This PDF file contains the front matter associated with SPIE Proceedings Volume 8061, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

The future of metering networks requires adaptation of different sensor technology while reducing energy exploitation. In this paper, a routing protocol with the ability to adapt and communicate reliably over varied IEEE standards is proposed. Due to sensor's resource constraints, such as memory, energy, processing power an algorithm that balances resources without compromising performance is preferred. The proposed A-PEARL protocol is tested under harsh simulated scenarios such as sensor failure and fading conditions. The inherent features of A-PEARL protocol such as data aggregation, fusion and channel hopping enables minimal resource consumption and secure communication.

In this paper, we consider the use of cooperative communications for broadcast wireless networks where the signal transmitted from a source node is relayed by a relay to the destination users, which are distributed within a circular area. The objective of this paper is, given the available resources, to properly determine the position of the relay so that the worst-case outage probability performance within the service area is minimized. The problem is solved through the use of semidefinite relaxation.

Quality-of-service (QoS) metrics for sensor types in a wireless sensor network (WSN) can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, congestion, etc. These QoS metrics are typically set by the application layer of the protocol stack. Application-layer metrics, in turn, depend on the support from lower protocol layers: session, transport, network, data link (MAC), and physical. Protocol dependencies of QoS metrics motivate a cross-layer design approach to QoS optimization for heterogeneous sensor types in a WSN. Cross-layer interactions in the protocol are represented, in previous work by the author, by a set of concatenated parameters and resource levels. The "best" cross-layer designs that optimize QoS are established by applying the general theory of martingale representations to parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of WSN behavior through cross-layer design is realized through parametric factorization of stochastic conditional rates of the MVPPs. Cross-layer parameters that optimize QoS are determined in solutions to stochastic dynamic programming conditions derived from models of transient flows of heterogeneous data. Adaptive transmit beamforming, simplified as sectored antennas, and rate control at sensor nodes are introduced to enhance the performance metrics of successful throughput, known as "goodput", congestion, capacity, etc. Adaptive antenna and rate controls are parametrized in realtime cross-layer models of WSN dynamics. Simulations demonstrate that adaptive antenna directionality and rate allocations improve overall QoS performance of a baseline design without such adaptation.

Obtaining the desired signals in wireless sensor networks can be challenging due to various constraints on sensor placement or deployment. Retrieving the information accurately from sensors placed at non-uniform locations, is a problem of sensor communication and signal interpolation. In this research, the optimal recovery (OR) method, a deterministic framework that can use a priori bandwidth or spectral shape information, is used to interpolate from the given non-uniformly spaced samples. The error to be minimized is the maximum possible norm difference over a set of feasible signals. In the OR problem formulation and solution, the role of worst case feasible signals can be recognized but these signals are very difficult to find analytically. Computer simulations of feasible signals can help to produce estimates of the theoretical minimal worst-case error bounds. In this paper, monitoring of OR error bounds serves to assess sensor deployment configuration quality and to optimize the placement of additional sensors. Starting from an initial configuration of sensors, optimal deployment of additional sensors is clearly a more powerful option than random deployment of such sensors. These two approaches are compared and contrasted to show the improvement that is possible using the OR framework for one-dimensional and two-dimensional signals.

This paper focuses on the performance of cochannel interference (CCI) which is the primary factor to limit the capacity of wireless communication systems. Several cellular network architectures have been proposed in the literature to reduce the cochannel interference, but none of them appears to effectively tackle this problem. Microzoning is the technique, where the cells are further divided into smaller zones. The advantage of this technique is that the cochannel interference in the cellular system is reduced because the cell maintains a particular coverage radius. The objective of this paper is to analyze the performance of cochannel interference on the reverse channels of the proposed microzone based CDMA cellular systems operating with perfect power control in an effort to reduce the cochannel interference. Simulation results showed that the proposed technique can effectively minimize cochannel interference and the proposed architecture can be used for practical applications.

This paper presents novel receiver processing for wideband continuous phase modulation (CPM). It is shown that a relatively simple basis function expansion can be used to reduce the receiver complexity for channel estimation and equalisation of CPM signals. Simulation results show that, in general, only two orthogonal basis functions are required in the receiver irrespective of the parameters for the transmitted CPM waveform. In addition, error rate performance curves demonstrate a robust frequency domain equaliser for multipath channels when compared to more traditional time domain techniques.

This paper will investigate the bit error rate (BER) performance of coded and interleaved continuous phase modulation (CPM) waveforms on multipath channels. Coded and interleaved CPM waveforms offer some very attractive performance benefits since the CPM waveform can be viewed as rate 1 recursive inner code which can be concatenated with an outer convolutional code and when iteratively decoded, achieve performance close to the Shannon bound. This paper will begin with a brief overview of CPM waveforms. Then, an investigation into several features of CPM waveforms such as spectral characteristics, uncoded performance and iterative decoded performance will be provided. Following this, the optimum CPM demodulator for use on multipath channels will be described and its BER performance evaluated for a few multipath channels. This paper will conclude with a brief summary of the results.

Constant Envelope, Spread Spectrum Modulation is highly desirable for low-power, battery-operated systems. It has been demonstrated that Hybrid CPM is a constant envelope modulation with similar frequency diversity properties to the standard spread-spectrum m-PSK DSSS and spread-MSK modulation schemes while retaining a superior emissions profile. This paper continues the analysis of the novel constant envelope spread spectrum modulation technique with an analysis of the commonly utilized rake receiver signal processing. Initially, a simple channel model is developed to illustrate and compare the convergence of the channel estimate over a fixed, non-time-varying channel. A more complex, wireless channel model is then developed and a new corresponding method for channel estimation created. A Monte- Carlo simulated bit error rate performance of Hybrid CPM is then generated to evaluate the overall performance of the Hybrid CPM modulation scheme.

Geo-security service, which refers to the authorization of persons or facilities based on their distinctive location information, is an application of the fields of position, navigation and time (PNT). Location features from radio navigation signals are mapped into a precise verification tag or geotag to block or allow certain action or access. A device that integrates a location sensor and geotag generation algorithm is tamper-resistant, that is, one cannot spoof the device to bypass the location validation. This paper develops a theoretical framework of the geotag-based positioning and security systems, and evaluates the system performance analytically and experimentally by using Loran signals as a case study.

We proposed in our previous work an iterative minimum-mean-square-error (MMSE) cooperative positioning algorithm. MMSE cooperative positioning method achieves better root-mean-square-error (RMSE) performance than existing classical estimators. And it is implemented in an iterative pattern so as to circumvent the intense computation burden of the numerical multiple integral computation methods. The basis of the proposed iterative MMSE method is the single-node MMSE, which is actually the special case of the MMSE cooperative method when the number of node N being 1. In this work, we study the properties of the single-node MMSE and accordingly propose three variants of the original algorithm to improve the performance. The single-node MMSE and its variants can also be used to produce initial position estimation for the maximum likelihood estimator (MLE), one of the most popular existing classical estimators, and achieve almost the same performance as using true positions as the initial positions.

This paper presents a novel density-based geolocation algorithm for locating a non-cooperative radio emitter using measurements of the power difference of arrival (PDOA), also known as received signal strength difference (RSSD). Consider a 2D space in a Cartesian coordinate system with N sensors and one stationary radio emitter and assume that the distance from a sensor to the radio emitter is the hypotenuse of a right triangle. For any combination of three sensors, there exists a system of three Pythagorean equations that can be transformed into a system of three circle equations whose centers and radii are related to the corresponding PDOA measurements. The intersections of the circles represent possible locations for the radio emitter. For N sensors, we can have a maximum of N(N-1) intersections of the circles. Dividing the 2D space into a grid, each grid cell contains a certain number of intersections. This method finds the grid cell with the highest intersection density and uses the center of this cell as the position fix estimate. MATLAB-based numerical simulations were used to evaluate the performance of this algorithm for various scenarios and parameters.

Based on the symmetrically distributed array (SDA) structure and the resultant generalised conjugate symmetric property of its optimum weight vector, a transformation matrix is introduced to preprocess the received array data, after which the original complex-valued optimum weight vector is reduced to a real-valued one, so that in the following weight adaptation we can simply remove imaginary part of the weight vector. As a result of this regularization, improved performance is achieved with much lower computational complexity. There is an undetermined phase factor in the transformation matrix and two different cases are studied with beamforming examples provided for each case, supported by simulation results.

In wideband beam steering, when we need to change the beam direction frequently, the most convenient and flexible way is through digital circuits via FIR/IIR filtering. However this becomes infeasible when the signal frequency and bandwidth are extremely high. To solve this problem, instead of sampling the signals in the temporal domain for digital processing, we sample the signals spatially with more sensors positioned behind the original array of sensors. The spatially sampled signals are then processed using simple analogue circuits (variable gain amplifiers) to form the required steering delays. The delay between the spatially sampled signals is dependent on the sensor spacing and the directions of the designed beams, and is not limited by signal frequency. Design examples are provided to show that different delays can be effectively realised by a spatial filtering system to steer a nominal beam to required directions.

In our previous paper, we studied a model of location based service (LBS) in a wireless sensor network. In this paper, we study a post-data process of the motion-trace data of an object with the proposed model, which is based on the aforementioned model. Compared with the one which uses a single model to describe the motion traces, the Interacting Multiple Model (IMM) with Unscented Kalman lter (UKF) provides a powerful framework when tracking a motion object with the position service in a LBS tracking system. We study an UKF based algorithm applied to smooth the trace of a positioned object. The implementation of the locating device and the experiments conducted in the real applied scenarios are described in this paper.

This paper presents a novel algorithm for self-mapping of the cricket motes that can be used for indoor navigation of autonomous robotic systems. The cricket system is a wireless sensor network that can provide indoor localization service to its user via acoustic ranging techniques. The behavior of the ultrasonic transducer on the cricket mote is studied and the regions where satisfactorily distance measurements can be obtained are recorded. Placing the motes in these regions results fine-grain mapping of the cricket motes. Trilateration is used to obtain a rigid coordinate system, but is insufficient if the network is to be used for navigation. A modified SLAM algorithm is applied to overcome the shortcomings of trilateration. Finally, the self-mapped cricket motes can be used for navigation of autonomous robotic systems in an indoor location.

An improved antenna circuit model is presented, which utilizes a transmission line to rotate s11 values to better fit measured data. Antennas are frequently modeled as either a series or parallel resonant circuit, the results of which are only exact over a small range of frequencies in the vicinity of resonance. These simple models are inadequate at frequencies distant from the antenna resonant frequency, however. Single-point matching, which preserves impedance match near resonance, cannot be used to design matching networks where there is a requirement to operate on frequencies other than the natural resonant frequency of the antenna, while maintaining a good impedance match. This paper describes an antenna model that uses a transmission line as a modeled circuit component. The transmission line allows the modeled impedances to be rotated about the Smith chart (transformed) in such a way as to closely match measured antenna impedance data from a vector network analyzer. The resulting matching network is valid over a very wide range of frequencies and allows precision matching networks (within a measurement error of ~2%) to be created. Measured results from a variety of antennas show high correlation with the theoretical circuit model.

The visible light communication (VLC) systems using light emitting diodes (LEDs) has been a promising transmission technology to complement wireless communications. In this work, a spectrum sensor array is proposed to be implemented on the receiver side. Following the concept of multi-antenna communication systems, signal fusion algorithm is presented. By proper design of the weighting for each individual spectrum sensor, the effective output signal to interference ratio (SIR) can be maximized and hence make interference rejection possible.

The objective of this paper is to develop the theory for integrating magnetometer measurements with an existing inertial navigation system (INS) aided by an acoustic wireless sensor network. The system without magnetometer measurements provides position information reliably. However, in the absence of dynamic motion the orientation errors are not observable using the sensor network, which only provides position information. The magnetometer provides consistent observability of the orientation. The measurement model needed to estimate the orientation errors using the magnetometer is derived in this paper. This measurement model is integrated with measurements from the acoustic sensor network into a complimentary Kalman filter that is used to estimate the error states of an INS.

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 soft 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. Bit Interleaved Coded Modulation with Iterative Demodulation (BICM-ID), which is a similar iterative coding system that allows full coherent processing, will be analyzed and compared to the DPSK BCJR iterative system. Monte Carlo simulation results will be shown for the Additive White Gaussian Noise (AWGN) and Rayleigh fading channels.

This paper describes the use of multiple-input, multiple-output (MIMO) communication technology as a radio frequency (RF) sensor. We suggest some possible measures for determining how the changes in MIMO channel are related to objects moving through the MIMO channel. Initially, we examine the singular values of the channel matrix. We further demonstrate the effects of the signal-to-noise ratio (SNR) in conjunction with the target physical properties in the creation of eigenchannels. These eigenchannels represent the key factor in the ability of a MIMO system to perform as an effective sensor. Another important feature of MIMO technology is that it allows us to capture spatial information about the target, beyond the typical time and frequency information. Preliminary experimental results at 750 MHz demonstrate that targets can be detected and distinguished based on these simple measures. For example, a vehicular target is distinguishable from a person or groups of people. Our concept is closely related to a MIMO radar approach. However, a key difference is that we make use of the natural process of establishing a MIMO communication link rather than interrogate a specific physical region via a pulsed RF waveform. MIMO communications requires sounding of the physical environment and the creation of a channel matrix in order to maximize data throughput. We leverage this information about the area of interest already captured by the communication system. This allows the use of a MIMO system for both sensing and communication.

Orthogonal Frequency Division Multiplexing (OFDM) has been adopted in many military communications systems in recent years. Blind estimation of OFDM signals is therefore becoming imperative in surveillance and reconnaissance applications. A captured signal is oversampled for complete reception and correct estimations. Cyclostationarity of the signal is therefore introduced after oversampling. In this paper we propose a cyclostationarity-based two-step progressive algorithm to precisely estimate the sampling rate of an oversampled OFDM signal with low computational complexity. In the first step, a frequency segment of the cyclo-spectrum which contains the interested cyclic frequency is roughly determined by a coarse estimation using small-size FFT to minimize the computational complexity. In the second step, a fine estimation is carried out over the selected frequency segment using zoom fast Fourier transform (ZFFT) to improve the estimation accuracy with comparatively low computational complexity. Other OFDM system parameters are also estimated subsequently. Simulation results confirm the improvements of the estimation precision and computational efficiency of the proposed algorithm.