Systems and Communications Commons^™

Impact Of Large-Scale Correlated Failures On Multilevel Virtualized Networks, Max G. Medina, Mohammed J.F. Alenazi, Egemen K. Cetinkaya

Electrical and Computer Engineering Faculty Research & Creative Works

Communication network architectures have been evolving with increased programmability and virtualization of physical infrastructures. While this evolution enables a faster introduction of new services and efficient utilization of resources, the complexities and interdependencies among the physical and virtual infrastructures, as well as the control and management planes, hinder a complete understanding of the system at hand. It is imperative, therefore, to model and study these evolving virtualized infrastructures. We propose a multilevel virtualized network embedding model and study its performance against correlated failures. Our analysis of multiple synthetic network models identified that grid-like infrastructures capture the realistic Internet2 structure the …

Magneto Inductive Communication System For Underwater Wireless Sensor Networks, Niaz Ahmed

Doctoral Dissertations

"Underwater wireless sensor networks have found a number of applications in underwater environment monitoring, infrastructure monitoring, military applications and ocean exploration. Among the four possible means of underwater wireless communication, namely acoustic, electromagnetic (EM), magneto-inductive (MI) and optics communication, MI communication enjoys the advantages of being low cost and robust equally in air, water and soil. This dissertation presents design and implementation of a low-power and low-cost MI sensor network node that is suited for long-term deployment of underwater and underground infrastructure monitoring, such as bridge scour and levee scour monitoring. The designed MI sensor node combat the directionality of …

Node Localization In Underwater Sensor Networks (Uwsn), Huai Huang

Doctoral Dissertations

"This dissertation focuses on node localization in underwater wireless sensor networks (UWSNs) where anchor nodes have knowledge of their own locations and communicate with sensor nodes in acoustic or magnetic induction (MI) means. The sensor nodes utilize the communication signals and the locations of anchor nodes to locate themselves and propagate their locations through the network.

For UWSN using MI communications, this dissertation proposes two localization methods: rotation matrix (RM)-based method and the distance-based method. Both methods require only two anchor nodes with arbitrarily oriented tri-directional coils to locate one sensor node in the 3-D space, thus having advantages in …

A Family Of Optimized Lms-Based Algorithms For System Identification, Silviu Ciochinǎ, Constantin Paleologu, Jacob Benesty, Steven L. Grant, Andrei Anghel

Electrical and Computer Engineering Faculty Research & Creative Works

The performance of the least-mean-square (LMS) algorithm is governed by its step-size parameter. In this paper, we present a family of optimized LMS-based algorithms (in terms of the step-size control), in the context of system identification. A time-variant system model is considered, and the optimization criterion is based on the minimization of the system misalignment. Simulations performed in the context of acoustic echo cancellation indicate that these algorithms achieve a proper compromise in terms of fast convergence/tracking and low mis adjustment.

Approximated Proportionate Affine Projection Algorithms For Block-Sparse Identification, Felix Albu, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper two block-sparse approximated memory improved proportionate affine projection algorithm are proposed for block sparse system identification. An approximation is used for a recently proposed family of block-sparse proportionate affine projection algorithms. It is shown that the proposed algorithms have close convergence performance to the original ones, and they are less numerically complex. An investigation of the influence of their parameters is also presented.

Selective Body Biasing For Post-Silicon Tuning Of Sub-Threshold Designs: A Semi-Infinite Programming Approach With Incremental Hypercubic Sampling, Hui Geng, Jianming Liu, Jinglan Liu, Pei Wen Luo, Liang Chia Cheng, Steven L. Grant, Yiyu Shi

Electrical and Computer Engineering Faculty Research & Creative Works

Sub-threshold designs have become a popular option in many energies constrained applications. However, a major bottleneck for these designs is the challenge in attaining timing closure. Most of the paths in sub-threshold designs can become critical paths due to the purely random process variation on threshold voltage, which exponentially impacts the gate delay. In order to address timing violations caused by process variation, post-silicon tuning is widely used through body biasing technology, which incurs heavy power and area overhead. Therefore, it is imperative to select only a small group of the gates with body biasing for post-silicon-tuning. In this paper, …

A Fast Filtering Block-Sparse Proportionate Affine Projection Sign Algorithm, Felix Albu, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a new proportionate affine projection sign algorithm for block-sparse identification using a fast recursive filtering procedure and dichotomous coordinate descent iterations is proposed. It is shown that the proposed algorithm is a good candidate for network echo cancellation systems operating under impulsive environments.

Proportionate Affine Projection Algorithms For Block-Sparse System Identification, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

A new family of block-sparse proportionate affine projection algorithms (BS-PAPA) is proposed to improve the performance for block-sparse systems. This is motivated by the recent block-sparse proportionate normalized least mean square (BS-PNLMS) algorithm. It is demonstrated that the affine projection algorithm (APA), proportionate APA, (PAPA), BS-PNLMS and PNLMS are all special cases of the proposed BS-PAPA algorithm. Meanwhile, an efficient implementation of the proposed BS-PAPA and block-sparse memory PAPA (BS-MPAPA) are also presented to reduce computational complexity. Simulation results demonstrate that the proposed BS-PAPA and BS-MPAPA algorithms outperform the APA, PAPA and MPAPA algorithms for block-sparse system identification in terms …

Proportionate Adaptive Filtering For Block-Sparse System Identification, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a new family of proportionate normalized least mean square (PNLMS) adaptive algorithms that improve the performance of identifying block-sparse systems is proposed. The main proposed algorithm, called block-sparse PNLMS (BS-PNLMS), is based on the optimization of a mixed norm of the adaptive filter's coefficients. It is demonstrated that both the NLMS and the traditional PNLMS are special cases of BS-PNLMS. Meanwhile, a block-sparse improved PNLMS (BS-IPNLMS) is also derived for both sparse and dispersive impulse responses. Simulation results demonstrate that the proposed BS-PNLMS and BS-IPNLMS algorithms outperformed the NLMS, PNLMS and IPNLMS algorithms with only a modest …

An Optimized Proportionate Adaptive Algorithm For Sparse System Identification, Silviu Ciochina, Constantin Paleologu, Jacob Benesty, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

Proportionate-type adaptive algorithms are commonly used for the identification of sparse impulse responses, like in network and acoustic echo cancellation. In this paper, we propose an optimized proportionate LMS adaptive filter in the context of a state variable model. The algorithm follows an optimization criterion based on the minimization of the system misalignment and uses an iterative procedure for computing the proportionate factors. Consequently, it achieves a proper compromise between the performance criteria, i.e., fast convergence/tracking and low mis adjustment. Simulations performed in the context of sparse system identification indicate the good behavior of the proposed algorithm.

A Low Complexity Reweighted Proportionate Affine Projection Algorithm With Memory And Row Action Projection, Jianming Liu, Steven L. Grant, Jacob Benesty

Electrical and Computer Engineering Faculty Research & Creative Works

A new reweighted proportionate affine projection algorithm (RPAPA) with memory and row action projection (MRAP) is proposed in this paper. The reweighted PAPA is derived from a family of sparseness measures, which demonstrate performance similar to mu-law and the l0 norm PAPA but with lower computational complexity. The sparseness of the channel is taken into account to improve the performance for dispersive system identification. Meanwhile, the memory of the filter's coefficients is combined with row action projections (RAP) to significantly reduce computational complexity. Simulation results demonstrate that the proposed RPAPA MRAP algorithm outperforms both the affine projection algorithm (APA) and …

Block Sparse Memory Improved Proportionate Affine Projection Sign Algorithm, J. Liu, S. L. Grant

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A block sparse memory improved proportionate affine projection sign algorithm (BS-MIP-APSA) is proposed for block sparse system identification under impulsive noise. The new BS-MIP-APSA not only inherits the performance improvement for block-sparse system identification, but also achieves robustness to impulsive noise and the efficiency of the memory improved proportionate affine projection sign algorithm (MIP-APSA). Simulations indicate that it can provide both faster convergence rate and better tracking ability under impulsive interference for block sparse system identification as compared with APSA and MIP-APSA.

An Improved Variable Step-Size Zero-Point Attracting Projection Algorithm, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an improved variable step-size (VSS) scheme for zero-point attracting projection (ZAP) algorithm. The proposed VSS is proportional to the sparseness difference between filter coefficients and the true impulse response. Meanwhile, it works for both sparse and non-sparse system identification, and simulation results demonstrate that the proposed algorithm could provide both faster convergence rate and better tracking ability than previous ones.

Selective Body Biasing For Post-Silicon Tuning Of Sub-Threshold Designs: An Adaptive Filtering Approach, Hui Geng, Jianming Liu, Pei Wen Luo, Liang Chia Cheng, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

A sub-threshold design could provide a compelling approach to power critical applications. An exponential relationship exists, however, between the delay and the threshold voltage, that makes this design-time timing closure extremely difficult, if not impossible, to achieve. Several previous studies were focused on the technique of body biasing during post-silicon tuning for delay compensation. But they were mostly for super-threshold designs where spatially correlated L eff variation dominates. They cannot be applied directly to sub-threshold designs in which purely random threshold voltage variations dominate. These works also assumed multiple body biasing voltage domains and multiple body biasing voltage levels, which …

Echo Cancellation For Bone Conduction Transducers, Mohammadhossein Behgam, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

Bone conducting transducers are attractive technologies for voice communication systems. Bone vibrators (BVs), typically located on the condyle bone, allow users to listen while leaving their outer ears open, enhancing situational awareness. Meanwhile, bone conduction microphones (BCMs), often located on the temple, increase the transmitted signal to noise ratio because they are relatively insensitive to ambient air born environmental noise. A communication headset consisting of a BV and a BCM is a natural combination of these promising technologies. The prospect of acoustic coupling between the BVs and BCMs results in acoustic echo if full-duplex communication is used. To our knowledge, …

Design And Implementation Of Low Complexity Wake-Up Receiver For Underwater Acoustic Sensor Networks, Ming Yue

Masters Theses

"This thesis designs a low-complexity dual Pseudorandom Noise (PN) scheme for identity (ID) detection and coarse frame synchronization. The two PN sequences for a node are identical and are separated by a specified length of gap which serves as the ID of different sensor nodes. The dual PN sequences are short in length but are capable of combating severe underwater acoustic (UWA) multipath fading channels that exhibit time varying impulse responses up to 100 taps. The receiver ID detection is implemented on a microcontroller MSP430F5529 by calculating the correlation between the two segments of the PN sequence with the specified …

A Generalized Proportionate Adaptive Algorithm Based On Convex Optimization, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

A general framework is proposed to derive proportionate adaptive algorithms for sparse system identification. The proposed algorithmic framework employs the convex optimization and covers many traditional proportionate algorithms. Meanwhile, based on this framework, some novel proportionate algorithms could be derived too. In the simulations, we compare the new derived proportionate algorithm with the traditional ones and demonstrate that it could provide faster convergence rate and tracking performance for both white and colored input in sparse system identification.

On Over-Determined Frequency Domain Bss, Christopher Osterwise, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces two new frequency domain overdetermined blind source separation (BSS) algorithms: Inter-frequency Correlation with Microphone Diversity (ICMD), and ICA with Triggered Principal component analysis (ITP). In the first, we consider different sets of microphones, where in each set the number of microphones and sources are equal. In the second, we extract principal components from an overdetermined mixture to form a determined mixture for separation. Both techniques utilize inter-frequency correlation to align permutations via energy profiles. Both monitor the condition number of an inter-frequency cross-correlation matrix of the normalized de-mixed signals' envelopes to determine if separation has failed for …

A New Variable Step-Size Zero-Point Attracting Projection Algorithm, Jianming Liu, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a new variable step-size (VSS) scheme for the recently introduced zero-point attracting projection (ZAP) algorithm. The proposed variable step-size ZAPs are based on the gradient of the estimated filter coefficients' sparseness that is approximated by the difference between the sparseness measure of current filter coefficients and an averaged sparseness measure. Simulation results demonstrate that the proposed approach provides both faster convergence rate and better tracking ability than previous ones. © 2013 IEEE.

On An Iterative Method For Basis Pursuit With Application To Echo Cancellation With Sparse Impulse Responses, Pratik Shah, Steven L. Grant, Jacob Benesty

Electrical and Computer Engineering Faculty Research & Creative Works

Basis pursuit has been shown to be an effective method of solving inverse problems with a small amount of data when the system to be determined has a sparse representation. Adaptive filters fall under this general category of problems. Here, we use the echo cancellation context to introduce a method of solving the basis pursuit problem with an iterative method based on the proportionate normalized affine projection algorithm (PAPA). Earlier, it has been shown that PAPA can be derived from a basis pursuit perspective. Here we refine the assumptions made in those derivations and show that an iterative form of …

Effect Of Frequency Oversampling And Cascade Initialization On Permutation Control In Frequency Domain Bss, Christopher Osterwise, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a new algorithm for addressing the permutation ambiguity in convolutive blind source separation. the proposed algorithm seeks to prevent permutations by frequency oversampling, and then exploiting the induced correlation between bins. Any remaining permutation is then corrected by beam pattern estimation. Cascade initialization is shown to improve system performance while decreasing processing time, while frequency oversampling is shown to increase performance with slight increases in computational time. the algorithm is proven robust against isotropic noise, producing an SIR improvement of 12.9 dB when the reverberation time is 260 ms, and the signals at the input are only …

Infrared And Intertial Tracking In The Immersive Audio Environment For Enhanced Military Training, Pratik Shah, Ayman Faza, Raghavendra Nimmala, Steven Grant, William Chapin, Robert Montgomery

Psychological Science Faculty Research & Creative Works

The Immersive Audio Environment (IAE) was designed to provide an effective military training facility. It's efficacy at synthesizing sounds from desired directions and also the ability to synthesize moving sounds has been previously reported. This paper discusses the addition of a tracking system to evaluate subject training performance. Numerous tracking systems have been developed for tracking in immersive environments. Some examples include using head mounted web cams, visible light cameras mounted on the support structure, or even single camera tracking as in commercially available entertainment. Our system uses a combination of an existing infrared tracking system and a specially designed …

A Comparison Of Bss Algorithms In Harsh Environments, Christopher Osterwise, Steven Grant

Electrical and Computer Engineering Faculty Research & Creative Works

This paper compares the performance of several blind source separation (BSS) algorithms in environments of varying reverberation, noise, microphone spacing, and sparsity. of particular interest are two frequency domain algorithms: one Cascaded ICA with Intervention Alignment (CICAIA), and one algorithm by Pham, Servire, and Boumaraf. the former is found to work exceptionally well in high noise, low microphone spacing environments. the latter proves to work exceptionally well in high SNR and moderate- to widely spaced arrays. in addition, while the literature on BSS algorithms is extensive, their performance under varying noise conditions has not been widely explored. Also, though usually …

Calibration And 3-D Sound Reproduction In The Immersive Audio Environment, Pratik Shah, Steven Grant, William Chapin

Electrical and Computer Engineering Faculty Research & Creative Works

The effectiveness of virtual environments depends largely on how efficiently they recreate the real world. in the case of auditory virtual environments, the importance of accurate recreation is enhanced since there are no visual cues to assist perception, as in the case of audio-visual virtual environments. in this paper, we present the Immersive Audio Environment (IAE), an easily constructible and portable structure, which is capable of 3-D sound auralization with very high spatial resolution. a novel method for acoustically positioning loudspeakers in space, which is required by the IAE for simulation of sound sources, is presented in this paper. Our …

Proportionate Affine Projection Sign Algorithms For Network Echo Cancellation, Zengli Yang, Yahong Rosa Zheng, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

Two proportionate affine projection sign algorithms (APSAs) are proposed for network echo cancellation (NEC) applications where the impulse response is often real valued with sparse coefficients and long filter length. the proposed proportionate-type algorithms can achieve fast convergence and low steady-state misalignment by adopting a proportionate regularization matrix to the APSA. Benefiting from the characteristics of l1-norm optimization, affine projection, and proportionate matrix, the new algorithms are more robust to impulsive interferences and colored input than the proportionate least mean squares (PNLMS) algorithm and the robust proportionate affine projection algorithm (Robust PAPA). the new algorithms also achieve much faster convergence …

Proportionate Affine Projection Sign Algorithms For Sparse System Identification In Impulsive Interference, Zengli Yang, Yahong Rosa Zheng, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

Two proportionate affine projection sign algorithms (APSAs) are proposed for system identification applications, such as network echo cancellation (NEC), where the impulse response is often real valued with sparse coefficients and long filter length. the proposed proportionate-type algorithms can achieve fast convergence and low steady-state misalignment by adopting a proportionate regularization matrix to the APSA. Benefiting from the characteristic of l1-norm algorithms, affine projection, and proportionate matrix, the new algorithms are robust to impulsive interferences and colored input and achieve much faster convergence rate in sparse impulse responses than the original APSA, the normalized sign algorithm (NSA), and the proportionate …

A Frequency Domain Doubletalk Detector Based On Cross-Correlation And Extension To Multi-Channel Case, Mohammad Asif Iqbal, Steven L. Grant, Jack W. Stokes

Electrical and Computer Engineering Faculty Research & Creative Works

Most teleconferencing conversations are conducted in the presence of Acoustic echoes. Typically, an adaptive filter is used to cancel the echo, with a control device called the doubletalk detector which controls the adaptation. We derive a novel test statistic for the doubletalk detection based on the cross-correlation between the microphone signal and the cancellation error for the frequency domain adaptive algorithm. the main advantage of the proposed algorithm is its simplicity and computational efficiency. We compare our results with the normalized cross-correlation based doubletalk detector proposed in [2]. We also generalize the idea of the proposed doubletalk detector (single channel) …

Novel Variable Step Size Nlms Algorithms For Echo Cancellation, Mohammad Asif Iqbal, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper we present two new variable step size (VSS) methods for adaptive filters. These vs.S methods are so effective; they eliminate the need for a separate double-talk detection algorithm in echo cancellation applications. the key feature of both approaches is the introduction of a new near-end signal energy estimator (NE-SEE) that provides accurate and computationally efficient estimates even during double-talk and echo path change events. the first vs.S algorithm applies the NESEE to the recently proposed Nonparametric vs.S NLMS (NPVSS-NLMS) algorithm. the resulting algorithm has excellent convergence characteristics with an intrinsic immunity to double-talk. the second approach is …

Block Level Link Path Design And Multilayer Via Transition Model Assembly Using S-Parameters, Francesco De Paulis

Masters Theses

"In high-speed data communication systems the complexity of link path between transmitters and receivers present a challenge for designers to maintain an acceptable bit error rate. An approach is presented in this thesis to design the link path on a block-by-block basis. The unique advantage of this approach lies on the physics-based model of each block, which then relates performance to geometry and makes design improvement and optimization possible. A tool based on the manipulation of frequency domain data has been designed to help in the design and analysis process of fast communication systems. It accepts as inputs the frequency …

Novel And Efficient Download Test For Two Path Echo Canceller, Mohammad Asif Iqbal, Steven L. Grant

Electrical and Computer Engineering Faculty Research & Creative Works

The two-path echo cancellation technique is a popular method for handling the double-talk problem in acoustic and line echo cancellation applications. the method uses two filters. a so-called background adaptive filter adapts its coefficients to predict echo all or most of the time regardless of signal activity on the near end. a second foreground filter, that also predicts the echo, receives it coefficients from the background filter, but only when the background is performing better than the foreground. Only the foreground residual echo is sent to the far-end. so any background divergence due to double-talk is not observed by the …