Alam Zaib

• Doctor of Philosophy
• Associate Professor at COMSATS University Islamabad, Abbottabad Campus, Abbottabad

In many real classification problems where a limited number of training samples is available, the linear classifiers based on discriminant analysis are unable to deliver accurate results. Moreover, the testing and/or the training data can be erroneous due to noise contamination which further degrades their performance. Regularization techniques bec...

This paper presents a novel framework for link-level performance abstraction for multiple input multiple output (MIMO) receivers using a neural network model. The link-level performance abstraction is widely used to predict the receiver performances through a lookup table (LUT). As opposed to the classical LUT-based techniques, in the proposed neur...

The energy efficient resource allocation scheme based on genetic algorithm (GA) for the downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) is developed in this paper. To maximize the spectrum efficiency for the fifth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cel...

In this paper, a novel scheme for radio resource allocation is proposed for downlink transmission in a clustered cellular network that employs orthogonal frequency division multiple access. The proposed resource allocation scheme is based on maximizing the cluster throughput, with emphasis on improving individual performance, especially those at th...

Linear discriminant analysis (LDA) based classifiers tend to falter in many practical settings where the training data size is smaller than, or comparable to, the number of features. As a remedy, different regularized LDA (RLDA) methods have been proposed. These methods may still perform poorly depending on the size and quality of the available tra...

MIMO systems employing sphere decoding (SD) algorithm are known to achieve near maximum likelihood (ML) performance at a reduced complexity by restricting the candidate search space to a sphere of a certain radius. The performance of SD depends on the precise estimation of its soft output. In this paper, a low complexity modified Likelihood Ascent...

The objective of this work is to detect the cell phone and/or camera used by a person in restricted areas. The paper is based on intensive image processing techniques, such as, features extraction and image classification. The dataset of images is generated with cell phone camera including positive (with cell phone) and negative (without cell phone...

In [1] , the following line was missing: “Weiyu Xu and Haider Ali Jasim Alshamary contributed equally to this article.”

This paper presents link to system (L2S) interfacing technique for multiple input and multiple output (MIMO) iterative receivers. In L2S interfacing, usually the post detection signal to noise ratio (SNR)‐based frame error rate lookup tables (LUT) are used to predict the link level performance of receivers. While L2S interfacing for linear MIMO rec...

By exploiting large antenna arrays, massive MIMO (multiple input multiple output) systems can greatly increase spectral and energy efficiency over traditional MIMO systems. However, increasing the number of antennas at the base station (BS) makes the uplink joint channel estimation and data detection (JED) challenging in massive MIMO systems. In th...

Linear discriminant analysis (LDA) based classifiers tend to falter in many practical settings where the training data size is smaller than, or comparable to, the number of features. As a remedy, regularized LDA (RLDA) methods are proposed. The capabilities of these methods vary depending on the training and test data. In this paper, we propose a d...

Wireless communication systems utilizing orthogonal frequency division multiplexing (OFDM) transmissions are capable of delivering high data rates over multipath frequency selective channels. This paper deals with joint estimation/interpolation of wireless channel using pilot symbols transmitted concurrently with the data. We propose a low complexi...

In this paper, the impact of initial search radius on the complexity and performance of a sphere decoding algorithm is investigated for different user positions within a distributed antenna system. In a distributed antenna system, users can take up random positions within the cell clusters. The channel matrix can therefore take up infinitely differ...

In this paper a low-cost link level performance prediction technique is proposed for a single input and multiple output system. Receiver link level abstraction is used in system level simulations of large networks in order to reduce their complexity. Usually, a single lookup table is employed in link level abstraction to predict a receiver's perfor...

In this paper, we consider uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. With increased number of antennas, the channel estimation problem becomes very challenging as exceptionally large number of channel parameters have to be estimated. We propose an efficient distributed ...

This paper considers the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. We propose efficient algorithms achieving the exact ML non-coherent data detection, for both constant-modulus constellations and nonconstant-modulus constellations. Despite a large nu...

Massive MIMO communication systems, by virtue of utilizing very large number of antennas, have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. In this paper, we consider uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. With increased number of ante...

Massive MIMO systems have made significant progress in increasing spectral and energy efficiency over traditional MIMO systems by exploiting large antenna arrays. In this paper we consider the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. Despite the lar...

This paper investigates the joint maximum likelihood (ML) data detection and channel estimation problem for Alamouti space-time block-coded (STBC) orthogonal frequency-division multiplexing (OFDM) wireless systems. The joint ML estimation and data detection is generally considered a hard combinatorial optimization problem. We propose an efficient l...

Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, previous assumption is not justified. To overcome difficulties caused by an unknown number of sources, an adaptive algorithm based on a simple geometric approach for Indepen...