Channel equalization method and communication system thereof based on precoding

Abstract

The invention provides a channel equalization method based on precoding. The method comprises that geometric mean decomposition is carried out to obtain R matrix, P matrix and Q matrix and then equalization is carried out according to the three matrixes, at a sending end, T-H precoding processing is carried out on modulated data according to the R matrix at first and then the data after the T-H precoding is sent and filtered according to the P matrix and at a receiving end, the data is received and filtered according to the Q matrix. The invention further respectively provides a communicationsystem with a single carrying wave realization way, which is based on the precoding and a communication system with a multiple-carrying wave realization way, which is based on the precoding. The invention eliminates error floor which is generated under high SNR when QR decomposition is used for the prior art and improves the system error code performance and is compatible with a single or multiple carrier waves communication system at the same time. The invention also provides a flexible geometric mean decomposition scheme so that the system can obtain excellent performance under low complexity.

Description

technical field [0001] The invention belongs to the technical field of wireless broadband access, and specifically proposes a precoding-based channel equalization method and a precoding-based communication system. Background technique [0002] As an effective anti-multipath fading technology for high-speed wireless communication, channel equalization technology is adopted by the 3G long-term evolution system LTE. When the data transmission rate is high, because the maximum multipath delay greatly exceeds the duration of a single transmission symbol, the data received at a certain moment is the superposition of tens or even hundreds of symbols before, so the recovery at the receiving end Raw data flow is incredibly difficult. Mathematically speaking, the channel equalizer first estimates the impulse response matrix of the channel through the channel estimation module, and then performs the inverse operation of the channel matrix on the received signal to recover the data. T...

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Problems solved by technology

The reason is that under high-order modulation, the deterioration of system performance due to residual ISI will become very significant, thus seriously curbing the bit error performance

It can be seen from the figure that the time-frequency equalization scheme based on QR decomposition of the channel matrix has a not very steep slope at high SNR, and there are different degrees of error flat. This is because the QR decomposition technology is used in these schemes, which will cause As a result, the signal-to-noise ratio of some sub-data streams at the end of the data block is significantly lower than that of the data at the head, that is, the received signal-to-noise ratio is uneven, so that the tail data with low signal-to-noise ratio will drag down system performance at high signal-to-noise ratio

like Figure 4 as shown, Figure 4 It is a schematic diagram of the error flat bottom of the equalization method based on the QR decomposition of the channel matrix at a high SNR. In this case, no matter how the SNR is improved, the effective SNR of some data cannot meet the requirements.

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