Nasreen Badruddin

Maximizing the Sum Rate in Symmetric Networks of Interfering Links

We consider the power optimization problem of maximizing the sum rate of a symmetric network of interfering links in Gaussian noise. All transmitters have an average transmit power constraint, the same for all transmitters. This problem has application to DSL, as well as wireless networks. We solve this nonconvex problem by indentifying some underlying convex structure. In particular, we characterize the maximum sum rate of the network, and show that there are essentially two possible states at the optimal solution depending on the cross-gain (√ε) between the links, and/or the average power constraint: the first is a wideband (WB) state, in which all links interfere with each other, and the second is a frequency division multiplexing (FDM) state, in which all links operate in orthogonal frequency bands. The FDM state is optimal if the cross-gain between the links is above 1/√2. If √ε <; 1/√2, then FDM is still optimal provided the SNR of the links is sufficiently high. With √ε <; 1/√2, the WB state occurs when the SNR is low, but as we increase the SNR from low to high, there is a smooth transition from the WB state to the FDM state: For intermediate SNR values, the optimal configuration is a mixture, with some fraction of the bandwidth in the WB state, and the other fraction in the FDM state. We also consider an alternative formulation in which the power is mandated to be frequency flat. In this formulation, the optimal configuration is either all links at full power, or just one link at full power. In this setting, there is an abrupt phase transition between these two states.

Brain activation during cognitive tasks: An overview of EEG and fMRI studies

Brain controls all body functions that enable us to perform daily life events dynamically. Memory is an important part of brain that controls and processes our present and past information and interconnects with future plans to assist corresponding dynamic activities of whole body. In cognitive psychology, human memory processes are functionally divided into three categories namely encoding, retention, and recalling. This paper provides an overview of memory processes and brain regions that are activated during these processes using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We discussed issues related to cognitive tasks design that may be helpful in future memory research to conduct experiment with EEG and fMRI in a better way.

An Enhanced Detection Technique for Spectral Amplitude Coding Optical CDMA Systems

In this letter, we investigate the use of the multiphotodiode balanced detection (MPBD) scheme proposed by Williams in IEEE Photonics Technology Letters, (volume 8, pages 148-150, January 1996), to reduce phase-induced intensity noise (PIIN) in spectral amplitude coding optical code-division multiple access (SAC OCDMA). The MPBD is based on balancing the power reaching the balanced detector by utilizing multiple numbers of photodiodes. Since PIIN is signal dependent, by reducing the power reaching each photodiode, the overall PIIN can be reduced. Results show that MPBD outperforms the conventional balanced detector at a cost of added complexity.

Automatic eye-blink artifact removal method based on EMD-CCA

This research proposes a new hybrid algorithm for automatic removal of eye blink artifact from EEG data based on empirical mode decomposition (EMD) and canonical correlation analysis (CCA). The validity and efficiency of the proposed algorithm is evaluated using correlation coefficient and signal-to-artifact ratio (SAR) and the proposed algorithm is also compared with other popular eye blink artifact removal techniques (CCA, ICA, EMD-ICA) on simulated EEG data of two channels. From the simulation results, the average correlation coefficients for the EEG channels are obtained as 0.908 and 0.864 respectively. The SAR of the EEG signal also improved from 2.2 dB to 6.0 dB after correction using our proposed method. Compared to other eye blink artifact removal techniques, our proposed method has two benefits. Firstly, no visual inspection is required to detect the eye blink artifact components. Secondly, computational assessment of corrected EEG waveforms reveals that the proposed algorithm retrieves the EEG data by removing the eye blink artifacts reliably.

EEG mean power and complexity analysis during complex mental task

The aim of this study was to investigate the association between EEG measures (mean power and sample entropy) and complex mental reasoning task (IQ test). Six healthy university students participated voluntarily in the experiment. EEG was recorded at resting states (eye open and eye closed) and during performing IQ test and analyzed over 12 regions across the scalp. EEG mean power measure of delta and theta frequency significantly (p<;0.025) discriminated the IQ test from resting states at frontal regions and alpha frequency at parietal, occipital and parieto-occipital regions. Highly reduced mean power of beta frequency was found during IQ test at parietal, occipital and parieto-occipital regions as compared to frontal regions. Results of Sample Entropy (SE) showed high complexity in EEG signal during IQ test than resting state eye closed. Our findings showed high cortical activation and increased EEG complexity during IQ test than resting states.

A method for automatic removal of eye blink artifacts from EEG based on EMD-ICA

The electroencephalography (EEG) recordings are mostly contaminated by eye blink artifacts. It is very difficult to analyze and interpret the EEG signal due to frequent occurrence of the eye blink artifact. In this paper, a new hybrid algorithm that automatically removes the eye blink artifact from the EEG, based on Empirical Mode Decomposition (EMD) and Independent Component Analysis (ICA) is proposed. The proposed algorithm is evaluated on simulated EEG to calculate correlation coefficient and signal-to-artifact ratio (SAR). A non-corrected EEG was simulated to have a SAR of -19.1673 dB. From the simulation results, the highest average correlation coefficient and SAR of corrected EEG from non-corrected EEG are obtained as 0.871094 and 2.71645 dB respectively by applying proposed algorithm. The results demonstrate that proposed method recovers the EEG data by removing the eye blink artifacts reliably. In addition, the proposed method is applied on real spontaneous EEG data with eye blink artifact.

Capacity improvement in a CDMA system using relaying

This paper presents an approach that uses relaying to increase CDMA cellular capacity (spectral efficiency). The key insight is that, since the power received by the mobile falls off rapidly, as a function to distance to the base station, relaying could potentially be used to eliminate the out-of-cell interference, thus increasing the cellular capacity. However, as the paper shows, achieving the increase in capacity requires a specific relaying architecture, which can successfully control the interference at the relay stations. This architecture is shown to achieve up to 20% increase in CDMA cellular capacity, when shadowing effects are absent.

Mental stress assessment using simultaneous measurement of EEG and fNIRS.

Previous studies reported mental stress as one of the major contributing factors leading to various diseases such as heart attack, depression and stroke. An accurate stress assessment method may thus be of importance to clinical intervention and disease prevention. We propose a joint independent component analysis (jICA) based approach to fuse simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) on the prefrontal cortex (PFC) as a means of stress assessment. For the purpose of this study, stress was induced by using an established mental arithmetic task under time pressure with negative feedback. The induction of mental stress was confirmed by salivary alpha amylase test. Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% compared to EEG alone and +11% compared to fNIRS alone. Similar improvements were also observed in sensitivity and specificity of proposed approach over unimodal EEG/fNIRS. Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to assess mental stress objectively.

Brain Behavior in Learning and Memory Recall Process: A High-Resolution EEG Analysis

Learning is a cognitive process, which leads to create new memory. Today, multimedia contents are commonly used in classroom for learning. This study investigated brain physiological behavior during learning and memory process using multimedia contents and Electroencephalogram (EEG) method. Fifteen healthy subjects voluntarily participated and performed three experimental tasks: i) Intelligence task, ii) learning task, and iii) recall task. EEG was recorded duration learning and memory recall task using 128 channels Hydro Cel Geodesic Net system (EGI Inc., USA) with recommended specifications. EEG source localization showed that deep brain medial temporal region was highly activated during learning task. EEG theta band in frontal and parietal regions and gamma band at left posterior temporal and frontal regions differentiated successful memory recall. This study provide additional understanding of successful memory recall that complements earlier brain mapping studies.

Maximising sum rate for two interfering wireless links

In this paper, we consider the problem of maximising the sum rate of two interfering links in Gaussian noise. We assume no fading and that interference is treated as worst-case Gaussian noise, and that the optimal power allocation must be time-invariant. We show that either both links must operate at maximum power, or one link operates at maximum power and the other link is switched off. The switching point between one power scheme to another depends on the value of gamma which is the SNR of the link, as well as the channel gains at all links.