CN107171989A - Channel estimation methods based on DFT in visible light communication system - Google Patents

Abstract

The invention discloses the channel estimation methods based on DFT in a kind of visible light communication system, DFT channel estimation methods based on pilot tone calculate fairly simple, estimated accuracy is higher, often application is in systems in practice, the presence of virtual carrier causes the problem of DFT channel estimation methods based on pilot tone have energy leakage in visible light communication system, the loss of learning for needing the presence to virtual carrier to cause is compensated, but the influence of virtual carrier can be completely eliminated in not a kind of optimal backoff algorithm.The present invention carries out time domain amendment to the DFT channel estimation methods based on pilot tone that there is virtual carrier, so as to not influenceed completely by virtual carrier, improves the performance of channel estimation.

Description

Channel Estimation Method Based on DFT in Visible Light Communication System

technical field

The present invention relates to the technical field of visible light communication, in particular to a channel estimation method based on DFT in visible light communication.

Background technique

The application of Orthogonal frequency division multiplexing (OFDM) in a communication system can effectively resist Inter-symbol interference (ISI). At the same time, inter-carrier interference (Inter Carrier Interference, ICI) can be further eliminated by inserting a cyclic prefix (Cyclic Prefix, CP) between symbols.

Therefore, the application of OFDM technology in the VLC (visible light communication) system can effectively resist ISI and ICI, and at the same time improve the spectrum utilization rate of the system. In the VLC system, Intensity Modulation/Direct Detection (IM/DD) is used, and the signal is transmitted with light intensity as the carrier. The modulation method used in this system is DCO-OFDM (Direct Current Optical-OFDM).

Channel estimation is a very important step in a communication system. Only when channel information is obtained can subsequent channel equalization, demodulation, decoding, etc. be performed. The pilot-based channel estimation algorithm is relatively simple and has high accuracy. The commonly used channel estimation algorithms include least squares (Least Squares, LS), linear minimum mean square error (Linear Minimum Mean Squared Error, LMMSE) and DFT-based channel estimation algorithm. The LS algorithm does not consider the influence of noise and has poor performance. The LMMSE performance is better but the high complexity is not applicable in the actual system, and the channel estimation algorithm based on DFT is simple to calculate and has better performance. Therefore, the present invention will be based on DFT The channel estimation algorithm is applied in the VLC system.

Contents of the invention

Purpose of the invention: The present invention aims at the problems existing in the prior art, and provides a channel estimation method based on DFT in a visible light communication system, which has simple calculation and good performance.

Technical scheme: described in the present invention

The DFT-based channel estimation method in the visible light communication system of the present invention includes the following steps:

(1) Using the LS algorithm to obtain the initial frequency domain channel response of the pilot subcarrier in the visible light communication system in,

In the formula, Y _P represents the received signal at the pilot position, X _P is the N _P ×N _P diagonal matrix of the data inserted at the pilot position by the transmitting end, and its diagonal elements are the N-point FFT transformation values of the transmitted signal x The value at the corresponding pilot position of , N _P is the number of pilots, and N is the number of subcarriers;

(2 pairs Do matrix operations to get the initial time domain channel response of the channel Only take the channel information within the channel response length, that is,

In the formula, B is a DFT matrix of N _P ×L order, and L is the maximum length of the channel time domain response;

(3) The initial time domain channel response Zeros are added to the tail to make the length N, that is

(4) yes Do N-point DFT transformation to get the estimated channel in,

Beneficial effects: Compared with the prior art, the present invention has the remarkable advantage that the time domain correction algorithm of the present invention is the idea of the time domain LS algorithm, and for the process of transforming to the time domain in step 2, instead of directly doing IDFT, it uses The incomplete IDFT transformation matrix can directly obtain the time domain response, which avoids the error caused by the lack of channel information caused by the existence of virtual carriers, that is, the problem of energy leakage is also avoided. Therefore, the algorithm is no longer affected by the virtual carrier, it is better than the simple compensation algorithm, and there is no error platform.

Description of drawings

Figure 1 is a block diagram of a visible light DCO-OFDM baseband system.

Figure 2 is a basic block diagram of the VLC baseband system transmitter.

Fig. 3 is a basic block diagram of the VLC baseband system receiver.

Fig. 4 is the physical layer frame structure of the visible light DCO-OFDM system.

Fig. 5 is the NMSE of the DFT compensation algorithm and the time domain correction algorithm based on the pilot frequency.

detailed description

1. Analysis of technical problems

The system model of the present invention is designed according to the DCO-OFDM system, specifically as shown in Figure 1, and Figure 2 is a basic block diagram of a VLC baseband system transmitter. The information received from the MAC layer reaches the baseband processing part of the FPGA through the network port module, and performs operations such as scrambling, channel coding, interleaving, constellation mapping, IFFT transformation, and CP addition on the Ethernet frame data to obtain discrete data in the time domain. Before the data enters the DAC module, it is necessary to add frame header data, namely short training sequence (Short Training Sequence, STS), long training sequence (Long Training Sequence, LTS), physical header (PHY Header) and other data, for the synchronization of the receiving end , channel estimation, etc. Fig. 3 shows the main processing flow of the receiver of the visible light DCO-OFDM system. After the receiver data undergoes AD conversion, first perform frame detection, synchronization, etc., then remove the CP from the received data, and then obtain the frequency domain data through FFT operation, and extract the previous training sequence data and the received pilot sequence data. Channel estimation, followed by subsequent operations such as frequency domain equalization, demodulation, deinterleaving, channel decoding, and descrambling. Baseband processing is implemented at the physical layer. Figure 4 shows the physical layer frame structure of the visible light DCO-OFDM system. The frame design method in the VLC system refers to IEEE802.11a. A frame of data includes STS, LTS, PHY Header, physical layer load (PHY Payload) and frame space (IFS). Among them, the STS is used for frame detection and frame synchronization, and the LTS is used after the STS for channel estimation after the frame detection. Then there is the physical header part, which is used to transmit some parameters required for demodulation at the receiving end, such as modulation order, etc., and the length is one OFDM symbol. After the physical header is the transmission of valid data, and finally the frame interval part, which is one or two OFDM symbols in length and is used to mark the end of a frame of data in the physical layer.

For the DCO-OFDM system, the received signal at the pilot position can be expressed as

Y _P ＝X _P H _P +W _P

In the formula, X _P is the diagonal matrix of N _P ×N _P , and its diagonal elements are the values at the corresponding pilot positions of the N-point FFT transformation value of the transmitted signal x, and H _P is the N _P ×1-dimensional channel column Vector, W _P is N _P ×1-dimensional noise vector.

The pilot-based channel estimation process mainly considers the following three aspects: the selection of the pilot pattern at the transmitting end, obtaining the channel information at the pilot, and obtaining the entire channel information through the channel information at the pilot.

In the OFDM transmission system, commonly used pilot patterns include comb pilot and block pilot. Comb pilots are suitable for fast fading channels, while block pilots are suitable for slow fading channels. Since the visible light channel is a slow fading channel, a block pilot method is used to calculate the channel estimation.

The DFT-based channel estimation algorithm is easy to implement and has good performance, so it has attracted much attention. In order to prevent interference from other systems, the VLC system reserves a part of subcarriers on both sides of the transmission bandwidth as guard frequency bands, which are called virtual subcarriers (Virtual Carriers, VC).

In a system with a virtual carrier, generally the frequency response value at the virtual subcarrier is set to 0 directly after the LS algorithm estimation. In the frequency domain, the existence of the virtual carrier is equivalent to adding two rectangular window functions to the channel frequency response; in the time domain, it is equivalent to convolving the time domain impulse response of the system with the time domain response of the rectangular window function. Due to the convolution with the sinc function containing two main lobes in the time domain, the channel energy is no longer concentrated on the previous L points, but will leak to all sampling points, causing the channel CIR to become longer, resulting in energy leakage.

In order to analyze the impact of the virtual carrier on the system, it is assumed that there are pilots at the position of the virtual carrier, and its distribution law is the same as that at the effective data subcarrier. Assume are the number of pilots in the effective data subcarriers on the right and left of the virtual subcarrier in the middle, and the number of pilots in the virtual subcarrier, respectively, and N _P is the total number of pilots, that is I ^In and I ^Out are the set of pilot positions in effective data subcarriers and virtual subcarriers respectively, and

Then the channel response after setting the value at the pilot position in the virtual subcarrier to zero for

In the formula, Indicates the channel response value at the pilot position estimated by the LS channel estimation algorithm.

Then the channel estimation based on DFT transform for

where N _u is the number of effective data subcarriers, is the DFT transformation matrix of N _u × _NP , is the actual frequency response at the effective data subcarrier, is the channel estimation error, the data in the virtual carrier is 0, is the channel frequency response where the pilot should be at the virtual subcarrier. Then the estimation error in the effective data subcarrier of the system with virtual carrier is

It can be seen from the above formula that the error of the channel estimation algorithm is caused by the noise and the lack of channel information in the virtual subcarrier, and these two parts are independent of each other.

Then the mean square error (Mean Square Error, MSE) of the channel estimation algorithm is

Where β is a constant related to the modulation method, SNR is the average signal-to-noise ratio of the input signal, is the autocorrelation matrix of the channel frequency response.

It can be seen that the DFT-based channel estimation error in the presence of virtual carriers consists of two parts: one is the error caused by the influence of noise, which can be considered to be equal to the DFT channel estimation error when there is no virtual carrier; the other is the error caused by the virtual carrier The error caused by the lack of information, the more information missing at the virtual carrier, the greater the channel estimation, especially at high signal-to-noise ratio, the existence of the virtual carrier makes the energy leak to the adjacent useful subcarriers, However, the truncation operation in the time domain makes the energy loss of the useful signal, resulting in the floor effect.

In order to reduce the impact of the virtual carrier on the DFT-based channel estimation algorithm, two aspects can be considered, one is to reduce the impact of noise, and the other is to reduce the error caused by the lack of virtual carrier information, that is, the channel value at the virtual carrier needs to be calculated compensate. Reducing the impact of noise is the basic DFT-based channel estimation algorithm. In order to improve the accuracy of channel estimation, it is necessary to compensate the error caused by the absence of virtual carriers.

2. Technical methods

In order to reduce the impact of virtual carriers on the system, common compensation algorithms include repeated edge value method and partial subcarrier method. The calculation of these two algorithms is relatively simple, but the error is relatively large, and there is no optimal compensation algorithm to completely eliminate the influence of the virtual carrier. The present invention corrects the method based on DFT, improves estimation performance, and concrete steps are as follows:

(1) Using the LS algorithm to obtain the initial frequency domain channel response of the pilot subcarrier in the visible light communication system in,

(2 pairs Do matrix operations to get the initial time domain channel response of the channel Only take the channel information within the channel response length, that is,

In the formula, B is a DFT matrix of N _P ×L order, and L is the maximum length of the channel time domain response;

(3) The initial time domain channel response Zeros are added to the tail to make the length N, that is

(4) yes Do N-point DFT transformation to get the estimated channel in,

F _N is the DFT transformation matrix.

3. Simulation verification

The floating-point simulation analysis and comparison of the pilot-based DFT channel estimation algorithm in the visible light DCO-OFDM system is carried out on MATLAB. Since the visible light channel is a slow time-varying channel, the block pilot is used for channel estimation research. In this system, under the condition that the transmission data frame is not long, it is considered that the channel within one frame remains unchanged. Usually, two long training sequences are designed in the frame header, and the average of the two is used to improve the quality of channel estimation, and the average of the two estimates can generally increase the accuracy by 3dB. The main simulation parameters are: FFT/IFFT points N=512, subcarrier spacing Δf=312.5KHz, signal bandwidth BW=242×312.5KHz=75.625MHz, pilot subcarrier position k=2～243, 271～512, virtual subcarrier Position k=1,244-270, CP length N _CP =64, CIR length N _CIR =25, number of OFDM symbols in one frame of data N _OFDM =32. In the simulation, the normalized mean square error (Normalized MSE, NMSE) is used as the performance index of the channel estimation algorithm, and NMSE is defined as follows

where H represents the actual response value of the channel, Indicates the estimated value of the channel.

The simulation analysis of the pilot-based DFT channel estimation algorithm when there is a virtual carrier in the visible light DCO-OFDM system is carried out. Figure 5 shows the LS algorithm, the DFT-based channel estimation algorithm when there is a virtual carrier, two compensation algorithms and time domain The NMSE simulation results of the revised algorithm. It can be seen from the simulation results that the performance of the time domain correction algorithm is greatly improved compared with the compensation algorithm, and there is no error platform.

What is disclosed above is only a preferred embodiment of the present invention, which cannot limit the scope of rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope of the present invention.

Claims (1)

1. A channel estimation method based on DFT in visible light communication system is characterized in that: the method comprises

(1) Method for obtaining initial frequency domain channel response of pilot frequency subcarrier in visible light communication system by LS algorithmWherein,

<mrow> <msub> <mover> <mi>H</mi> <mo>^</mo> </mover> <mrow> <mi>P</mi> <mo>,</mo> <mi>L</mi> <mi>S</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>Y</mi> <mi>P</mi> </msub> <mo>/</mo> <msub> <mi>X</mi> <mi>P</mi> </msub> <mo>,</mo> </mrow>

in the formula, Y_PIndicating the received signal at the pilot position, X_PInserting N of data at pilot location for transmit end_P×N_PA diagonal matrix whose diagonal elements are values at corresponding pilot positions of N-point FFT transform values of the transmission signal x, N_PIs the number of pilot frequencies, and N is the number of subcarriers;

(2) to pairMatrix operation is carried out to obtain initial time domain channel response of channelTaking channel information only within the length of the channel response, i.e.

<mrow> <msub> <mover> <mi>h</mi> <mo>^</mo> </mover> <mrow> <mi>P</mi> <mo>,</mo> <mi>L</mi> <mi>S</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>(</mo> <msup> <mi>B</mi> <mi>H</mi> </msup> <mi>B</mi> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <msup> <mi>B</mi> <mi>H</mi> </msup> <msub> <mover> <mi>H</mi> <mo>^</mo> </mover> <mrow> <mi>P</mi> <mo>,</mo> <mi>L</mi> <mi>S</mi> </mrow> </msub> </mrow>

In which B is N_P× L-order DFT matrix, L is the maximum length of channel time domain response;

(3) initial time domain channel responseThe tail of the tail is zero-added to have a length ofN is that

<mrow> <mover> <mi>h</mi> <mo>~</mo> </mover> <mo>=</mo> <mo>&amp;lsqb;</mo> <msub> <mover> <mi>h</mi> <mo>^</mo> </mover> <mrow> <mi>P</mi> <mo>,</mo> <mi>L</mi> <mi>S</mi> </mrow> </msub> <mo>,</mo> <msub> <mn>0</mn> <mi>L</mi> </msub> <mo>,</mo> <mn>0</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msub> <mn>0</mn> <mrow> <mi>N</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>&amp;rsqb;</mo> <mo>;</mo> </mrow>

(4) To pairPerforming N-point DFT conversion to obtain estimated channelWherein,

<mrow> <msub> <mover> <mi>H</mi> <mo>^</mo> </mover> <mrow> <mi>D</mi> <mi>F</mi> <mi>T</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>DFT</mi> <mi>N</mi> </msub> <mrow> <mo>(</mo> <mover> <mi>h</mi> <mo>~</mo> </mover> <mo>)</mo> </mrow> <mo>.</mo> </mrow>1