Digital satellite communication systems are equipped with nonlinear amplifiers such as travelling wave tube (TWT) amplifiers at or near saturation for better efficiency. The TWT exhibits nonlinear distortion in both amplitude and phase (AM/AM and AM/PM) conversion, respectively. That is, in the digital satellite communication the transmission is disturbed not only by the non-linearity of transmitter amplifier, but also by the inter-symbol interference (ISI) with additive white Gaussian noise. To compensate the non-linearity of the transmitter amplifier and ISI, in this thesis, a new nonlinear compensation scheme consists of the predistorter and adaptive third-order Volterra-based equalizer, with the inverse QRD-RLS (IQRD-RLS) algorithm, which are located before and after the nonlinear channel, is proposed respectively. The third-order Volterra filter (TVF) equalizer based on the IQRD-RLS algorithm achieve superior performance, in terms of convergence rate, steady-state mean-squared error (MSE), and numerically stable. They are highly amenable to parallel implementation using array architectures, such as systolic arrays. The computer simulation results using the M-ary PSK modulation scheme are carried out the signal¡¦s constellation diagrams, the learning curve of the MSE and the bit error rate (BER) are compared with conventional least mean square (LMS), gradient adaptive lattice (GAL) and adaptive LMS with lattice pre-filter algorithms.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / FPGAs are increasingly being employed for building real-time signal processing systems. They have been used extensively for implementing the PHY in software radio architectures. This paper provides a technology and market perspective on the use FPGAs for signal processing and demonstrates FPGA DSP using an adaptive channel equalizer case study.

In recent years Multiple Input Multiple Output (MIMO) systems have been employed in wireless communication systems to reach the goals of high data rate. A MIMO use multiple antennas at both transmitting and receiving ends. These antennas communicate with each other on the same frequency band and help in linearly increasing the channel capacity. Due to the multi paths wireless channels face the problem of channel fading which cause Inter Symbol Interference (ISI). Each channel path has an independent path delay, independent path loss or path gain and phase shift, cause deformations in a signal and due to this deformation the receiver can detect a wrong or a distorted signal. To remove this fading effect of channel from received signal many Neural Network (NN) based channel equalizers have been proposed in literature. Due to high level non-linearity, NN can be efficient to decode transmitted symbols that are effected by fading channels. The task of channel equalization can also be considered as a classification job. In the data (received symbol sequences) spaces NN can easily make decision regions. Specifically, NN has the universal approximation capability and form decision regions with arbitrarily shaped boundaries. This property supports the NN to be introduced and perform the task of channel equalization and symbol detection. This research project presents the implementation of NN to be use as a channel equalizer for Rayleigh fading channels causing ISI in MIMO systems. Channel equalization has been done using NN as a classification problem. The equalizer is implemented over MIMO system of different forms using Quadrature Amplitude Modulation scheme (4QAM & 16QAM) signals. Levenberg-Marquardt (LM), One Step Secant (OSS), Gradient Descent (GD), Resilient backpropagation (Rprop) and Conjugate Gradient (CG) algorithms are used for the training of NN. The Weights calculated during the training process provides the equalization matrix as an estimate of Channel. The output of the NN provides the estimate of transmitted signals. The equalizer is assessed in terms of Symbol Error Rate (SER) and equalizer efficiency.