A method for joint channel estimation in multi-cell networks under time-division duplex cellular networks

Abstract

This invention discloses a method for joint channel estimation of multiple cells in a time-division duplex cellular network, belonging to the technical field of wireless communication. The method includes the following steps: In the cell search phase, the primary cell is first searched according to conventional steps to obtain system information and the current frame number. Then, interference removal is applied to the PBCH / PSS / SSS signals to obtain neighboring cell system information. For each neighboring cell's system information obtained, the local PBCH / PSS / SSS sequence of that cell in each frame can be reconstructed by updating only the frame number. In the channel estimation phase, the received signal of each frame's PBCH / PSS / SSS is extracted, and a system of equations is listed, consisting of the received signal, the local sequences of multiple cells and ports, and their channel information. By assuming that adjacent time-frequency resource channels remain unchanged to reduce the number of unknown variables, the system of equations has a unique solution. The method of this invention can simultaneously obtain interference-free channel information for multiple cells and ports, and when applied to wireless gesture recognition, it can achieve high recognition accuracy in different scenarios.

Description

Technical Field

[0001] This invention relates to a method for joint channel estimation in multiple cells under time-division duplex cellular networks, belonging to the technical field of wireless communication. Background Technology

[0002] Time Division Duplex (TDD) and Frequency Division Duplex (FDD) are two important duplexing modes, both widely used in mobile communication networks. TDD, due to its channel reciprocity and suitability for beamforming, is widely used in high-frequency bands. Because TDD uses different time slots to distinguish uplink and downlink data, in actual deployments, the entire network is synchronized and uses the same uplink / downlink subframe ratio to prevent uplink / downlink self-interference.

[0003] Mobile communication networks typically employ cellular networking to achieve coverage in different areas. Compared to inter-frequency networking, co-frequency networking offers higher spectrum utilization and facilitates neighbor cell measurements by the user terminal (UE), thus it is widely used in fourth-generation (4G) and fifth-generation (5G) mobile communication systems. However, the biggest drawback of co-frequency networking is inter-cell interference (ICI). Inter-cell interference occurs when adjacent cells simultaneously transmit data in the same resource block (RB). In particular, interference to the reference symbols used for channel estimation leads to inaccurate channel state information (CSI) estimation. For traditional communication systems, inter-cell interference reduces the signal-to-interference-plus-noise ratio (SNR), increases the bit error rate, and decreases cell throughput. When applied to integrated sensing systems, inaccurate channel estimation results degrade sensing performance.

[0004] In practical applications, inter-cell interference can be reduced to some extent through certain network deployment schemes and physical layer signal designs. Both 4G and 5G networks use Physical Cell Identifier (PCI) allocation schemes to ensure that neighboring cell reference symbols are distributed on different frequency domain subcarriers. For example, in the 4G physical layer standard Long Term Evolution (LTE), the subcarrier index of a single-port reference symbol is PCI modulo 6, while the subcarrier indexes of dual-port and quad-port reference symbols are PCI modulo 3. By assigning different modulo values ​​of PCI to neighboring cells, the cell reference symbol (CRS) can be placed on different subcarriers. Similarly, in the 5G physical layer standard New Radio (NR), neighboring cells are assigned different modulo 4 values ​​of PCI to ensure that the frequency domain positions of the demodulation reference symbol (DMRS) in different synchronization signals and downlink broadcast channel blocks (SSBs) are different.

[0005] While the above methods ensure 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 cell's CRS will be used to fill the PDCCH or PDSCH data. Therefore, the primary cell's CRS will interfere with the PDCCH and PDSCH of neighboring cells. Common interference suppression methods include beamforming and interference cancellation. Beamforming can be applied in scenarios where the direction of interference is known, but it relies on multi-antenna processing. As the number of interference streams increases, the effectiveness of beamforming deteriorates. Interference cancellation can be implemented with a single antenna, but it requires the sequence of interference sources to be known, and its implementation complexity is high when the number of interference streams is large. Considering that in cellular networks, it is difficult to solve the PDCCH / PDSCH of neighboring cells in the local cell, interference cancellation methods are difficult to apply.

[0006] Furthermore, in integrated sensing applications such as cellular signal-based positioning and gesture recognition, accuracy can be improved through joint sensing of multiple cell channels. Since the CRS (Channel Reference Signal) of each cell is distributed across different subcarriers, theoretically, the channel information from the terminal to multiple cells can be obtained based on the CRS. However, in general, the primary cell signal is stronger than that of neighboring cells, and the reference symbols of neighboring cells are also subject to interference from the primary cell signal, and this interference is greater than the interference from neighboring cells to the primary cell. Therefore, the accuracy of neighboring cell CSI obtained based on CRS is worse than that of the local cell CSI. Summary of the Invention

[0007] To suppress inter-cell interference without relying on multiple antennas and simultaneously obtain the CSI of multiple cells, this invention proposes a method for joint estimation of multi-cell channels in time-division duplex cellular networks. Utilizing the broadcast channels with time-frequency domain locations determined in the cellular system, the system information of the current cell and all neighboring cells is first obtained through cell search and interference cancellation techniques, thereby reconstructing the local sequence of the multi-cell multi-port broadcast channels. Then, the multi-cell multi-port CSI is simultaneously solved by solving a system of simultaneous equations. When the number of equations is less than the number of CSI streams to be solved, we assume that the cell frequency domain channels are identical in adjacent time-frequency resource grids (REs), reducing the number of unknown CSI variables and ensuring a unique solution to the equations.

[0008] A method for joint channel estimation in multi-cell networks under time-division duplex cellular networks, the specific steps of which are as follows:

[0009] Step 1: Search for 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 according to the frame number of the current frame.

[0010] Step 2: Search for and obtain information about all neighboring cell systems in the received multi-cell mixed signal.

[0011] Step 3: Reconstruct the local sequence of PBCH / PSS / SSS for each transmit port of all primary and neighboring cells in each frame.

[0012] Step 4: Take any one of the signals from PBCH / PSS / SSS in each frame, and list the equations for the received signal, multi-cell multi-port local sequence, and multi-cell multi-port channel under each RE, as follows:

[0013] The relationship between the received signal under each RE, the transmitted signal at each port of each cell, and their channels is established as follows:

[0014]

[0015] Where y(k,l) and 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 for each cell.

[0016] Assuming that the channels of adjacent REs remain unchanged, and that the frequency domain channels of the K subcarriers and L symbols preceding and following each subcarrier are identical, then for each RE(k,l), the above equation approximates as a system of equations:

[0017]

[0018] Step 5: Solve the system of equations obtained in Step 4 with each RE as the center to obtain the multi-cell multi-port channel estimate.

[0019] The advantages of this invention are:

[0020] 1. The method for joint channel estimation of multiple cells in time-division duplex cellular networks of the present invention can reconstruct the local sequence of broadcast channels of all frames by using the decoding result of the broadcast channel of any frame, based on the LTE / NR frame format and broadcast channel characteristics.

[0021] 2. The method for joint channel estimation of multiple cells in time-division duplex cellular networks of the present invention jointly solves the channel from the terminal to multiple cells and multiple transmit antennas, and the solution is not affected by inter-cell interference;

[0022] 3. The method for joint channel estimation of multiple cells in time-division duplex cellular networks of the present invention can simultaneously estimate the interference-free channels of multiple cells using only a single receiving antenna;

[0023] 4. The method for joint channel estimation of multiple cells in time-division duplex cellular networks of the present invention only requires the terminal to meet the minimum system bandwidth requirements of LTE and NR, which can reduce power consumption and complexity. Attached Figure Description

[0024] Figure 1 This is a flowchart of the method for joint channel estimation of multiple cells in a time-division duplex cellular network according to the present invention;

[0025] Figure 2 This is a traditional method in the embodiments of the present invention based on the multi-cell frequency domain channel obtained by LTE CRS;

[0026] Figure 3 This is a multi-cell frequency domain channel obtained based on LTE PBCH in an embodiment of the present invention;

[0027] Figure 4 This is a comparison of the results of temporal main path channel extraction applied to wireless sensing in the embodiments of the present invention;

[0028] Figure 5 This refers to the type of gesture to be recognized in the embodiments of the present invention. Specific Implementation

[0029] The invention will now be further described with reference to the accompanying drawings.

[0030] 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, besides reference symbols, many channels are periodically transmitted in broadcast form. In LTE and NR, the Downlink Broadcast Channel (PBCH), Primary Synchronization Signal (PSS), and Secondary Synchronization Signal (SSS) are all transmitted in fixed time slots and subcarriers at fixed periods. In LTE, the PBCH, PSS, and SSS are located in different time domain positions, while in NR, they are grouped together to form the SSB.

[0031] In this system, the local sequences of PSS / SSS are fixed; while the local sequence of PBCH varies for each frame, but the main information block (MIB) bits, except for the frame number, remain unchanged. In LTE / NR frame transmission mode, the frame numbers of all frames can be deduced by obtaining only the frame number of one frame. The generation from MIB to PBCH strictly follows the 3GPP protocol. When the system information of a cell is known, the local sequences of PBCH for all frames can be easily reconstructed. In TDD systems, thanks to network-wide synchronization, the PBCH / PSS / SSS of the primary cell and neighboring cells are superimposed on the same time-frequency resource grid (RE). The receiver will receive a mixed signal of multiple cell signals superimposed on the time-frequency resource grid corresponding to the PBCH / PSS / SSS. After cell search, not only the local cell can be found, but multiple neighboring cells can also be found through interference cancellation technology, obtaining the total number of cells, the number of antenna ports in each cell, and the system information of each cell.

[0032] Using this system information, the local sequences of PSS / SSS / PBCH for all cells in all frames can be reconstructed. With the local sequences known, the multi-cell channels can be solved from the mixed multi-cell received signals. In LTE, PSS / SSS / PBCH can all be used for multi-cell joint channel estimation. PSS / SSS has a shorter period but only supports single-port transmission; PBCH has twice the period of PSS / SSS but occupies more resource grids and supports up to four-port transmission. In NR, PSS / SSS / PBCH are merged into SSB, but SSBs transmitted on different ports are mapped to different time domain locations. Multi-cell multi-port channels can also be obtained through SSB.

[0033] Based on the above, this invention designs a method for joint channel estimation in multi-cell networks under time-division duplex cellular networks, such as... Figure 1 As shown, the specific steps are as follows:

[0034] Step 1: Search for the main cell in 4G-LTE or 5G-NR signals using traditional methods, synchronize time and frequency and decode MIB to obtain main cell system information such as frame number and bandwidth, calculate the frame number of all subsequent frames in sequence based on the decoded frame number, and collect multi-cell mixed signals of PBCH, PSS and SSS in multiple consecutive system frames.

[0035] Step 2: In the acquired multi-frame PBCH / PSS / SSS, interference removal is used to remove the main cell's signal from the mixed signal. Then, the neighboring cell with the highest signal-to-noise ratio is found using the conventional cell search method. The Cyclic Redundancy Check (CRC) of the MIB decoded from the PBCH is used as the basis to determine whether the neighboring cell has been successfully decoded. For each newly decoded neighboring cell, the MIB and the number of transmit ports of that neighboring cell are recorded. Subsequently, the currently decoded neighboring cell is deleted, and the next neighboring cell is decoded, until no new cell is decoded.

[0036] Step 3: Based on the frame numbers of all frames in the primary cell system derived in Step 1, and according to the MIBs and transmit port numbers of each neighboring cell recorded in Step 2, reconstruct the primary cell and all neighboring cell MIB information for each frame. Replace the bit representing the frame number in the MIB with the bit corresponding to the frame number of each frame, leaving the remaining bits unchanged. Furthermore, reconstruct the local sequence of PBCH / PSS / SSS for each transmit port of each primary cell and neighboring cells in each frame, as well as the reference symbols inserted in the middle of the PBCH, according to the 3GPP protocol.

[0037] Step 4: For each frame, take any one of the signals from PBCH / PSS / SSS, and list the equations for the received signal, multi-cell local sequence, and multi-cell channel under each RE, where the received signal and local sequence are known variables, and the multi-cell channel is the variable to be solved. Specifically:

[0038] 401. Establish equations for the received signal, multi-cell multi-port local sequence, and multi-cell multi-port channel under each RE;

[0039] This invention considers a typical multi-cell, multi-port scenario. For any signal among PBCH / PSS / SSS, the relationship between the received signal under each RE, the transmitted signal at each port of each cell, and their channels is as follows:

[0040]

[0041] Where y(k,l) and 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 in cell c, respectively. C is the total number of cells (including the primary cell); P(c) is the number of transmit ports for each cell. If noise is ignored, for each equation, the received signal y(k,l) and the transmitted signal local sequence x... p,c (k,l) are known variables, and the frequency domain channel h is... p,c (k,l) are unknown variables. However, because the number of unknown variables in each equation... Since the value is greater than 1, a unique solution cannot be obtained. Therefore, it is necessary to establish a system of equations with a unique solution.

[0042] 402. Establish a system of equations with a unique solution;

[0043] In general, the channel changes between adjacent REs are small. To make the equation solvable, the channels of adjacent REs are kept constant, and the frequency domain channels of the K subcarriers and L symbols before and after each subcarrier are the same. Then, for each RE(k,l), equation (1) can be approximated as a system of equations:

[0044]

[0045] Therefore, for any set (k,l), the unknown variable h p,c The number of (k,l) remains the same. However, the number of equations becomes (2K+1)(2L+1), which requires... Only when the system of equations has a unique solution can it exist.

[0046] To simplify the expression, the above formula is written in matrix form:

[0047] y(k,l)=X(k,l)h(k,l)+w(k,l),

[0048] in, These represent the set vectors of received signal and noise centered at RE(k,l), respectively. It is a set vector of multi-cell, multi-port channels. It is a matrix of local sequence sets for multiple cells and multiple ports.

[0049] 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 the multi-cell multi-port channel estimate.

[0050] In this invention, the channel estimate is obtained using the least squares method:

[0051]

[0052] Example:

[0053] 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, the system can identify which gesture the user is making. In a home scenario, the main TDD-LTE signal source is China Mobile's B40 band signal, with a center frequency of 2.3498 GHz and a bandwidth of 20 MHz. The primary cell has a PCI of 252, and there are two neighboring cells with PCIs of 249 and 256 in this scenario. All cells are single-port configured. First, the frequency domain channels of multiple cells are estimated using CRS, and the results are as follows: Figure 2 As shown, due to inter-cell interference, the channel estimation results based on CRS contain many spikes, which are irregularly distributed in the time and frequency domains. However, when the method of this invention is used for channel estimation, the results obtained are as follows: Figure 3 As shown, PBCH is used for channel estimation, with K=2 and L=1. It can be seen that the estimated channels of multiple cells are free from interference, and even the channel estimation results of neighboring cells with weaker signals are very smooth.

[0054] To achieve gesture recognition, this invention transforms the frequency domain channel into the time domain using an inverse Fourier transform, as shown in the following figure. Figure 4 As shown, by extracting the main path on a 20MHz bandwidth, the interference to the main path channel of the CRS is significantly reduced in the first half of the sampling time. However, in the second half of the sampling time, when the PDCCH / PDSCH of neighboring cells occupy a large number of REs, the number of CRSs affected by interference increases, and the interference of the extracted main path also increases. Moreover, the magnitude of the interference is comparable to the fluctuation caused by hand movements (between sampling points 100-150), which obviously affects the result of gesture recognition. In contrast, the main path extracted based on PBCH is smooth, and the gesture effect is obvious. Even in neighboring cells with a PCI of 256, obvious fluctuations in CSI can be observed. The PBCH-based method only uses the minimum system bandwidth of LTE, 1.4MHz, and its performance is significantly better than that of CRS based on a 20MHz bandwidth.

[0055] After extracting the main path channel, the same method is used to further process the CRS-based and PBCH-based channel estimations. Phase noise is removed using multi-antenna CSI phase filtering, and the dynamic path is extracted using bandpass filtering. Finally, the Doppler frequency shift is calculated to obtain the time-varying changes in hand speed and direction, thus recognizing the corresponding gesture. This design incorporates... Figure 5 Several gestures were shown, and experiments were conducted in two home scenarios: the living room and the bedroom. The recognition accuracy of each gesture was statistically analyzed. In each scenario, 400 gestures were tested, and the accuracy of the present invention and the traditional CRS-based channel estimation method were compared. 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 over 93% in both scenarios. Furthermore, the accuracy of the method based on the present invention is significantly higher than that of the CRS-based channel estimation method.

[0056] Table 1. Gesture recognition accuracy of the present invention and traditional methods

[0057]

Claims

1. A method for joint channel estimation of multiple cells in a time division duplex cellular network, characterized in that: 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 order according to the frame number of the current frame; Step 2: search and obtain the system information of all neighboring cells in the received multi-cell mixed signal; Step 3: reconstruct the local sequences of PBCH / PSS / SSS of all primary cells and neighboring cells at each transmission port in each frame; first, reconstruct the MIB information of the primary cell and all neighboring cells in each frame, 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 sequences of PBCH / PSS / SSS of all primary cells and neighboring cells at each transmission port in each frame; Step 4: take any one of PBCH / PSS / SSS in each frame, list the equations about the received signal, multi-cell multi-port local sequence and multi-cell multi-port channel at each RE, the method is: Establish the relationship between the received signal at each RE, the transmission signal of each cell and each port, and its channel as: where 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 of antenna port p of cell c and the local signal sequence, respectively; C is the total number of cells; P(c) is the number of transmitting ports of each cell; Consider that the channels of adjacent REs remain unchanged, and the frequency domain channels of K subcarriers and L symbols before and after each RE are the same, then for each RE (k, l), the above equation is approximately a system of equations: k'∈[k-K,k+K],l'∈[l-L,l+L] Step 5: solve the system of equations obtained in step 4 with each RE as the center to obtain the multi-cell multi-port channel estimation value.

2. The method of claim 1, wherein the method is performed in a time division duplex (TDD) cellular network. The method for obtaining the system information of neighboring cells is: delete the signal of the primary cell in the multi-cell mixed signal obtained in step 1, then find the neighboring cell with the highest signal-to-noise ratio, and use the cyclic redundancy check of the MIB decoded by PBCH to determine whether the neighboring cell is successfully decoded; record the MIB and the number of transmission ports of the neighboring cell every time a new neighboring cell is decoded; then, delete the currently solved neighboring cell to solve the next neighboring cell until no new cell is decoded.

3. The method of claim 1, wherein the method is performed in a time division duplex (TDD) cellular network. In step 4, K and L need to satisfy: Where C is the total number of cells; P(c) is the number of transmission ports of each cell.

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