Analysis of the Methods for Channel Impulse Response Assessment in Communication Systems with OFDM Technology

Abstract

Communication systems are a key tool in the development of modern society. Technological developments have led to the need for high-speed data exchange in large volumes. Therefore, improvement of the existing and creating new communication systems is an urgent task. One of the most promising technologies for the development of digital communication systems is orthogonal frequency division multiplexing (OFDM). The main advantage of OFDM is its high resistance to multi-path fading. In an urban environment, where radio waves are reflected from buildings, the signal arrives at the receiver with different delays, which causes intersymbol interference (ISI). OFDM solves this problem by dividing a high-speed data stream into many slow sub streams, each of which is transmitted on a separate, narrow subcarrier frequency. Due to this, the symbols become longer than the delays caused by reflections, which minimizes the impact of ISI. In addition, OFDM provides high spectral efficiency, that is, it enables to transmit more data per unit of frequency band. This is achieved due to the orthogonality of subcarriers, the spectra of which overlap, but do not interfere with each other. This allows to tightly "pack" subcarriers, making the most of the available frequency range. The paper analyzes methods for estimating the impulse response of a communication channel in communication systems using OFDM technology. Assessment of communication channel parameters is an important stage in the operation of OFDM systems, since the number of errors that occur during information transmission depends on the accuracy of the assessment of channel parameters. In particular, the maximum length sequence method (MLS), which does not require a priori information about the channel, and the linear minimum mean square error method (LMMSE), for which it is necessary to know the autocovariance matrix of the channel, are considered. These methods are widely used in practice, but have their drawbacks. The analysis of the effectiveness of the methods was carried out on a model example by statistical modeling. The communication channel was described using the Rayleigh model. The analysis results showed that the MLS method is simple to implement, but demonstrates worse estimation accuracy compared to the LMMSE method. The LMMSE method shows a gain of up to 2 dB compared to the MLS method, but has an order of magnitude higher computational complexity.