Syed Amjad Ali

Efficient expression and bound for pairwise error probability in Rayleigh fading channels, with application to union bounds for turbo codes

This work provides a new exact expression for the pairwise error probability under perfect channel state information. Using this expression, the average union upper bounds for (1,7/5,7/5) and (1,5/7,5/7) turbo coding schemes are presented based on transfer function approach assuming fully interleaved Rayleigh fading channels. Derivation for the pairwise error probability leads to a compact approximation which overlaps with the exact expression. This new approximation is computationally more efficient than the existing ones, and leads to a much quicker general ion of union bounds for performance analysis.

Closed form expression and improved bound on pairwise error probability for performance analysis of turbo codes over Rician fading channels

This letter provides derivations for an exact expression and a bound on pair wise error probability over fully interleaved Rician fading channels under the assumption of ideal channel state information. The derivation which is based on the probability distribution of the sum of squared Rician random variables leads to an improved upper bound in comparison with the only known bound in literature. Pairwise error probability plots together with average union upper bounds for turbo codes having (1,7/5,7/5) and (1,5/7,5/7) generator polynomials are presented to demonstrate the effectiveness of the new results

Exact expression and tight bound on pairwise error probability for performance analysis of turbo codes over nakagami-m fading channels

This letter presents derivation for an exact and efficient expression on pairwise error probability over fully interleaved Nakagami-m fading channels under ideal channel state information at the decoder. As an outcome, this derivation also leads to a tight upper bound on pairwise error probability which is close to the exact expression. Pairwise error probability plots for different values of Nakagami parameter m along with an already existing numerically computable expression are provided. As an application of pairwise error probability, average union upper bounds for turbo codes having (1,7/5,7/5) and (1,5/7,5/7) generator polynomials employing transfer function approach are presented to illustrate the usefulness of the new efficient results

Rule Based Segmentation and Subject Identification Using Fiducial Features and Subspace Projection Methods

This paper describes a framework for carrying out face recognition on a subset of standard color FERET database using two different subspace projection methods, namely PCA and Fisherfaces. At first, a rule based skin region segmentation algorithm is discussed and then details about eye localization and geometric normalization are given. The work achieves scale and rotation invariance by fixing the inter ocular distance to a selected value and by setting the direction of the eye-to-eye axis. Furthermore, the work also tries to avoid the small sample space (S3) problem by increasing the number of shots per subject through the use of one duplicate set per subject. Finally, performance analysis for the normalized global faces, the individual extracted features and for a multiple component combination are provided using a nearest neighbour classifier with Euclidean and/or Cosine distance metrics.

A simple moment based approximation to pairwise error probability for memoryless fading channels

This paper provides a simple approximation to pairwise error probability for memoryless fading channels when there is no channel state information at the decoder. The derived approximation is independent of the fading process and depends only on the mean and variance of the fading distribution. The new approximation is considerably better than an already existing approximation and a bound for low signal to noise ratio values. It can be applied to obtain average union upper bounds for block and turbo-like coding schemes. Plots for pairwise error probability for Rician, Rayleigh and Nakagami-m fading channels along with average union upper bounds for turbo codes with (1,5/7,5/7) generator polynomial are given to illustrate improvement in already published work

Balancing Energy Loads in Wireless Sensor Networks through Uniformly Quantized Energy Levels-Based Clustering

Clustering is considered a common and an effective method to prolong the lifetime of a wireless sensor network. This paper provides a new insight into the cluster formation process based on uniformly quantizing the residual energy of the sensor nodes. The unified simulation framework provided herein, not only aids to reveal an optimum number of clusters but also the required number of quantization levels to maximize the networks lifetime by improving energy load balancing for both homogeneous and heterogeneous sensor networks. The provided simulation results clearly show that the uniformly quantized energy level-based clustering provides improved load balancing and hence, a longer network lifetime than existing methods.

Energy Load Balancing for Fixed Clustering in Wireless Sensor Networks

Clustering can be used as an effective technique to achieve both energy load balancing and an extended lifetime for a wireless sensor network (WSN). This paper presents a novel approach that first creates energy balanced fixed/static clusters, and then, to attain energy load balancing within each fixed cluster, rotates the role of cluster head through uniformly quantized energy levels based approach to prolong the overall network lifetime. The method provided herein, not only provides near-dynamic clustering performance but also reduces the complexity due to the fact that cluster formation phase is implemented once. The presented simulation results clearly show the efficacy of this proposed algorithm and thus, it can be used as a practical approach to obtain maximized network lifetime for energy balanced clusters in fixed clustering environments.

Performance analysis of turbo codes over Rician fading channels with impulsive noise

The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for additive white Gaussian noise (AWGN) channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be modified in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Rician fading channels with Middletons additive white class-A impulsive noise (MAWCAIN). Simulation results for the memoryless Rician fading channels using coherent BPSK signaling for both the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder are provided. An eight state turbo encoder having (1,13/15,13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Rician fading channels with impulsive noise rather than AWGN.

An adept segmentation algorithm and its application to the extraction of local regions containing fiducial points

Locating human fiducial points like eyes and mouth in a frontal head and shoulder image is an active research area for applications such as model based teleconferencing systems, model based low bit rate video transmission, computer based identification and recognition systems. This paper proposes an adept and efficient rule based skin color region extraction algorithm using normalized r-g color space. The given scheme extracts the skin pixels employing a simple quadratic polynomial model and some additional color based rules to extract possible eye and lip regions. The algorithm refines the search for fiducial points by eliminating falsely extracted feature components using spatial and geometrical representations of facial components. The algorithm described herein has been implemented and tested with 311 images from FERET database with varying light conditions, skin colors, orientation and tilts. Experimental results indicate that the proposed algorithm is quite robust and leads to good facial feature extraction.

On the Analysis of Expected Distance between Sensor Nodes and the Base Station in Randomly Deployed WSNs

In this study, we focus on the analytical derivation of the expected distance between all sensor nodes and the base station (i.e., E[d toBS ]) in a randomly deployed WSN. Although similar derivations appear in the related literature, to the best of our knowledge, our derivation, which assumes a particular scenario, has not been formulated before. In this specific scenario, the sensing field is a square-shaped region and the base station is located at some arbitrary distance to one of the edges of the square. Having the knowledge of E[d toBS ] value is important because E[d toBS ] provides a network designer with the opportunity to make a decision on whether it is energy-efficient to perform clustering for WSN applications that aim to pursue the clustered architectures. Similarly, a network designer might make use of this expected value during the process of deciding on the modes of communications (i.e., multi-hop or direct communication) after comparing it with the maximum transmission ranges of devices. Last but not least, the use of our derivation is not limited to WSN domain. It can be also exploited in any domain when there is a need for a probabilistic approach to find the average distance between any given number of points which are all assumed to be randomly and uniformly located in any square-shaped region and at a specific point outside this region.