PAPR Reduction at Large Multi-User-MIMO-OFDM using Adaptive Data Detection Algorithm

Abstract

Wireless communication in present era contains large-scale MIMO network architecture that need to deliver an optimize-QoS to multi-user (MU).
The optimize data rate transmission in massive MU-MIMO wireless systems is one of the most difficult task due to the extremely high implementation complexity. The practical wireless system channels generally exhibits the PAPR and frequency selective fading, it is also necessary to have a precoding solution in PAPR for the selected desirable channels. A solution for the designed problem of a noble error-correcting code for OFDM process with a low PAPR, in the case of impulse noise should be considered. In this paper, Adaptive-Data-detection (ADD) algorithm is proposed to obtain lower-complexity data-detection that corresponds to high throughput design and impulse noise removal for large MUI-MIMO wireless systems by the OFDM modulation technique. That contains some steps such as; initialization,
pre-processing and equalization steps in order to get no performance loss and to minimalize the recurrent amount at each iterations during operation. In order to use simplify model, here we assume suitably perfect synchronization, large cyclic prefix and perfect-CSI (channel-state-information) which has been developed through the pilot depended training. Simulation results analysis show the proposed method substantial improvement over the existing algorithm in terms of both ‘Error-rate’ minimization and PAPR reduction.