Department Publications

This paper studies the coverage maximization for wireless networks in which base station (BS) locations are drawn from a homogenous spatial Poisson point process, and user locations are arbitrary. A user is covered for communication if its received signal-to-noise-ratio (SNR) is above a given threshold value, and the objective is to maximize the coverage probability under per unit area power density constraints. The resulting optimization problem is solved analytically by making use of the underlying concavity in the objective function when transmissions are impaired only by a power-law bounded path loss. Our results show that the optimal transmit power per BS is independent of the power density constraint, and the solution to the optimization problem represents the Pareto optimal boundary between the power density constraint and the coverage probability. Then, these results are extended to a system in which …

The downlink performance of a two-cell relay enhanced wireless network is investigated. A single relay is shared by the two base stations in the system. The relay is assumed to be placed in a geographic region covered by both base stations. The relay station is operating in the decode-and-forward mode. Closed-form approximations which estimate the exact results extremely closely are derived for the outage probability and the ergodic rate of the system. The impact of finite rate channel state information feedback on the user ergodic rate is examined.

Delay variation or jitter is an inherent feature of packet switched communication networks due to bottlenecks. In communication systems buffering is commonly used to mitigate in real time multimedia applications at the expense of an additional delay. This method is therefore not suitable for control systems implemented over packet switched communication networks due to the additional delay which can make the system unstable. Hence, jitter modelling and management is necessary. This paper focuses on the development and experimental verification of a suitable jitter model for wireless and wired network bottlenecks. The effects of jitter are then investigated by quantifying the performance of a simulated Networked Control System (NCS). According to the results, the reduction in attenuation due to jitter compared to a jitter free benchmark ranges from approximately 0.01-0.04dB depending on the encoding type.

Vehicle tracking and surveillance is an area which is having a considerable attention in the context of security and safety. The detection and tacking of moving vehicles through multiple cameras is considered as a method of vehicle surveillance. This work addresses a problem of detecting and matching vehicles through multiple cameras. The power of GPUs are used to increase the number of video streams which can be processed using a single computer. In the detection process the Gabor filter is used as a directional filter and the SURF is used by the matcher to uniquely represent the vehicle.

A novel wireless sensor network architecture designed for gathering and managing onsite dynamic information in emergency situations is presented. The system can operate in two different states-normal and emergency, where switching between states occurs according to perception from the environment. The main functionalities of the system include perceiving, processing and sharing the gathered information within a wireless sensor network which is deployed in a multi-story indoor environment. Algorithms for sensor localization, network self-configuration as well as data filtering and prediction are studied in the characterized emergency environment. The proposed architecture will act to reduce risk in rescue operations following an emergency as well as generating early warnings of possible emergencies.

Flying and handling qualities are substantially dependent on, and this paper is described it, in terms of the stability and control characteristics of UAV. It is essential to be able to describe and quantify the stability and control parameters completely. It is absolutely essential to understand the relationship between the aerodynamics of the airframe and its stability characteristics to prolong the flight endurance and effective deployment. And this paper is described the stability analysis based on the dynamic model of the twin boom double vertical stabilizer UAV.

The Australian construction industry is identified as one among five industries to receive priority attention under the Australian Work Health and Safety Strategy 2012-2022. Among the recorded construction fatalities in 2012, vehicle incidents accounted for 15% and being hit by moving objects accounted for 10%. Tracking of individuals on-site could provide a technological solution to improve safety. This paper proposes a novel, non-tagging-based, wireless networking solution (called device-free localization) to enhance safety on site. Device free localization techniques use radio signal propagation effects such as multi-path fading and shadowing caused by the obstruction(s). The proposed solution defines zones in the construction site. Zone identification is based on the risk associated with the location map of the site. Defining risk profiles considers the activities associated with the geographic location, such as …

Early detection of hypertension generally requires continuous monitoring of blood pressure levels which is not facilitated by traditional methods such as the cuff, which cannot be used in the normal environment for continuous monitoring due to the regular pressurization of certain body parts. Thus there is a need for non-invasive continuous pressure monitoring mechanism. In this paper we present a relationship between Pulse Transit Time (PTT) and Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) for continuous pressure monitoring and its experimental validation.

Manual analysis of large volumes of video surveillance footage stemming from the widespread deployment of security cameras is error prone, expensive and time consuming. Despite the commercial availability of software for automated analysis, many products lack third party extensibility, the capability to perform simultaneous event detection and have no provision for anomaly detection in highly dense crowded scenes. We present a plugin based software system for video surveillance applications addressing these shortcomings and achieve realtime performance in typical crowded scenes. Core parameters are computed once per frame and shared among plugins to improve performance by eliminating redundant calculations. A novel multiple pedestrian tracking algorithm is incorporated into the framework to achieve the expected performance. We also propose an improvement to anomaly detection in densely …

Abnormal activity detection plays an important role in many areas such as surveillance, military installations, and sports. Existing abnormal activity detectors mostly rely on motion data obtained over a number of frames to characterize abnormality. However, only motion may not be able to capture all forms of abnormality, in particular, poses that do not amount to motion "outliers". In this paper, we propose two different spatio-temporal descriptors, a silhouette and optic flow based method and a dense trajectory based method which additionally include trajectory shape descriptor, to detect abnormalities. These two descriptors enable us to classify abnormal versus non-abnormal activities using SVM. Comparison with existing methods, using five standard datasets, shows that dense trajectory based method outperforms state-of-the-art results in crowd dataset and silhouette and optic flow based method outperforms …

Device free detection and localization is a promising and a very practical research area where installation of expensive sensors and/or tagging the intruder is not feasible. This paper reports a mesh network developed for device free trespasser detection. We use the Received Signal Strength Indicator (RSSI) measurements of the wireless links within the mesh as the sole sensing mechanism. A fingerprint of RSSI measurements characterizes the environment under normal conditions including multi-path effects. A technique to differentiate RSSI variations due to trespassers from those due to multi-path effects is demonstrated. The results of the experiments conducted in an outdoor environment have verified that the proposed method can be used to detect trespassers successfully. The reliability of the detection is improved by cross-correlating RSSI variations among the multiple links in the mesh. The ability to extend …

Multi-view video has gained widespread popularity in the recent years. 3DTV, surveillance, immersive teleconferencing and free view-point television are few notable applications of multi-view video. Excessive storage and transmission bandwidth requirements are the major challenges faced by the industry in facilitating multi-view video applications. This paper presents efficient tools for coding of multi-view video based on the state of the art single view video coding standard H.265/HEVC (High Efficiency Video Coding). Our approach employs the LDI (Layered Depth Image) representation technique which is capable of compactly representing 3D scene content. We propose techniques and algorithms for LDI construction, view synthesis, efficient coding of LDI layers and associated auxiliary information. Subjective assessments indicate that our approach offers more than 50% reduction in bitrate compared to HEVC …

In this paper, we consider a multi-cell multi-user MISO broadcast channel. The system operates according to the opportunistic beamforming framework in a multi-cell environment with variable number of transmit beams (may alternatively be referred as the transmission rank) at each base station. The maximum number of co-scheduled users in a cell is equal to its transmission rank, thus increasing it will have the effect of increasing the multiplexing gain. However, this will simultaneously increase the amount of interference in the network, which will decrease the rate of communication. This paper focuses on optimally setting the transmission rank at each base station such that a set of Quality of Service (QoS) constraints, that will ensure a guaranteed minimum rate per beam at each base station, is not violated. Expressions representing the achievable region of transmission ranks are obtained considering different …

This paper presents a performance optimized FPGA based design for low rank matrix estimation using robust principal component analysis. The system is constructed using mesh connected processor array for singular value decomposition and specialized architectures for merge sort and matrix multiplication for re-composition of the matrix which is computed iteratively. There are no prior implementations of Robust PCA on FPGA and this work presents at least a 50 times performance increment upto 2048×2048 matrices, compared to a Matlab implementation running on Core i7-3610QM, 2.3 GHz processor with 8GB RAM.

Difficult conditions on outdoor terrains make outdoor autonomy for rovers, a challenging task. The conventional wheel odometry method uses orientation measurements to assume a momentary plane to apply wheel encoder readings. On uneven terrains, this method often gives poor results for position tracking, and therefore rarely used. To improve the conventional odometry motion model, immediate terrain data can be used. This paper proposes a novel state variable extension (SVE) method to establish a connection between state space variables of a terrain rover by combining terrain point clouds with rover kinematics. The simulation results show that when the 2D state variables (x, y, yaw) are known, the 2D state can be extended to its 3D state (x, y, z, roll, pitch, yaw) with minimal error. The proposed SVE method is employed in a particle filter to determine the 2D state variables, which in turn results in achieving …

In this paper, we consider a cellular network operating according to the classical opportunistic beamforming and scheduling scheme. In a multi-cell network, interference is the main bottleneck on the communication rate, compared to noise. In this paper, we focus on deriving the ergodic downlink sum-rate scaling law for the system of interest considering an interference-limited regime (i.e., the high SNR region). More specifically, through deriving the moment generating function of the sum-rate, we show that the ergodic downlink sum-rate scales logarithmically as the number of users grows large. This result is different from the well-known double logarithmic sum-rate growth with increasing number of users due to the interference-limited assumption. Finally, numerical results are also presented to validate our analysis and provide further insights.

Transferring computational tasks from user-worn devices to everyday objects allows users to freely focus on their regular non-computing tasks. Identifying micro-activities (short-repetitive-activities that compose the macro-level behavior) enables the understanding of subtle behavioral changes and providing just-in-time information without explicit user input. In this paper, we propose the concept of micro-activity recognition of augmented-everyday-objects and evaluate the applicability of machine learning algorithms that are previously used for macro-level activity recognition. We outline a few proof-of-concept application scenarios that provide micro-activity-aware just-in-time information.

Localization is a significant consideration in a Wireless Sensor Network (WSN), as it is essential to correlate sensor information with the geographic location it originates from. The DV-Hop algorithm, being a range-free, distributed algorithm, is an attractive option in this regard, due to its simplicity. In this paper, we present two algorithms to improve the localization accuracy of the DV-Hop algorithm. The Hop Size derived through a distributed fashion by the DV-Hop algorithm is optimized using the knowledge of the position of the anchor nodes. The locations of the unknown nodes are then estimated using the optimum hop size. We examine the performance of the proposed algorithms through simulations in environments with varying node numbers, anchor ratios and radio range. The results show that the proposed algorithms have improved performance in localization accuracy and stability compared to the original …

The downlink performance of a dual-cell relay enhanced wireless network is investigated. A single relay is shared by the two base stations in the system. The relay is assumed to be placed in a region covered by both base stations. The relay station is operating in the decode-and-forward mode. Closed-form approximations which follow the exact results extremely closely are derived for the outage probability and the ergodic rate of the system.

Complex Event Processing (CEP) is an emerging field in high performance computing paradigm where real time (low latency) computing capability is expected over big data processing (high throughput). Significant number of software architectures have been developed to improve the throughput while reduce the latency but maintaining of the both aspects reaches the limits of the software platforms. This paper proposes a novel custom hardware accelerator architecture framework for CEP in big data domain. The proposed design improves the throughput performance more than 10 times over the software counterpart while keeping the latency value at less than 100 nano seconds. Same Structured Query Language(SQL) type queries used in reference software architecture were used to improve the flexibility. A query compiler based on the same query language grammar was designed to convert the queries in to …

Action recognition in a video plays an important role in computer vision and finds many applications in areas such as surveillance, sports, and elderly monitoring. Existing methods mostly rely on stationary backgrounds. Action recognition in dynamic backgrounds typically requires standard preprocessing steps such as motion compensation, background modeling, moving object detection and object recognition. The errors of the motion compensation step and background modelling increase the mis-detections. Therefore action recognition in dynamic background is challenging. In this paper, we use a combination of pose characterized by a silhouette and optic flows synthesized into a histogram. This enables us to classify the movement of the actor versus movement of the background. We use four background models to extract the silhouette from the frame. We use SVM to recognize actions, according to several …

The biological world is an ideal place for seeking inspiration for developing mathematical optimization algorithms. In this paper we propose two hybrid stochastic optimization algorithms that bear resemblance to the sexual reproduction cycle of Jellyfish and asexual reproductive cycle of species of Hydra. The performance of these two algorithms are investigated against other common optimization algorithms on a set of benchmark optimization problems. The results show that the proposed algorithms perform well.

This paper studies a cellular network in which base station (BS) locations are modeled using a homogenous spatial Poisson point process, and user locations are modeled using an arbitrary stationary homogenous point process. The objective is to maximize the Coverage-Intensity Product (CIP), which represents the average number of users covered per unit area, under constraints on transmit power, BS intensity and transmit power density (per unit area). Expressions for the CIP are obtained considering two user coverage models that differ from each other depending on the BS-user association. Using these expressions, solutions for the optimization problem are provided. All these results are presented for general bounded path loss models that satisfy some mild conditions. The results are also illustrated using a specific bounded path loss model to provide further insights.