The growth of wireless networking has contributed to the need for high-speed services and multimedia applications anywhere and at any time. OFDM WiMAX technology is now considered one of the most popular technologies capable of delivering faster implementation and lower cost than standard wired options for Broadband Wireless Connectivity in metropolitan areas. This paper proposes appropriate adaptive modulation to be used in wireless networks based on SISO and MIMO OFDM WiMAX, which allows the performance of the network to be improved in the case of non-line-of-sight communications that are typical in urban environments. The effects of several paths, signal attenuation, Doppler shift, and different mobility speeds on the performance of the system were investigated. Mathematical models analysis of adaptive modulation in SISO and MIMO systems is treated by using BER, SNR and noise components. Simulation results show that the adaptive algorithm would improve throughput. It can also be concluded that when processing signals in a receiving system under conditions of multi-path signal propagation, the use of adaptive algorithms has a positive effect on noise immunity. HIGHLIGHTS With the growing evolution of wireless communication technologies, there is still a need for higher data rates, increased system capacity, and improved service quality 3D OFDM-MIMO WiMAX technology is now regarded as one of the most common solutions for Broadband Wireless Connectivity in Urban Areas, capable of offering faster implementation and lower costs than standard wired options Effective adaptive algorithm processing in 3D wireless networks based on SISO-OFDM and MIMO-OFDM WiMAX was proposed, enabling network performance to be enhanced in the case of non-LOS wireless communications, which are standard in urban conditions. On the performance of the system, signal attenuation, the effects of several paths, different mobility speeds and Doppler shift were studied The adaptive algorithm significantly reduces the probability of error and increases the throughput. It can be concluded that the use of adaptive spatio-temporal algorithms has a positive effect on noise immunity when processing signals in the receiving system under conditions of multipath signal propagation GRAPHICAL ABSTRACT

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In this paper,  a mixed transform method is proposed based on a combination of wavelet transform (WT) and multiwavelet transform (MWT) in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI) or Computed Tomography (CT) images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results show that a high peak signal to noise ratio (PSNR) is improved significantly and the characteristic features are well preserved by employing mixed transform of WT and MWT due to their capability of separating noise signals from image signals. Moreover, the corresponding mean square error (MSE) is decreased accordingly compared to other available methods.

With the growing evolution of wireless communication technologies, there is still a need for higher data rates, increased system capacity, and improved service quality. OFDM WiMAX technology is now regarded as one of the most common solutions for Broadband Wireless Connectivity in Urban Areas, capable of offering faster implementation and lower costs than standard wired options. This paper proposes effective adaptive algorithm processing with MMSE for use in wireless networks based on SISO and MIMO OFDM WiMAX, enabling network performance to be enhanced in the case of non-LOS wireless communications, which are standard in urban conditions. On the performance of the system, signal attenuation, the effects of several paths l, different mobility speeds and Doppler shift were studied. Combines the adaptive algorithm with MMSE, achieves improved joint channel estimation and signal detection which performs the technique effectively mobile. SNR, MSE and noise components are used to analyses mathematical models of adaptive modulation for transmitting images in SISO and MIMO systems. Simulation results show that the adaptive algorithm with MMSE would improve throughput. For example, when SNR equal 15 dB, the probability of MSE for BPSK based on MIMO principle is equal to 0.0016 with adaptive algorithm. Also, for the same value of SNR, the probability of MSE for BPSK based on MIMO principle is equal to 0.164 without adaptive algorithm. It can also be concluded that when processing signals in a receiving system under conditions of multi-path signal propagation, the use of adaptive algorithms with MMSE has a positive effect on noise immunity.