Ibrahim M. Hussain

Performance of Routing Protocols in WiMAX Networks

The selection of an appropriate routing protocol is a key issue when designing a scalable and efficient wireless networks. Various routing protocols have been used in wireless networks. In this paper, we investigate different routing protocols and evaluate their performances on 802.16 WiMAX networks. Using simulation, different routing protocols have been tested with various network parameters. Results show that DSDV in general outperforms other routing protocols.

Vehicle detection using morphological image processing technique

Vehicle detection and classification of vehicles play an important role in decision making for the purpose of traffic control and management. In this paper we propose a novel and efficient algorithm based on image processing using aerial cameras for vehicle detection and classification especially in highways. The algorithm is mainly based on a sequence of morphological methods being applied on an image taken by an aerial camera of a road segment. The algorithm also uses thresholding and edge detection techniques for vehicle detection. Experiments are carried out over a wide range of vehicles, road segments and camera heights. A success rate of more than 85% and proper vehicle classification is achieved.

A simple and novel method for vehicle detection and classification (a model based test)

Vehicle detection and classification of vehicles play an important role in decision making for the purpose of traffic control and management. We propose a novel and efficient algorithm based on image processing using vertically positioned camera for vehicle detection and classification according to their size. The algorithm is based on different techniques including image differencing, thresholding, edge detection and binary morphological process. Experiments are carried out over a wide range of vehicles, road segments and camera positions. A success rate of around 85% is achieved in both vehicle detection and classification.

Novel SLM Based Techniques for PAPR Reduction of OFDM

Three new algorithms based on minimization of autocorrelation of transmitted symbols and the SLM approach which are computationally less demanding have been proposed. In the first algorithm, autocorrelation of complex data sequence is minimized to a value of 1 that results in reduction of PAPR. Second algorithm generates multiple random sequences from the sequence generated in the first algorithm with same value of autocorrelation i.e. 1. Out of these, the sequence with minimum PAPR is transmitted. Third algorithm is an extension of the second algorithm and requires minimum side information to be transmitted. Multiple sequences are generated by modifying a fixed number of complex numbers in an OFDM data sequence using only one factor. The multiple sequences represent the same data sequence and the one giving minimum PAPR is transmitted. Simulation results for a 256 subcarrier OFDM system show that significant reduction in PAPR is achieved using the proposed algorithms

Distributed Least Significant Bit technique for data hiding in images

In this paper we propose an algorithm based upon Least Significant Bit (LSB) algorithm called Distributed LSB. This algorithm has better performance both in capacity and the amount of degradation which takes place in the cover image during secret data hiding. The embedding method is distributed amongst pixel based upon their intensity levels and not sequential as in case of the conventional LSB algorithm. Both algorithms are tested on various intensity images and results are presented in the form of absolute entropy curves. Obtain results show that Distributed LSB has better hiding capacity than conventional LSB technique.

PAPR reduction of OFDM signals using autocorrelation based SLM without side information

Aperiodic autocorrelation and power variance are two parameters that play an important role in PAPR reduction in OFDM symbols. In this paper, we have tackled the aperiodic autocorrelation factor and based on it, two algorithms have been proposed. In the first algorithm, called selective autocorrelation (SA), the value of first aperiodic autocorrelation coefficient is minimized to 1 for reducing the PAPR. In the second algorithm, called selected sequences with variable autocorrelation SLM (SSVA), multiple sequences are generated by modifying a fixed number of complex numbers. The one giving minimum PAPR is transmitted. Simulation results show significant reduction in PAPR. Further a novel technique based on data insertion is used to handle the side information generated by the two algorithms without degrading the PAPR performance.

New SUB-SLM Method for PAPR Reduction in OFDM Signals

Selected mapping is an efficient algorithm for PAPR reduction in multicarrier systems. Two major issues in this technique are the side information and complexity of the implementation in terms of the number of IF FT blocks being used. Our proposed algorithm deals with the complexity issue. The new algorithm called sub-SLM algorithm divides the OFDM sequence into multiple equal length sequences then the SLM algorithm is applied on these individual partial sequences. Both the length of the new IFFT and the SLM is changed in the individual block which reduces the complexity. Simulation results show a reduction of almost 3 dB and reduction of complexity by a factor greater than two. The PAPR performance is slightly degraded as compared to the original SLM technique but the complexity is improved considerably.

Medium Access and Flow Management in IEEE 802.11 and 802.11e WLANS

With the increasing demand of multimedia services over internet and local area networks, techniques to provide better data rate, low latency and low packet loss have also emerged. For this reason, IEEE has introduced a standard for local area networks known as IEEE 802.11e. In this paper, we provide a comparative analysis of basic and new standard in terms of medium access technique and management of multiple flows. NS2 is used as a simulation tool and different traffic types like CBR, VBR and FTP are used to completely analyze the performance differences between two standards. The enhanced standard is found better in protecting and providing less delay in medium access to high priority flows.

On the contribution of power variance in PAPR reduction for OFDM signals

In various literatures, it has been argued that the power variance PV can be used as a sound model of peak-to-average power ratio PAPR for decisions aimed at reducing the power of the transmitted orthogonal frequency division multiplexing OFDM signals. Hence, it has been argued in the past that the PV is a good measure when it comes to power efficiency of OFDM signals. We argue that this may not be always true and that the PV-based power reduction may give misleading results in efforts aimed at PAPR reduction. We support our argument using simulation results. Furthermore, we show that the PV-based comparison in selected mapping reduction technique gives a degraded PAPR performance compared to the actual PAPR-based comparison.

A New Effective and Efficient Measure of PAPR in OFDM

In multi-carrier wireless OFDM communication systems, a major issue is related to high peaks in transmitted signals, resulting in such problems as power inefficiency. In this regard, a common practice is to transmit the signal that has the lowest Peak to Average Power Ratio (PAPR). Consequently, some efficient and accurate method of estimating the PAPR of a signal is required. Previous literature in this area suggests a strong relationship between PAPR and Power Variance (PV). As such, PV has been advocated as a good measure of PAPR. However, contrary to what is suggested in the literature, our research shows that often low values of PV do not correspond to low values of PAPR. Hence, PV does not provide a sound scientific basis for comparing and estimating PAPR in OFDM signals. In this paper a novel, effective, and efficient measure of high peaks in OFDM signals is proposed, which is less complex than PAPR. The proposed measure, termed as Partial Power Variance (PPV), exploits the relationship among PAPR, Aperiodic Autocorrelation Co-efficient (AAC), and Power Variance (PV) of the transmitted signal. Our results demonstrate that, in comparison to PV, Partial Power Variance is a more efficient as well as a more effective measure of PAPR. In addition, we demonstrate that the computational complexity of PPV is far less than that of PAPR.