere radius obtained from the decoding process of previous time-frames. Concrete methods have been derived for the choice of appropriate queue sizes. Numerical experiment is performed for demonstrating the efficiency of the adaptive technique.

Packet-based communication systems, such as Time Division Multiple Access (TDMA) systems, often employ a preamble sequence to allow coarse estimation of carrier frequency offset, phase offset, and signal delay at the receiver. Successful acquisition of these parameters is of critical importance in synchronization and data demodulation. In this work, a simple preamble structure consisting of a continuous wave (CW) signal followed by a unique, continuous phase modulated (CPM) start-of-message (SOM) sequence is analyzed. Simulation results for frequency, phase and timing error are shown to compare favourably with their respective lower bounds. The required CW and SOM sequence lengths are established by statistical analysis of the effect of residual frequency error on symbol timing performance. In particular, it is shown that an iterative peak search of the SOM crosscorrelation nearly achieves the modified Cramer-Rao bound (MCRB) on symbol timing, making it an attractive option for timing acquisition with minimal overhead. In addition, the proposed preamble format and processing approach are compared to that of the MIL-188-181B standard.

Estimation of channel fading parameters is an important task in the design of communication links such as maximum ratio combining (MRC). The MRC weights are directly related to the fading channel coefficients. In this paper, we propose a subspace based parameter estimation algorithm for the estimation of the parameters of Nakagami-m fading channels in the presence of additive white Gaussian noise. Comparisons of our proposed approach are made with other techniques available in the literature. The performance of the algorithm with respect to the Cramer-Rao bound (CRB) is investigated. Computer simulation results for different signal to noise ratios (SNR) are presented.

The real-time multi-hop location system (RMLS) is a kind of service systems with a great potential in the distributed applications. The RMLS provides the precise positioning information of each node relative to one or more beacon node(s); and their absolute positions can be determined from the information. This paper study a new positioning model based on the RMLS and it applies a statistical method to increase the location's precision and enhance the robustness of a time-of-arrive(TOA)-based location system. This model has the advantage to fix the errors caused from the non-line-of-sight (NLOS) and multi-path effect (MPE); and it could be used to provide a reliable and stable location-based service for the applications, such as the scenes of an emergent logistics management and a disaster-relief emergent positioning.

Identifying coverage holes makes an important topic for optimization of quality service for wireless sensor network hosts. This paper introduces a new way to identify and describe how is the network's structure, its number of holes and its components, assuming there's a sensor covering an area where a network communication exists. The simplicial complex method and algebraic graph theory will be applied. Betti numbers and Euler characteristics will be used for a sensor network represented by a simplicial complex, and the Tutte polynomial will be used for describing visual graphs algebraically, for a complete identification.

With the increasing popularity of wireless sensor networks (WSNs) for the daily operations in both commercial and defense sectors, designing an efficient and secure query processing mechanism becomes critical to returning a reliable data response to the user in a timely manner. While recent research efforts on database based query processing dramatically improves the efficiency of query processing, another critical component, security, is still in its early stage of development. The intent of this work is to develop an efficient trust-aware querying mechanism to identify the trustworthiness of sensor nodes, while simultaneously filtering out bogus data in the querying process. Our final goal is to return the highest-fidelity data response to the user while monitoring the health of the network by flagging suspected compromised nodes. It is noted that the proposed trust-aware querying mechanism does not eliminate the utilization of any conventional cryptographic approaches, and it works as a complementary component to provide an advanced security solution with the imperfect WSN of today.

The interception of low probability of intercept signals has become increasingly difficult due to the availability of waveform agile transmitters and increased spectral bandwidth. Current detection techniques based on energy detection ignore the important cross-sensor correlation information. Additionally, existing TDOA/FDOA based localization techniques pair up the sensors and perform only pair-wise processing which is highly inefficient. To circumvent this problem we show how to use multiple spatially distributed sensors to detect and localize an emitter whose waveform is completely unknown. We present the generalized likelihood ratio detector which optimally combines the multiple sensor information for improved detection. Additionally, as part of the detector the MLE for target location is available, leading to improved localization.

Timely dissemination of information to mobile users is vital in many applications. In a critical situation, no network infrastructure may be available for use in dissemination, over and above the on-board storage capability of the mobile users themselves. We consider the following specialized content distribution application: a group of users equipped with wireless devices build an ad hoc network in order cooperatively to retrieve information from certain regions (the mission sites). Each user requires access to some set of information items originating from sources lying within a region. Each user desires low-latency access to its desired data items, upon request (i.e., when pulled). In order to minimize average response time, we allow users to pull data either directly from sources or, when possible, from other nearby users who have already pulled, and continue to carry, the desired data items. That is, we allow for data to be pushed to one user and then pulled by one or more additional users. The total latency experienced by a user vis-vis a certain data item is then in general a combination of the push delay and the pull delay. We assume each delay time is a function of the hop distance between the pair of points in question. Our goal in this paper is to assign data to mobile users, in order to minimize the total cost and the average latency experienced by all the users. In a static setting, we solve this problem in two different schemes, one of which is easy to solve but wasteful, one of which relates to NP-hard problems but is less so. Then in a dynamic setting, we adapt the algorithm for the static setting and develop a new algorithm with respect to users' gradual arrival. In the end we show a trade-off can be made between minimizing the cost and latency.

This paper reports on an integrated system of wirelessly linked radiation detectors that are sensitive to alpha, beta, gamma, and neutron radiation. The detectors use glass and quartz doped with ¹⁰B nanoparticles to detect impinging radiation producing varying optical pulses which exit the material. The varying optical pulses are differentiated by onchip pulse height spectroscopy. Signal discrimination is done with on-chip CMOS circuitry using a 0.35 μm process and a photodiode or photo-multiplier (PM) tube. On-chip CMOS interfacing is key to the production of small integrated radiation detection packages that are cheaper, more reliable, and easier to produce than assembled devices that use commercial off-the-shelf parts. CMOS packages are designed for low power consumption with maximum battery life; this lends itself to creating small, hard to detect radiation sensor packages that are easy to integrate with wireless sensor nodes. The network would use a mesh configuration and transmit real time radiation information from each node to a local hub. As a radiation source enters the coverage area, the data from sensors in the immediate area is transmitted and compared to find the location of the source. Pinpointing the source is achieved by comparing data received from each node. Radiation testing was done using ²⁴¹Am, ⁹⁰Sr, and ⁶⁰Co sources for alpha, beta, and gamma particles. Initial results show that quartz and glass scintillators doped with boron are able to detect each form of radiation. The quartz scintillator is also able to detect neutron radiation particles, which being neutral, are undetected with traditional solid state radiation detectors.

This paper evaluates the ACRi Blind Beamforming (ABB) smart antenna algorithm which addresses the significant problem caused by high-power transmitters located in close proximity to users. Current solutions are overwhelmed by the rapid increase in number and variety of strong interference sources. ABB requires less computational complexity than standard algorithms, making it feasible to be added to current and next-generation systems, and provides a highly adaptive and reliable interference-resistant communications environment. Simulations show that ABB automatically nulls jamming signals that are 20 dB to 40 dB stronger than the user signal, achieving close to the theoretically best performance despite being a blind solution (no information required about the jammer or user signal) and its low computational requirements. Systems with a limited number of antennas are evaluated because legacy and current generation systems have as little as two antennas.

This paper evaluates tracking and interference suppression performance for the ultra low computational complexity Non- Eigen Decomposition (NED) blind beamforming algorithm. Current blind beamforming algorithms require computational complexity too high for many target applications. NED does not rely on the eignenvalues and eigenvectors used by conventional algorithms and requires significantly less computations, with a total computational load of O(4M-4) per snapshot for a system with M receiving antennas by approximating the cross correlation vector of the received signals in the reference and other antennas. This technique requires neither a training sequence nor an assumption of incoherency among impinging signals. Simulations show that NED achieves comparable performance as conventional blind beamforming algorithms in tracking, interference suppression, and misadjustment.

This paper describes and evaluates the beamforming performance for a flexible sparse array smart antenna system that can be reconfigured through the use of multiple mobile robots. Current robotic systems are limited because they cannot utilize beamforming due to their limited number of antennas and the high computational requirement of beamformers. The beamforming techniques used in this paper are unique because unlike current beamformers, the antennas in the sparse array are not connected together; instead, each robot has a single antenna. This work is made possible through breakthroughs by the authors on ultra-low computational complexity beamforming and multi-mobile robot cluster control. This new beamforming paradigm provides spatial reconfigurability of the array to control its location, size, inter-antenna spacing and geometry via multi-robot collaborative communications. Simulation results evaluate the effectiveness of smart antenna beamforming techniques when 1, 2, 3, 4, and 8 robots are utilized with and without interference signals present.