5G waveform system synchronization method based on index modulation

Abstract

The invention discloses a 5G waveform system synchronization method based on index modulation. The method comprises the following steps: dividing sending end parallel data of a filter orthogonal frequency division multiplexing system based on index modulation into index bit data and constellation modulation data, performing sub-band matching filtering processing, cyclic prefix removal and Fouriertransform at a receiving end, detecting the position of an activated sub-carrier, estimating an index bit, and demodulating constellation symbol information; establishing a training sequence based ona pseudo-random sequence and a Zadoff-Chu sequence, and performing timing and frequency offset estimation based on a pilot frequency data aided method; and completing timing estimation, performing fractional frequency offset estimation, performing integer frequency offset estimation by using the power difference between the activated subcarrier and the silent subcarrier, determining a receiving end Fourier transform starting window according to timing estimation information, determining a receiving end demodulation carrier frequency according to an estimated frequency offset value, and completing system synchronization. According to the invention, on the premise of not reducing the transmission efficiency, the influence of frequency offset on the system performance is effectively reduced.

Description

technical field [0001] The invention belongs to the technical field of 5G mobile communication, and in particular relates to a method for synchronizing a 5G waveform system based on index modulation. Background technique [0002] Orthogonal Frequency Division Multiplexing (OFDM, Orthogonal Frequency Division Multiplex-ing) technology has many advantages such as simple implementation, strong anti-multipath fading ability, and strong anti-intersymbol interference ability. It has been widely used in the system, but its fixed parameter configuration limits its application in the next generation mobile communication system. In the 5G Internet of Everything era, in order to maximize the use of existing spectrum resources, it is necessary to introduce waveforms with more flexible parameter configurations to meet the three business scenarios of enhanced mobile bandwidth, ultra-high reliability and low-latency communication, and machine-type communication. [0003] Existing timing a...

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Problems solved by technology

[0003] Existing timing and frequency offset estimation synchronization methods only consider how to effectively complete timing and frequency offset estimation, but do not consider how to effectively reduce the impact of frequency offset on system performance

For classic OFDM timing synchronization methods, such as SC method, Minn method, and Park method, although the timing metric function curve has been gradually improved, the secondary peaks that affect the timing estimation accuracy have not been fundamentally eliminated; secondly, SC method, Jian method, etc. The filter problem is not considered in the frequency offset estimation, and its estimation performance is continuously improved in the OFDM system. The above method is directly applied to the filter orthogonal frequency division multiplexing (F-OFDM-IM, Filtered Orthogonal Frequency Division Multiplexing Based on IndexModulation) system, its estimation performance is still not ideal

This is because in the F-OFDM-IM system, due to the existence of the filter, the autocorrelation of the training sequence is reduced. At this time, if only the autocorrelation of one OFDM symbol is used for estimation, the estimation performance will inevitably be greatly reduced. , and one OFDM training symbol cannot take into account the precise estimation of timing and frequency offset at the same time; the existing Liang method is based on the Filtered Orthogonal Frequency Division Multiplexing (F-OFDM, Filtered Orthogonal Frequency Division Multiplexing) system, and the training symbols of this method are composed of three OFDM symbols are generated, although better timing accuracy can be obtained, but the waste of spectrum resources caused by it cannot be ignored, and the estimation range of the fractional frequency offset is small, so it is impossible to complete the complete estimation of the fractional frequency offset. Integer frequency offset estimation affects

Finally, the above methods all have good performance only in the Gaussian white noise channel, but in the multipath channel, the intersymbol interference problem caused by the multipath effect is not considered, resulting in a significant drop in estimation performance

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