Reducing the pilot contamination in a Multi Input Multi Output – Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is one of the demanding and essential tasks in recent days. Because, the pilot contamination can affect the overall performance of the communication system, so it must be reduced for enabling a reliable data transmission. Energy harvesting is also one of the important considerations in MIMO-OFDM systems, which improves the communication efficiency of transmit and receive antennas. For this reason, different pilot scheduling mechanisms are developed in the traditional works, which intends to develop the pilot reuse mechanism for reducing the contamination effects. Still, it remains with the issues like increased channel estimation error, complexity and reduced performance rate. Due to these problems, a hybrid methodology is developed in this work for MIMO-OFDM systems. The major objectives that focused on this work are, reducing the pilot contamination, efficient channel scheduling, energy harvesting, and channel estimation. Here, the Genetic Algorithm (GA) is utilized to schedule the most optimal channel for communication with reduced contamination rate. Then, the water filling strategy is employed to perform the energy harvesting with increased data rate and maximum capacity. Also, a hybrid methodology is developed for estimating the best channel by incorporating the functionalities of Maximum Likelihood (ML) and Minimum Mean Squared Error (MMSE) models. The simulation results evaluate the performance of this system by evaluating various measures. Also, its superiority is proved by comparing it with the existing scheduling mechanisms.
Volume 11 | 02-Special Issue
Pages: 1928-1939