in this work a new algorithm has been proposed to improve the wireless systems that are compatible with the current new technologies. Therefore, Denoise Orthogonal Frequency Division Multiplexing (OFDM) symbols and Replace the high Peak-to-Average Power Ratio (PAPR); (DORP) has been modified. In DORP, wavelets techniques have been used to denoise the affected OFDM symbol by high PAPR values. After that and based on adaptive threshold method the local maxima and minima will be determined and replaced by the average of them and their surrounding neighbors.The algorithm mainly tackles and overcomes the effect of the high Peak-to-Average Power Ratio problem that is found in OFDM systems, MIMO-OFDM combination has been developed to meet the rapidly increment in the users demand such as the ubiquitous transmission, imposing new multimedia applications and wireless services.A system performance investigation process will be accomplished based on both of numerical method and MATLAB simulation. Moreover, a comparison has been made to check the validity of our proposition either with our previously published work or with the literature. Although, the achieved results show that the proposed work gives an improvement of the BER; an additional complexity has been added to transceiver's structure. Moreover, and as a result to the comparison with the conventional systems, the bit error rate (BER) performance has been improved for the same bandwidth occupancy.As a validity process a comparison has been made with the current values found in the literature and we have achieved around 27% PAPR extra reduction. That is in addition to around 81% verification rate and noise immunity.

This work makes use of the entropy in order to propose a wavelet transformation algorithm to detect the odd peaks. Furthermore, this algorithm has been used to enhance the Orthogonal Frequency Division Multiplexing (OFDM) system performance based on combatting the peak-to-average power ratio (PAPR) problem.Three main stages are used to fulfill the process requirements; OFDM signal transformation based on the wavelet structure, thresholding process based on a predetermined criterion, and the filtration stage based on the moving filter.The proposed algorithm performance has been checked and validated not just numerically but also by a MATLAB conducted simulation. Furthermore, to check the simulation results, a comparison has been made to the literature; and shows promising results under the same bandwidth occupancy and systems limitations.

Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

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