Channel estimation by adaptive interpolation

Abstract

Methods and apparatus that achieve good channel estimation without using unnecessarily complex interpolation filters are described. Adaptive interpolation filtering of a signal in a receiver includes determining at least one correlation function parameter of the channel and determining a filter configuration based on the correlation function parameter. Interpolation filtering is then performed on the signal using the determined filter configuration. The interpolation may be performed in time, where a Doppler frequency shift can serve as the correlation function parameter, or in frequency, where a root mean square or maximum delay spread can serve as the correlation function parameter, or both. A worst case signal-to-noise ratio may be used in determining the filter configuration, or, optionally, the signal-to-noise ratio can determined in real time. The filter configuration can be determined in real time or selected from one of a plurality of predetermined configurations having different complexities.

Description

technical field [0001] The present application relates to digital communication in which channel is estimated by pilot symbols. In particular, it relates to situations where it is desirable to avoid or reduce high order interpolation filters because of the memory requirements and complexity of such filters. The present application also relates to the case where it is desired to estimate the channel correlation function by a low complexity method. Background technique [0002] In wireless communications, the data to be communicated is typically transmitted via a channel whose characteristics vary with time and frequency. That is, the amplitude and phase of the channel vary from one symbol to the next and from one frequency to the next. How much the signal changes in time between two symbols basically depends on two things, namely, the symbol period and how fast the actual channel changes; but how much the channel changes between two frequencies depends on the frequency sepa...

AI Technical Summary

Problems solved by technology

Due to the fact that the number of subcarriers is large, the symbol period will also be large, which means that if the part of the symbol used as a pilot remains the same, the pilots will be farther apart in time and the interpolation becomes harder, requiring more complex filters

Furthermore, due to the large number of subcarriers, the amount of data that must be buffered for each OFDM will also be large

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