Mitigation of impulsive noise in OFDM channels using ANN technique

Abstract: Orthogonal frequency division multiplexer (OFDM) is a recent modulation scheme used to transmit signals across power line communication (PLC) channel due to its robustness against some known PLC problems. However, this scheme is greatly affected by the impulsive noise (IN) and often causes corruption with the transmitted bits. Different impulsive noise error correcting methods have been introduced and used to remove impulsive noise in OFDM systems. However, these techniques suffer some limitations and require much signal to noise ratio (SNR) power to operate. In this paper, an approach of designing an effective impulsive-noise error-correcting technique was introduced using three-known artificial neural network techniques (Levenberg-Marquardt, Scaled conjugate gradient, and Bayesian regularization). Findings suggest that both Bayesian regularization and Levenberg-Marquardt ANN techniques can be used to effectively remove the impulsive noise present in an OFDM channel and using the least SNR power

Mitigation of impulse noise in powerline systems using ANFIS technique

Abstract: The use of OFDM channel for the transmission of data in power line communication (PLC) system has been of several importance to technology development. However, during transmission, the OFDM channel is greatly disturbed by impulse noise that causes a wrong information to be received. Several techniques such as iteration, coding, clipping and nulling methods have been used to lessen the upshot of impulse noise in OFDM channel. However, these techniques still suffer some drawbacks and require a high signal-to-noise (SNR) power for high performance. This paper presents an advanced use of artificial neuro-fuzzy inference system (ANFIS) technique in removing the complete impulse noise and some of the additive white Gaussian noise (AWGN) that were mixed with the transmitted data in an OFDM channel and using the minimum SNR power. Obtained results propose that ANFIS technique can be used to mitigate impulse noise from a powerline communication channel

Mitigation of impulsive noise for SISO and MIMO G.fast system

To address the demand for high bandwidth data transmission over telephone transmission lines, International Telecommunication Union (ITU) has recently completed the fourth generation broadband (4GBB) copper access network technology, known as G.fast. Throughout this thesis, extensively investigates the wired broadband G.fast coding system and the novel impulsive noise reduction technique has been proposed to improve the performance of wired communications network in three different scenarios: single-line Discrete Multiple Tone (DMT)- G.fast system; a multiple input multiple-output (MIMO) DMTG.fast system, and MIMO G.fast system with different crosstalk cancellation methods. For each of these scenarios, however, Impulsive Noise (IN) is considered as the main limiting factor of performance system. In order to improve the performance of such systems, which use higher order QAM constellation such as G.fast system, this thesis examines the performance of DMT G.fast system over copper channel for six different higher signal constellations of M = 32, 128, 512, 2048, 8192 and 32768 in presence of IN modelled as the Middleton Class A (MCA) noise source. In contrast to existing work, this thesis presents and derives a novel equation of Optimal Threshold (OT) to improve the IN frequency domain mitigation methods applied to the G.fast standard over copper channel with higher QAM signal constellations. The second scenario, Multi-Line Copper Wire (MLCW) G.fast is adopted utilizing the proposed MLCW Chen model and is compared to a single line G-fast system by a comparative analysis in terms of Bit-Error-Rate(BER) performance of implementation of MLCW-DMT G.fast system. The third scenario, linear and non-linear crosstalk crosstalk interference cancellation methods are applied to MLCW G.fas and compared by a comparative analysis in terms of BER performance and the complexity of implementation.University of Technology for choosing me for their PhD scholarship and The Higher Committee For Education Development in Iraq(HCED

Design and Linearization of Energy Efficiency Power Amplifier in Nonlinear OFDM Transmitter for LTE-5G Applications. Simulation and measurements of energy efficiency power amplifier in the presence of nonlinear OFDM transmitter system and digital predistortion based on Hammerstein-Wiener method

This research work has made an effort to understand a novel line of radio frequency power amplifiers (RFPAs) that address initiatives for efficiency enhancement and linearity compensation to harmonize the fifth generation (5G) campaign. The objective is to enhance the performance of an orthogonal frequency division multiplexing-long term evolution (OFDM-LTE) transmitter by reducing the nonlinear distortion of the RFPA. The first part of this work explores the design and implementation of 15.5 W class AB RF power amplifier, adopting a balanced technique to stimulate efficiency enhancement and redeeming exhibition of excessive power in the transmitter. Consequently, this work goes beyond improving efficiency over a linear RF power amplifier design; in which a comprehensive investigation on the fundamental and harmonic components of class F RF power amplifier using a load-pull approach to realise an optimum load impedance and the matching network is presented. The frequency bandwidth for both amplifiers was allocated to operate in the 2.620-2.690 GHz of mobile LTE applications. The second part explores the development of the behavioural model for the class AB power amplifier. A particular novel, Hammerstein-Wiener based model is proposed to describe the dynamic nonlinear behaviour of the power amplifier. The RF power amplifier nonlinear distortion is approximated using a new linear parameter approximation approach. The first and second-order Hammerstein-Wiener using the Normalised Least Mean Square Error (NLMSE) algorithm is used with the aim of easing the complexity of filtering process during linear memory cancellation. Moreover, an enhanced adaptive Wiener model is proposed to explore the nonlinear memory effect in the system. The proposed approach is able to balance between convergence speed and high-level accuracy when compared with behavioural modelling algorithms that are more complex in computation. Finally, the adaptive predistorter technique is implemented and verified in the OFDM transceiver test-bed. The results were compared against the computed one from MATLAB simulation for OFDM and 5G modulation transmitters. The results have confirmed the reliability of the model and the effectiveness of the proposed predistorter.Fundacão para a Ciência e a Tecnologia, Portugal, under European Union’s Horizon 2020 research and innovation programme ... grant agreement H2020-MSCA-ITN- 2016 SECRET-722424 I also acknowledge the role of the National Space Research and Development Agency (NASRDA) Sokoto State Government Petroleum Technology Trust Fund (PTDF