Uplink Scheduling in CDMA Packet-Data Systems

Uplink scheduling in wireless systems is gaining importance due to arising uplink intensive data services (ftp, image uploads etc.), which could be hampered by the currently in-built asymmetry in favor of the downlink. In this work, we propose and study algorithms for efficient uplink packet-data scheduling in a CDMA cell. The algorithms attempt to maximize system throughput under transmit power limitations on the mobiles assuming instantaneous knowledge of user queues and channels. However no channel statistics or traffic characterization is necessary. Apart from increasing throughput, the algorithms also improve fairness of service among users, hence reducing chances of buffer overflows for poorly located users. The major observation arising from our analysis is that it is advantageous on the uplink to schedule “strong” users one-at-a-time, and “weak” users in larger groups. This contrasts with the downlink where one-at-a-time transmission for all users has shown to be the preferred mode in much previous work. Based on the optimal schedules, we propose less complex and more practical approximate methods, both of which offer significant performance improvement compared to one-at-a-time transmission, and the widely acclaimed Proportional Fair (PF) algorithm, in simulations. When queue content cannot be fed back, we propose a simple modification of PF, Uplink PF (UPF), that offers similar improvement. Hereafter, we refer to users with low recieved power at the base even when transmitting at peak transmit power as “weak” users, and the strongly recieved users at the base as “strong” users. Krishnan Kumaran is currently a member of the Complex Systems Modeling section in the Corporate Strategic Research of ExxonMobil Corp., Clinton, NJ. Formerly, he was a Member of Technical Staff in the Mathematics of Networks and Systems Research Department at Bell Labs in Murray Hill, NJ, where his research interests were in modeling, analysis and simulation of design, resource management and scheduling issues in telecommunication networks. Lijun Qian is an assistant professor in the Department of Electrical Engineering at Prairie View A&M University. He received his B.S. from Tsinghua University in Beijing, M.S. from Technion-Israel Institute of Technology, and Ph.D. from WINLAB, Rutgers University, all in electrical engineering. Before joining PVAMU, he was a researcher at Networks and Systems Research Department of Bell Labs in Murray Hill, NJ. His major research interests are in wireless communications and networking technologies, especially in radio resource management, protocol design, TCP/RLP optimization and MPLS traffic engineering.     

Foveation-Based Error Resilience and Unequal Error Protection over Mobile Networks

By exploiting new human-machine interface techniques, such as visual eyetrackers, it should be possible to develop more efficient visual multimedia services associated with low bandwidth, dynamic channel adaptation and robust visual data transmission. In this paper, we introduce foveation-based error resilience and unequal error protection techniques over highly error-prone mobile networks. Each frame is spatially divided into foveated and background layers according to perceptual importance. Perceptual importance is determined either through an eye tracker or by manually selecting a region of interest. We attempt to improve reconstructed visual quality by maintaining the high visual source throughput of the foveated layer using foveation-based error resilience and error correction using a combination of turbo codes and ARQ (automatic reQuest). In order to alleviate the degradation of visual quality, a foveation based bitstream partitioning is developed. In an effort to increase the source throughput of the foveated layer, we develop unequal delay-constrained ARQ (automatic reQuest) and rate compatible punctured turbo codes where the punctual pattern of RCPC (rate compatible punctured convolutional) codes in H.223 Annex C is used. In the simulation, the visual quality is significantly increased in the area of interest using foveation-based error resilience and unequal error protection; (as much as 3 dB FPSNR (foveal peak signal to noise ratio) improvement) at 40% packet error rate. Over real-fading statistics measured in the downtown area of Austin, Texas, the visual quality is increased up to 1.5 dB in PSNR and 1.8 dB in FPSNR at a channel SNR of 5 dB.     

Acoustic emission technique for leak detection in an end shield of a pressurised heavy water reactor

This paper discusses the successful application of the Acoustic Emission Technique (AET) for detection and location of leak paths present on the inaccessible side of an end shield of a Pressurised Heavy Water Reactor (PHWR). The methodology was based on the fact that air and water leak AE signals have different characteristic features. Baseline data was generated from a sound end-shield of a PHWR for characterizing the background noise. A mock up end-shield system with saw cut leak paths was used to verify the validity of the methodology. It was found that air leak signals under pressurisation (as low as 3 psi) could be detected by frequency domain analysis. Signals due to air leaks from various locations of a defective end-shield were acquired and analysed. It was possible to detect and locate leak paths. Presence of detected leak paths were further confirmed by alternate test.     

Literature reviews in student project reports

Writing project reports is an important part of the engineering curriculum at Singapore universities. One important section of the formal report is the literature review. Most universities around the world provide guidelines on writing reviews, emphasizing that plagiarism is unethical. However, these guidelines do not offer explicit training on how to avoid plagiarism. In order to write academically acceptable reviews while avoiding copying from source materials, students face a major challenge and resort to employing various strategies to cope with the task. In this study, we examined the literature review sections of final year project reports to find out how engineering undergraduates in a Singapore university cope with writing reviews and to suggest ways in which they can extend their skills to improve their literature reviews.     

Synthesis and characterisation of N-toluyl methacrylatoethyl carbamates,homopolymers and copolymers with methyl methacrylate

The paper describes the synthesis of N-2/4-toluyl methacrylatoethyl carbamates using 2/4-toluyl isocyanate and 2-hydroxyethyl methacrylate. Homopolymerisation and copolymerisation of these novel monomers with methyl methacrylate was carried out using benzoyl peroxide as an initiator and tetrahydrofuran as solvent. Photopolymerisation of N-4-toluyl methacrylatoethyl carbamate could be carried out without the use of photosensitiser. Structural characterisation of copolymers was done using ¹H-NMR. Thermal stability of copolymers was evaluated in a nitrogen atmosphere by dynamic thermogravimetry.     

Short-term prediction of traffic flow using a binary neural network

This paper introduces a binary neural network-based prediction algorithm incorporating both spatial and temporal characteristics into the prediction process. The algorithm is used to predict short-term traffic flow by combining information from multiple traffic sensors (spatial lag) and time series prediction (temporal lag). It extends previously developed Advanced Uncertain Reasoning Architecture (AURA) k-nearest neighbour (k-NN) techniques. Our task was to produce a fast and accurate traffic flow predictor. The AURA k-NN predictor is comparable to other machine learning techniques with respect to recall accuracy but is able to train and predict rapidly. We incorporated consistency evaluations to determine whether the AURA k-NN has an ideal algorithmic configuration or an ideal data configuration or whether the settings needed to be varied for each data set. The results agree with previous research in that settings must be bespoke for each data set. This configuration process requires rapid and scalable learning to allow the predictor to be set-up for new data. The fast processing abilities of the AURA k-NN ensure this combinatorial optimisation will be computationally feasible for real-world applications. We intend to use the predictor to proactively manage traffic by predicting traffic volumes to anticipate traffic network problems.     

Gaming Social Capital: Exploring Civic Value in Multiplayer Video Games

Recent research suggests that social interactions in video games may lead to the development of community bonding and prosocial attitudes. Building on this line of research, a national survey of U.S. adults finds that gamers who develop ties with a community of fellow gamers possess gaming social capital, a new gaming‐related community construct that is shown to be a positive antecedent in predicting both face‐to‐face social capital and civic participation.     

Controllability results for damped second-order impulsive neutral integrodifferential systems with nonlocal conditions

In this paper, we establish a set of sufficient conditions for the controllability of damped second-order impulsive neutral integrodifferential systems with nonlocal initial conditions in Banach spaces. The approach used is the Sadovskii fixed point theorem combined with a noncompact condition on the cosine family of operators. An example is presented to illustrate the result.     

Energy and Trust Management Framework for MANET using Clustering Algorithm

In General, Mobile Ad-Hoc Network (MANET) has limited energy resources, and it cannot recharge itself. This research goal focuses on building a power management scheme that saves energy in the MANET. Due to power instability, there is a chance that cluster heads fail and function incorrectly in cluster-based routing. As a result, instability occurs with the cluster heads while collecting data and communicating with others effectively. This work focuses on detecting the unstable cluster heads, which are replaced by other nodes implementing the envisaged self-configurable cluster mechanism. A self-configurable cluster mechanism with a k-means protocol approach is proposed to designate cluster heads effectively. The proposed k-means procedure is based on periodic irregular cluster head rotations or altering the number of clusters. We also propose a trust management mechanism in this research to detect and avoid MANET vulnerabilities. Because of the continuously changing topology and limited resources (power, bandwidth, computing), the trust management algorithm should only use local data. Consequently, compared to traditional protocols, the proposed approach with the k-means procedure and its experimental results show lower power usage and provide an optimal system for trust management.