Estimação de canal em sistemas OFDM utilizando redes neurais artificiais RBF com transmitância de fase

Abstract

The wireless communication channel has severe signal degradation effects resulting from the usual multiplicity of propagation paths originated by reflection of the electromagnetic wave at specific points along the path of the digital transmitter-receiver link. Metallic building structures, for example, are points of reflection of the wave. This multiplicity of propagation paths, called multipath, generates signal interference on itself when multiple signals arrive at the receiver, degrading signal intelligibility, which increases the bit error rates of the link, reducing a reliability. This interference is called intersymbol interference (ISI) because, in the baseband signal at the receiver, overlapping of the digital modulation symbols occurs, resulting in a failure to detect the binary words associated with the symbols. In this context, the channel estimation and compensation process plays an important role in the wireless receiver. The increasing demand for systems with higher transmission capacities, robustness and less computational complexity, has driven several researches in the scope of the algorithms used in the channel estimation process. In recent years, data transmission technique through Orthogonal Frequency Division Multiplexing (OFDM) has been highlighted by resistance to ISI, good spectral efficiency and transmission capacity of high data rates. OFDM is a multi-carrier modulation technique that consists of dividing the total bandwidth into smaller subchannels by using orthogonal subcarriers spectrally superimposed. Despite its robustness, it is still required channel estimation techniques, in OFDM receiver, due to the multipath effect characteristic of a wireless communication channel. This work proposes the implementation of a channel estimator, based on a complex Radial Basis Function (RBF) network. The proposed network is trained from the impulse response of the channel obtained through the pilot carriers sent and known by the receiver. The simulation results show that the proposed network obtained better results than the classical estimators used for channel estimation in OFDM systems.