CN116760667A - A method for joint estimation of multi-cell channels in time-division duplex cellular network - Google Patents

Abstract

The invention discloses a method for joint estimation of multi-cell channels under a time-division duplex cellular network, and belongs to the technical field of wireless communications. The method includes the following steps: in the cell search phase, first search the main cell according to conventional steps and obtain system information and current frame number, and then apply interference deletion to the PBCH/PSS/SSS signal to obtain the neighboring cell system information. Each time a neighboring cell is solved, The system information of the area can be reconstructed by updating only the frame number to reconstruct the PBCH/PSS/SSS local sequence of the cell in each frame; in the channel estimation stage, the received signal of PBCH/PSS/SSS of each frame is taken out and the received signals are listed. It is a system of equations for signals, multi-cell multi-port local sequences and their channel information, and by assuming that adjacent time-frequency resource channels remain unchanged to reduce the number of unknown variables, there is a unique solution to the system of equations. The method of the present invention can simultaneously obtain multi-cell and multi-port interference-free channel information, and when applied to wireless gesture recognition, it can achieve high recognition accuracy in different scenarios.

Description

A method for joint estimation of multi-cell channels in time-division duplex cellular network

Technical field

The invention relates to a method for joint estimation of multi-cell channels in a time-division duplex cellular network, and belongs to the technical field of wireless communications.

Background technique

Time division duplex (TDD) and frequency division duplex (FDD), as two important duplex modes, are widely used in mobile communication networks. TDD is widely used in high-frequency bands because of its channel reciprocity and its advantages of being more suitable for beam forming. Since TDD uses different time slots to distinguish uplink and downlink data, in actual deployment, the entire network is synchronized and uses the same uplink and downlink subframe ratio to prevent uplink and downlink self-interference.

Mobile communication networks generally use cellular networking to achieve coverage in different areas. Compared with inter-frequency networking, co-frequency networking has high spectrum utilization and facilitates terminals (UE) to perform neighbor cell measurements. Therefore, it is widely used in fourth-generation (4G) and fifth-generation (5G) mobile communication systems. But the biggest drawback of co-frequency networking is inter-cell interference (ICI). Inter-cell interference occurs when adjacent cells transmit data in the same resource block (RB) at the same time. Especially when the reference symbols used for channel estimation are interfered with, the estimation results of the channel state information (CSI) will be inaccurate. For traditional communication systems, inter-cell interference will reduce the signal-to-interference-to-noise ratio, causing the bit error rate to increase and the cell throughput rate to decrease. When applied to a synaesthesia integrated system, the channel estimation results are inaccurate, which will cause a decrease in perceptual performance.

In practical applications, inter-cell interference can be reduced to a certain extent through some network deployment solutions and physical layer signal design. 4G/5G networks all use the physical cell identity (PCI) allocation scheme to ensure that neighboring cell reference symbols are distributed in different frequency domain subcarriers. For example, in the 4G physical layer standard Long Term Evolution (LTE), the subcarrier index of the single-port reference symbol is PCI modulo 6, and the subcarrier index of dual-port and four-port is PCI modulo 3. By allocating PCI with different modulus values to adjacent A cell can have cell reference symbols (CRS) on different subcarriers. Similarly, in the 5G physical layer standard New Radio (NR), adjacent cell PCIs are set to different modulo 4 values to ensure different synchronization signals and the demodulation reference symbols (DMRS) in the downlink broadcast channel block (SSB). The frequency domain positions are different.

Although the above method ensures no interference between reference symbols, interference between reference symbols and other signals still exists. For example, in LTE, when a certain RB is used to schedule the downlink control channel (PDCCH) or downlink shared channel (PDSCH), subcarriers other than the CRS of the local cell will be used to fill the PDCCH or PDSCH data. Therefore, the CRS of the primary cell will interfere with the PDCCH and PDSCH of the neighboring cells. Commonly used interference suppression methods include beamforming and interference cancellation. Beamforming can be applied to scenarios where the direction of the interference wave is known, but it relies on multi-antenna processing. When the number of interference flows increases, the effect of beamforming becomes worse. Interference deletion can be achieved with a single antenna, but it requires the interference source sequence to be known, which makes the implementation more complex when the number of interference flows is large. Considering that in cellular networks, the PDCCH/PDSCH of neighboring cells is difficult to solve in this cell, the interference deletion method is difficult to apply.

In addition, in integrated synaesthesia applications such as positioning and gesture recognition based on cellular signals, joint sensing through multi-cell channels can improve accuracy. Since the CRS of each cell is distributed on different subcarriers, in theory, the channel from the terminal to multiple cells can be obtained based on CRS. However, in general, the signal of the primary cell is stronger than that of the adjacent cell, and the reference symbols of the adjacent cell will also be interfered by the signal of the primary cell, and the interference is greater than the interference of the adjacent cell on the primary cell. Therefore, the accuracy of neighbor cell CSI obtained based on CRS is worse than the local cell CSI.

Contents of the invention

In order to suppress inter-cell interference without relying on multiple antennas and obtain CSI of multiple cells at the same time, the present invention proposes a multi-cell channel joint estimation method under a time-division duplex cellular network, using the time-frequency domain position determination in the cellular system. For the broadcast channel, the system information of the current cell and all neighboring cells is first obtained through cell search and interference removal technology, and then the local sequence of the multi-cell multi-port broadcast channel is reconstructed. Then, the multi-cell multi-port CSI is solved simultaneously through the method of solving a system of simultaneous equations. When the number of equations is less than the number of CSI flows to be solved, we reduce the number of unknown CSI variables by assuming that the cell frequency domain channels are the same on adjacent time-frequency resource grids (REs), and achieve a unique solution to the equation.

A method for joint estimation of multi-cell channels in a time-division duplex cellular network. The specific steps are:

Step 1: Search and obtain the primary cell system information in the received multi-cell mixed signal, and calculate the frame numbers of all subsequent frames in sequence based on the frame number of the current frame.

Step 2: Search and obtain all neighboring cell system information in the received multi-cell mixed signal.

Step 3: Reconstruct the local sequence of PBCH/PSS/SSS of all primary cells and neighboring cells at each transmit port in each frame.

Step 4: Take any signal among PBCH/PSS/SSS in each frame, and list the equations about the received signal, multi-cell multi-port local sequence and multi-cell multi-port channel under each RE, as follows:

The relationship between the received signal under each RE, the transmitted signal at each port of each cell and its channel is established as:

Among them, y(k,l), w(k,l) represent the received signal and white noise of subcarrier k and OFDM symbol l respectively; h ^p,c (k,l), x ^p,c (k,l) represent the frequency domain channel and local signal sequence of antenna port p of cell c respectively; C is the total number of cells; P(c) is the number of transmit ports in each cell.

Let the channels of adjacent REs remain unchanged, and the frequency domain channels of K subcarriers and L symbols before and after each subcarrier centered on each subcarrier are the same, then for each RE (k, l), the above formula is approximately a system of equations :

Step 5: Solve the system of equations obtained in Step 4 with each RE as the center to obtain multi-cell multi-port channel estimates.

The advantages of the present invention are:

1. The multi-cell channel joint estimation method under the time-division duplex cellular network of the present invention can reconstruct the local sequence of the broadcast channel of all frames through the decoding result of the broadcast channel of any frame according to the LTE/NR frame format and broadcast channel characteristics;

2. The multi-cell channel joint estimation method under the time-division duplex cellular network of the present invention jointly solves the channels from the terminal to multiple transmitting antennas in multiple cells, and the solution results are not affected by inter-cell interference;

3. The joint estimation method of multi-cell channels in a time-division duplex cellular network of the present invention can simultaneously estimate interference-free channels in multiple cells using only a single receiving antenna;

4. With the multi-cell channel joint estimation method under the time-division duplex cellular network of the present invention, the terminal only needs to meet the minimum system bandwidth requirements of LTE and NR, which can reduce power consumption and complexity.

Description of the drawings

Figure 1 is a flow chart of the method for joint estimation of multi-cell channels in a time division duplex cellular network according to the present invention;

Figure 2 is a multi-cell frequency domain channel obtained by the traditional method based on LTE CRS in the embodiment of the present invention;

Figure 3 is a multi-cell frequency domain channel obtained based on LTE PBCH in the embodiment of the present invention;

Figure 4 is a comparison of the results of time domain main path channel extraction applied in wireless sensing in the embodiment of the present invention;

Figure 5 shows the types of gestures to be recognized in the embodiment of the present invention.

Specific embodiments

The present invention will be further described below in conjunction with the accompanying drawings.

In communication systems, channel estimation is not limited to using specific reference symbols. Any known or solvable sequence can be used for channel estimation. In cellular signals, in addition to reference symbols, there are many channels that are periodically transmitted in the form of broadcasts. The downlink broadcast channel (PBCH)/primary synchronization signal (PSS)/secondary synchronization signal (SSS) in LTE and NR are all sent in fixed time slots and subcarriers at fixed periods. LTE's PBCH/PSS/SSS are at different time domain positions, while NR puts the three together to form SSB.

Among them, the PSS/SSS local sequence is fixed; while the local sequence of each frame of PBCH is different, but the main information block (MIB) bits carried remain unchanged except the frame number. In the LTE/NR frame transmission mode, only one frame is obtained The frame number of all frames can be calculated. The generation from MIB to PBCH strictly follows the 3GPP protocol. When the system information of a cell is known, the PBCH local sequence of all frames can be easily reconstructed. In the TDD system, thanks to the synchronization of the entire network, the PBCH/PSS/SSS of the primary cell and neighboring cells are superimposed on the same time-frequency resource grid (RE). The receiving end will receive the mixed signal superimposed by multiple cell signals on the time-frequency resource grid corresponding to PBCH/PSS/SSS. After cell search, not only the current cell can be searched, but also multiple neighboring cells can be searched through interference removal technology, and the total number of cells, the number of antenna ports of each cell, and the system information of each cell can be obtained.

Through these system information, the multi-cell PSS/SSS/PBCH local sequences under all frames can be reconstructed. When the local sequence is known, the multi-cell channel can be solved from the mixed multi-cell received signal. In LTE, PSS/SSS/PBCH can be used for multi-cell joint channel estimation. Among them, the PSS/SSS cycle is shorter, but only supports single-port transmission; the PBCH cycle is twice that of PSS/SSS, but occupies more resource slots and supports up to four-port transmission. PSS/SSS/PBCH in NR are combined into SSB, but the SSB transmitted on different ports are mapped to different time domain positions. Multi-cell multi-port channels can also be obtained through SSB.

Based on the above content, the present invention designs a multi-cell channel joint estimation method under time division duplex cellular network, as shown in Figure 1. The specific steps are as follows:

Step 1: Search for the primary cell in the 4G-LTE or 5G-NR signal according to the traditional method, synchronize time and frequency and decode the MIB to obtain the primary cell system information such as frame number, bandwidth, etc., and deduce all subsequent frames in sequence through the decoded frame number. frame number, and collect multi-cell mixed signals of PBCH, PSS and SSS in multiple consecutive system frames;

Step 2: Use the interference deletion method to delete the main cell signal from the mixed signal in the collected multi-frame PBCH/PSS/SSS, and then use the conventional cell search method to find the neighboring cell with the highest signal-to-noise ratio, and use PBCH decoding The cyclic redundancy check (CRC) of the MIB is used as the basis to determine whether the neighboring area is successfully solved. Each time a neighboring cell is solved, the MIB and transmit port number of the neighboring cell are recorded. Subsequently, the currently solved neighbor cell is deleted and the next neighbor cell is solved until no new cell is solved.

Step 3: Based on the frame numbers of all frames of the primary cell system derived in step 1, and based on the MIB and number of transmit ports of each neighboring cell recorded in step 2, reconstruct the MIB of the primary cell and all neighboring cells of each frame. Information, replace the bits representing the frame number in the MIB with the bits corresponding to the frame number of each frame, and the remaining bits remain unchanged. And according to the 3GPP protocol, the local sequence of PBCH/PSS/SSS of all primary cells and neighboring cells at each transmit port in each frame and the reference symbols inserted in the middle of the PBCH are reconstructed.

Step 4: Take any signal among PBCH/PSS/SSS in each frame, and list the equations about the received signal, multi-cell local sequence and multi-cell channel under each RE, where the received signal and local sequence are known Variable, multi-cell channel is the variable to be solved, specifically:

401. Establish equations for received signals, multi-cell multi-port local sequences and multi-cell multi-port channels under each RE;

The present invention considers the general multi-cell multi-port situation. For any signal among PBCH/PSS/SSS, the relationship between the signal received under each RE, the signal transmitted by each port of each cell and its channel is:

Among them, y(k,l), w(k,l) represent the received signal and white noise of subcarrier k and OFDM symbol l respectively; h ^p,c (k,l), x ^p,c (k,l) represent the frequency domain channel and local sequence of antenna port p of cell c respectively. C is the total number of cells (including the primary cell); P(c) is the number of transmit ports in each cell. If noise is ignored, for each equation, the received signal y(k,l) and the local sequence of the transmitted signal x ^p,c (k,l) are known variables, and the frequency domain channel h ^p,c (k,l) is an unknown variable. However, because of the number of unknown variables in each equation is greater than 1, so a unique solution cannot be obtained, so a system of equations with a unique solution needs to be established.

402. Establish a system of equations with a unique solution;

In general, the channel changes of adjacent REs are small. In order to make the equation solvable, the channels of adjacent REs are kept unchanged, and the frequency domain channels of K subcarriers and L symbols are centered on each subcarrier. are the same, then for each RE(k,l), equation (1) can be approximated as a system of equations:

Therefore, for any group (k,l), the number of unknown variables h ^p,c (k,l) is still But the number of equations becomes (2K+1)(2L+1), which requires/> A system of equations must have a unique solution.

To simplify the expression, write the above equation in matrix form:

y(k,l)=X(k,l)h(k,l)+w(k,l),

in, Represents the set vector of the received signal and noise centered on RE(k,l) respectively,/> is the set vector of multi-cell multi-port channels,/> is the multi-cell multi-port local sequence collection matrix.

Step 5. Use least squares estimation (LS) or other estimation methods (LMMSE, MMSE, etc.) to solve the system of equations centered on each RE to obtain multi-cell multi-port channel estimates.

In this invention, the channel estimation value is obtained by the least squares method:

Example:

Taking wireless gesture recognition as an example, by receiving mobile communication signals in space, estimating channel state information, and analyzing the changes in the propagation channel over time, we can identify which gesture the user made. In a home scenario, the main TDD-LTE signal source is China Mobile's B40 band signal, with a center frequency of 2.3498GHz and a bandwidth of 20MHz. The PCI of the main cell is 252, and there are two adjacent cells with PCIs of 249 and 256 in this scenario. All cells are single-port configurations. First, CRS is used to estimate the frequency domain channel of multiple cells. The results are shown in Figure 2. Affected by inter-cell interference, there are many burrs in the CRS-based channel estimation results. These burrs are irregularly distributed in the time-frequency domain. When the method of the present invention is used for channel estimation, the results obtained are shown in Figure 3. Among them, PBCH is used for channel estimation, K=2, L=1. It can be seen that the estimated multi-cell channels have no interference. , even for neighboring cells with weak signals, the channel estimation results are very smooth.

In order to realize gesture recognition, the present invention converts the frequency domain channel to the time domain through inverse Fourier transform, and the result is shown in Figure 4. By extracting the main path on the 20MHz bandwidth, the interference received by the CRS main path channel in the first half of the sampling time is significantly reduced. However, in the second half of the sampling time, when the PDCCH/PDSCH of the neighboring cell occupies a large number of REs, the number of interfered CRSs increases, and the extracted main path interference also becomes larger. Moreover, the size of the interference is comparable to the fluctuation caused by hand movement (between sampling points 100-150), which will obviously affect the results of gesture recognition. The main path extracted based on PBCH is smooth and the gesture effect is obvious. Obvious fluctuations in CSI can be observed even in the neighborhood of PCI 256. The PBCH-based method only uses LTE's minimum system bandwidth of 1.4MHz, and the effect is significantly better than CRS based on 20MHz bandwidth.

After the main path channel is extracted, the same method is used to further process the CRS-based channel estimation and the PBCH-based channel estimation. The influence of phase noise is removed through multi-antenna CSI phase, and the dynamic path is extracted through band-pass filtering. Finally, by calculating the Doppler frequency shift, the changes in hand speed and direction with respect to time can be obtained, and the corresponding gestures can be identified. Several gestures shown in Figure 5 are designed here, and experiments are conducted in two home scenarios, the living room and the bedroom, to calculate the recognition accuracy of each gesture. In each scenario, 400 gestures were tested to compare the accuracy of the present invention and the traditional CRS-based channel estimation method. The results are shown in Table 1. When the channel estimation method based on the present invention is used for gesture recognition, it can achieve a high accuracy of more than 93% in both scenarios. And after comparison, the accuracy of the method based on the present invention is much higher. Based on CRS channel estimation method.

Table 1 Gesture recognition accuracy rate under the present invention and traditional method

Claims (4)

1. A method for joint estimation of multi-cell channels in a time-division duplex cellular network, which is characterized by: The specific steps are: Step 1: Search and obtain the main cell system information in the received multi-cell mixed signal, and deduce the frame numbers of all subsequent frames in sequence based on the frame number of the current frame; Step 2: Search and obtain all neighboring cell system information in the received multi-cell mixed signal; Step 3: Reconstruct the local sequence of PBCH/PSS/SSS of all primary cells and neighboring cells at each transmit port in each frame; Step 4: Take any signal among PBCH/PSS/SSS in each frame, and list the equations about the received signal, multi-cell multi-port local sequence and multi-cell multi-port channel under each RE. The method is: The relationship between the received signal under each RE, the transmitted signal at each port of each cell and its channel is established as: Among them, y(k,l), w(k,l) represent the received signal and white noise of subcarrier k and OFDM symbol l respectively; h ^p,c (k,l), x ^p,c (k,l) Represent the frequency domain channel and local signal sequence of antenna port p of cell c respectively; C is the total number of cells; P(c) is the number of transmit ports of each cell; It is considered that the channels of adjacent REs remain unchanged, and the frequency domain channels of K subcarriers and L symbols centered on each RE are the same, then for each RE (k, l), the above formula is approximately a system of equations : Step 5: Solve the system of equations obtained in Step 4 with each RE as the center to obtain multi-cell multi-port channel estimates. 2. A method for joint estimation of multi-cell channels in a time-division duplex cellular network as claimed in claim 1, characterized in that: the neighboring cell system information acquisition method is: deleting the main signal from the multi-cell mixed signal obtained in step 1. The signal of the cell is then found, and then the neighboring cell with the highest signal-to-noise ratio is found, and the cyclic redundancy check of the MIB decoded by the PBCH is used as the basis to determine whether the neighboring cell is successfully decoded; each time a neighboring cell is decoded, the MIB of the neighboring cell is recorded. and the number of transmitting ports; then, the currently solved neighbor cell is deleted and the next neighbor cell is solved until no new cell is solved. 3. A method for joint estimation of multi-cell channels in a time-division duplex cellular network as claimed in claim 1, characterized in that: in step 3, first the MIB information of the main cell and all neighboring cells of each frame needs to be reconstructed, Replace the bits representing the frame number in the MIB with the bits corresponding to the frame number of each frame; then reconstruct the local sequence of the PBCH/PSS/SSS of all primary cells and neighboring cells at each transmit port in each frame. 4. A method for joint estimation of multi-cell channels in a time-division duplex cellular network as claimed in claim 1, characterized in that: in step 4, K and L need to satisfy: Among them, C is the total number of cells; P(c) is the number of transmit ports in each cell.