A phase noise estimation method and apparatus

Abstract

The application provides a phase noise estimation method and device, relates to the technical field of communication, and is used for improving phase noise estimation accuracy. The phase noise estimation method provided by the application comprises the following steps: acquiring a pilot signal and a data signal from a received signal; filtering the pilot signal to obtain a pilot filtered signal, comparing the pilot filtered signal with a theoretical pilot signal, and obtaining a pilot phase noise value; respectively performing forward filtering and backward filtering on the data signal to obtain a forward filtered signal and a backward filtered signal, and respectively determining a first phase noise value of the forward filtered signal and a second phase noise value of the backward filtered signal according to the pilot phase noise value; compensating the data signal according to the first phase noise value to obtain a first compensation signal; compensating the data signal according to the second phase noise value to obtain a second compensation signal; and selecting one compensation signal from the first compensation signal and the second compensation signal as a demodulation signal of the received signal.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a phase noise estimation method and apparatus. Background Technology

[0002] Terahertz active cable (TAC) equipment is a wired high-speed data communication device used to achieve high-density, high-speed data signal transmission. TAC equipment mainly consists of a plastic cable with terahertz waveguide capability and transceivers with standard package sizes connected to both ends of the plastic cable. The plastic cable is used for transmitting modulated signals; the transceivers are used for bidirectional transmission and reception of data signals. Due to the relatively high transmission loss of plastic cables, transceivers typically employ a coherent communication architecture to provide greater signal bandwidth and data transmission rates over longer transmission distances. Specifically, taking this transceiver, which includes a transmitting module and a receiving module, as an example, the transmitting module modulates the externally input data signal S(t) onto a local terahertz carrier LOt to obtain a modulated signal. Here, LO is an abbreviation for local, and t is an abbreviation for transmission. This modulated signal is transmitted to the receiving module on the other side via a plastic cable. The receiving module then uses another local terahertz carrier LOr to mix the modulated signal, where r is an abbreviation for receive, to obtain the demodulated data signal R(t). Because the two carriers LOt and LOr have different stability characteristics, there is a time-varying phase difference φ(t) between them. During the modulation and demodulation process, this phase difference φ(t) is added to the phase of the data signal S(t) and transmitted to the demodulated data signal R(t), forming phase noise. In high-speed communication scenarios, the bit error rate of the data signal is required to be extremely low, generally less than 10%. -6 In this situation, the phase noise generated by the phase difference between the two carriers Lot and Lor can lead to a severe bit error rate bottleneck. Therefore, to ensure the required bit error rate, it is necessary to estimate and track the change in the phase difference φ(t) in the data signal S(t) and compensate for this phase difference in the data signal R(t). Existing technologies estimate the phase noise in the data signal using the following two methods.

[0003] Option 1 involves estimating the phase noise at the location of each data signal within a data signal segment using pilot signals. For a data signal segment, the phase noise at the pilot signals at both ends of the data signal is first estimated, for example, denoted as φ(ta) and φ(tb). Then, linear or polynomial interpolation is used to estimate the phase noise at the location of each data signal within the segment, for example, denoted as... Here, F(.) represents the interpolation function. However, this phase noise estimation method only uses information from the pilot signals at both ends of the data signal segment, and because the pilot intervals are far apart and the correlation is weak, the accuracy of phase noise tracking is low, making it difficult to meet the needs of low bit error rate scenarios.

[0004] Scheme 2 involves using the phase noise estimate φ(t-1) from the previous time step to compensate for the phase noise of the data signal R(t) at the current time step t. The compensated signal R'(t) is then used to determine the estimated value S'(t) of the data signal S(t) at time step t. The phase noise φ(t) at the current time step t is then estimated based on the difference between R(t) and S'(t). This process is iterated to achieve phase noise estimation and compensation for all data signals. However, since the phase noise at times t and t-1 is not equal, the compensated signal R'(t) still carries some residual phase noise, increasing the probability of incorrect decisions for R'(t). If R'(t) is incorrectly determined, the receiving module will obtain an estimate S'(t) that is completely different from the data signal S(t). The phase noise calculated based on R(t) and S'(t) will also be biased. During the iteration process, this bias will further affect the phase noise estimation and compensation of subsequent signals. Moreover, when the phase noise of the receiving module is large, or the signal modulation mode is high, this estimation leads to an increased probability of error propagation, which in turn leads to a rapid deterioration of the bit error rate. Summary of the Invention

[0005] This application provides a phase noise estimation method and apparatus. This phase noise estimation method improves the accuracy of phase noise estimation while meeting the requirement of low bit error rate for data signals. To achieve the above objective, the embodiments of this application adopt the following technical solution:

[0006] In a first aspect, a phase noise estimation method is provided. The method includes: acquiring a pilot signal and a data signal from a received signal; filtering the pilot signal to obtain a pilot-filtered signal; comparing the pilot-filtered signal with a theoretical pilot signal to obtain a pilot phase noise value; wherein the pilot signal may include a first pilot component signal and a second pilot component signal located at the beginning and end of the data signal, respectively; the first pilot component signal corresponds to a first pilot phase noise value; the second pilot component signal corresponds to a second pilot phase noise value; and forward filtering and backward filtering are performed on the data signal to obtain a forward-filtered signal. The system receives a forward-filtered signal and a backward-filtered signal, and determines the first phase noise value of the forward-filtered signal and the second phase noise value of the backward-filtered signal based on the pilot phase noise value. Specifically, the first phase noise value is determined based on the first pilot phase noise value corresponding to the first pilot component signal, and the second phase noise value is determined based on the second pilot phase noise value corresponding to the second pilot component signal. The data signal is compensated based on the first phase noise value to obtain a first compensated signal, and the data signal is compensated based on the second phase noise value to obtain a second compensated signal. One of the first compensated signal and the second compensated signal is selected as the demodulation signal of the received signal.

[0007] In the above technical solution, the pilot signal is filtered to obtain a pilot-filtered signal, and the pilot-filtered signal is compared with the pilot signal to obtain the pilot phase noise value. Forward and backward filtering are performed on the data signal, and the first and second phase noise values ​​of the data signal are determined based on the pilot phase noise value. This process fully utilizes the correlation between the phase noise values ​​on the time axis, improving the accuracy of phase noise value estimation. Furthermore, the forward and backward filtering processes are independent of each other, preserving the difference between the estimated trajectories of the first and second phase noise values. This difference is used to perform symbol determination on the data signals after compensation for the first and second phase noise values, respectively. Based on this, FEC (Fault-Corrected Evidence) calculations are used to correct the differences in the data signals, thereby improving the accuracy of phase noise estimation and further ensuring the requirement for a low bit error rate in the data signal.

[0008] In one possible implementation of the first aspect, the theoretical pilot signal is the pilot signal included in the original signal corresponding to the received signal (i.e., the original pilot signal). In the above possible implementation, the theoretical pilot signal can be pre-configured to the transmitting module and the receiving module. By comparing the theoretical pilot signal with the filtered pilot signal, the phase noise value corresponding to the pilot signal is obtained, thereby ensuring the accuracy of the pilot phase noise value.

[0009] In one possible implementation of the first aspect, the pilot signal obtained from the received signal includes a first pilot component signal and a second pilot component signal located at the beginning and end of the data signal, respectively. The first pilot component signal corresponds to a first pilot phase noise value, and the second pilot component signal corresponds to a second pilot phase noise value. Determining the first phase noise value of the forward-filtered signal and the second phase noise value of the backward-filtered signal based on the pilot phase noise values ​​includes: determining the first phase noise value of the forward-filtered signal based on the first pilot phase noise value; and determining the second phase noise value of the backward-filtered signal based on the second pilot phase noise value. In the above possible implementation, the first phase noise value of the forward-filtered signal is determined using the first pilot phase noise value, and the second phase noise value of the backward-filtered signal is determined using the second pilot phase noise value. This process fully utilizes the correlation between the phase noise values ​​on the time axis, improving the accuracy of the estimation of the first and second phase noise values.

[0010] In one possible implementation of the first aspect, both the forward-filtered signal and the backward-filtered signal include M consecutive data component signals, where M is a positive integer; for the M data component signals included in the forward-filtered signal, determining the first phase noise value of the forward-filtered signal based on the first pilot phase noise value includes: determining the phase noise value of the first data component signal among the M data component signals based on the first pilot phase noise value, and determining the phase noise value of the (i+1)th data component signal among the M data component signals based on the phase noise value of the i-th data component signal among the M data component signals. The first phase noise value is obtained by taking the value of i from 1 to M-1. For the M data component signals included in the backward filtered signal, the second phase noise value of the backward filtered signal is determined based on the second pilot phase noise value, including: determining the phase noise value of the last data component signal among the M data component signals based on the second pilot phase noise value, and determining the phase noise value of the j-th data component signal among the M data component signals based on the phase noise value of the (j+1)-th data component signal among the M data component signals, so as to obtain the second phase noise value, where the value of j ranges from 1 to M-1. In the above possible implementation, the correlation between the phase noise values ​​on the time axis is fully utilized, and the forward filtering and backward filtering are independent of each other during the filtering process. The difference between the estimated trajectories of the first phase noise value and the second phase noise value is preserved, and the difference is used to perform sign decision on the data signals after compensation for the first phase noise value and the second phase noise value, respectively. On this basis, the difference in the data signal is corrected by FEC verification calculation, thereby improving the accuracy of phase noise estimation.

[0011] In one possible implementation of the first aspect, the first compensation signal and the second compensation signal are compared to determine the data location of unreliable data; the data component signal located at the data location in the data signal is subjected to forward filtering and backward filtering respectively to obtain forward component filtered signal and backward component filtered signal; the first component phase noise value of the forward component filtered signal and the second component phase noise value of the backward component filtered signal are determined respectively; the data component signal is compensated according to the first component phase noise value and the second component phase noise value respectively to obtain the first data component signal and the second data component signal; the first compensation signal and the second compensation signal are corrected according to the first data component signal and the second data component signal. In the above possible implementation, by comparing the first compensation signal and the second compensation signal, the data location of unreliable data in the data signal has been determined, and the data component signal located at the data location of the unreliable data has been determined. The data component signal is then subjected to forward filtering and backward filtering again, further ensuring the accuracy of phase noise estimation in the low bit error rate range.

[0012] In one possible implementation of the first aspect, obtaining the pilot signal and data signal from the received signal includes performing a serial-to-parallel conversion on the received signal to obtain a data block; and separating the pilot signal and the data signal from the data block. In the above possible implementation, separating the pilot signal and the data signal, and filtering the pilot signal and the data signal independently, ensures the independence of the filtering of the pilot signal and the data signal, and guarantees the accuracy of the phase noise estimation.

[0013] In one possible implementation of the first aspect, selecting one compensation signal from the first compensation signal and the second compensation signal as the demodulation signal of the received signal includes determining the forward bit error rate (BER) of the first compensation signal and the backward BER of the second compensation signal; and using the compensation signal corresponding to the smaller BER of the forward and backward BER as the demodulation signal of the received signal. In the above possible implementation, selecting the compensation signal corresponding to the smaller BER of the forward and backward BER as the demodulation signal of the received signal improves the accuracy of the compensation signal, thereby ensuring the requirement for a low bit error rate in the data signal.

[0014] In one possible implementation of the first aspect, the first compensation signal and the second compensation signal are signals after symbol decision. In the above possible implementation, symbol decision is performed on the data signals compensated for the first phase noise value and the second phase noise value to obtain the first compensation signal and the second compensation signal, further eliminating the difference in phase noise estimation and ensuring the accuracy of phase noise estimation.

[0015] In one possible implementation of the first aspect, the filtering is a Kalman filter. In the above possible implementation, Kalman filtering is applied to the pilot signal, and forward and backward Kalman filtering is applied to the data signal, ensuring the accuracy of the estimated pilot phase noise value, the first phase noise value, and the second phase noise value.

[0016] In one possible implementation of the first aspect, the filtering is either single-signal filtering or simultaneous multi-signal filtering. The above-described possible implementations can reduce the complexity of the filtering, thereby improving the speed of phase noise estimation.

[0017] In a second aspect, an apparatus is provided, comprising: an acquisition unit for acquiring a pilot signal and a data signal from a received signal; a first filtering estimation unit for filtering the pilot signal to obtain a pilot filtered signal; comparing the pilot filtered signal with a theoretical pilot signal to obtain a pilot phase noise value; a second filtering unit for performing forward filtering on the data signal to obtain a forward filtered signal; a third filtering unit for performing backward filtering on the data signal to obtain a backward filtered signal; a first estimation unit for determining a first phase noise value of the forward filtered signal and a second phase noise value of the backward filtered signal based on the pilot phase noise value; a compensation unit for compensating the data signal based on the first phase noise value to obtain a first compensated signal, and compensating the data signal based on the second phase noise value to obtain a second compensated signal; and a second estimation unit for selecting one of the first compensated signal and the second compensated signal as the demodulated signal of the received signal.

[0018] In one possible implementation of the second aspect, the theoretical pilot signal is the pilot signal included in the original signal corresponding to the received signal.

[0019] In one possible implementation of the second aspect, the pilot signal obtained from the received signal includes a first pilot component signal and a second pilot component signal located at the head and tail of the data signal, respectively. The first pilot component signal corresponds to a first pilot phase noise value, and the second pilot component signal corresponds to a second pilot phase noise value. The first estimation unit is used to: determine a first phase noise value of the forward filtered signal based on the first pilot phase noise value; and determine a second phase noise value of the backward filtered signal based on the second pilot phase noise value.

[0020] In one possible implementation of the second aspect, both the forward-filtered signal and the backward-filtered signal include M consecutive data component signals, where M is a positive integer. The first estimation unit is further configured to: for the M data component signals included in the forward-filtered signal, determine the phase noise value of the first data component signal among the M data component signals based on the first pilot phase noise value, and determine the phase noise value of the (i+1)th data component signal among the M data component signals based on the phase noise value of the i-th data component signal among the M data component signals, so as to obtain the first phase noise value, where the value of i ranges from 1 to M-1; for the M data component signals included in the backward-filtered signal, determine the phase noise value of the last data component signal among the M data component signals based on the second pilot phase noise value, and determine the phase noise value of the j-th data component signal among the M data component signals based on the (j+1)th data component signal among the M data component signals, so as to obtain the second phase noise value, where the value of i ranges from 1 to M-1.

[0021] In one possible implementation of the second aspect, the apparatus further includes a comparison unit and a correction unit; the comparison unit is used to compare the first compensation signal and the second compensation signal to determine the data position of unreliable data; the second filtering unit is further used to perform forward filtering on the data component signal located at the data position in the data signal to obtain a forward component filtered signal; the third filtering unit is further used to perform backward filtering on the data component signal located at the data position in the data signal to obtain a backward component filtered signal; the first estimation unit is further used to determine the first component phase noise value of the forward component filtered signal and the second component phase noise value of the backward component filtered signal respectively; the compensation unit is further used to compensate the data component signal according to the first component phase noise value and the second component phase noise value respectively to obtain the first data component signal and the second data component signal; the correction unit is used to correct the first compensation signal and the second compensation signal according to the first data component signal and the second data component signal.

[0022] In one possible implementation of the second aspect, the acquisition unit is further configured to: perform serial-to-parallel conversion on the received signal to obtain a data block; and separate the pilot signal and the data signal from the data block.

[0023] In one possible implementation of the second aspect, the second estimation unit is further configured to: determine the forward bit error check value of the first compensation signal and the backward bit error check value of the second compensation signal; and use the compensation signal corresponding to the smaller bit error check value between the forward bit error check value and the backward bit error check value as the demodulation signal of the received signal.

[0024] In one possible implementation of the second aspect, the first compensation signal and the second compensation signal are signals after symbol decision.

[0025] In one possible implementation of the second aspect, the filtering is a Kalman filter.

[0026] In one possible implementation of the second aspect, the filtering is either single-signal filtering or simultaneous multi-signal filtering.

[0027] A third aspect provides a transceiver including a processor and a memory coupled together, the memory including program instructions, the processor executing the phase noise estimation method provided by the first aspect or any possible implementation thereof.

[0028] Understandably, any of the devices provided above can be used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the structure of a receiving module provided in an embodiment of this application;

[0030] Figure 2 A flowchart of a phase noise estimation method provided in an embodiment of this application;

[0031] Figure 3 This is a schematic diagram of the structure of a data block provided in an embodiment of this application;

[0032] Figure 4 A schematic diagram of pilot signal filtering provided in an embodiment of this application;

[0033] Figure 5 A schematic diagram illustrating forward filtering and backward filtering provided in an embodiment of this application;

[0034] Figure 6 A schematic diagram illustrating how a serial number template is determined based on a comparison module, as provided in an embodiment of this application;

[0035] Figure 7 This is a schematic diagram illustrating forward and backward filtering of a data component signal, as provided in an embodiment of this application.

[0036] Figure 8 A schematic diagram illustrating forward and backward filtering of another data component signal provided in an embodiment of this application;

[0037] Figure 9 A schematic diagram illustrating a phase noise estimation method provided in an embodiment of this application;

[0038] Figure 10 A schematic diagram illustrating another phase noise estimation method provided in an embodiment of this application;

[0039] Figure 11 This is a schematic diagram of the structure of a phase noise estimation device provided in an embodiment of this application;

[0040] Figure 12 This is a schematic diagram of another phase noise estimation device provided in an embodiment of this application. Detailed Implementation

[0041] In this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, a and b, a and c, b and c, or a, b, and c, where a, b, and c can be single or multiple. Furthermore, embodiments of this application use terms such as "first" and "second" to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are merely to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the words “first” and “second” do not limit the quantity or the order of execution.

[0042] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0043] Terahertz active cable (TAC) equipment is a wired high-speed data communication device, typically installed between boards in data servers and / or between racks in data centers to achieve high-density, high-speed data signal transmission. TAC equipment mainly consists of a plastic cable and transceivers connected to both ends of the cable. The plastic cable is used to transmit modulated signals; the transceiver can include a small form-factor pluggable (SFP) module or a quad small form-factor pluggable (QSFP) module for bidirectional data signal transmission and reception. Specifically, taking an SFP transceiver comprising a transmitting module and a receiving module as an example, during one-way data signal transmission, the transmitting module receives the externally input data signal and modulates it onto a terahertz carrier wave to obtain a modulated signal. This modulated signal is transmitted through the plastic cable to the receiving module on the other side. The receiving module demodulates the received modulated signal to obtain the input data signal.

[0044] Due to the relatively high transmission loss of plastic cables, transceivers typically employ a coherent communication architecture to provide greater signal bandwidth and data transmission rate over longer transmission distances. Specifically, taking a transceiver including an SFP (Signal Processing Unit) comprising a transmitting module and a receiving module as an example, the transmitting module receives an externally input data signal S(t) and modulates it onto a local terahertz carrier LOt to obtain a modulated signal. This modulated signal is transmitted through the plastic cable to the receiving module on the other side. The receiving module then uses another local terahertz carrier LOr to mix the modulated signal, obtaining a demodulated data signal R(t). Because LOt and LOr have different stability characteristics, there is a time-varying phase difference φ(t) between them, and this phase difference exhibits a Wiener process with random walk characteristics, which satisfies formula (1):

[0045]

[0046] Where δ(t) is a random noise, φ(t) is the phase difference between LOt and LOR at time t, and φ(t-1) is the phase difference between LOt and LOR at time t-1.

[0047] During the demodulation process, the phase difference φ(t) between LOt and LOR is added to the phase of the data signal S(t) and transmitted to the demodulated data signal R(t), resulting in phase noise in the data signal R(t) received by the transceiver. The data signal R(t) satisfies formula (2):

[0048]

[0049] Where n(t) is the additive white noise in the transceiver, and i represents a complex number.

[0050] In high-speed communication scenarios, extremely low bit error rates (BERs) are required for data signals, typically less than 10 ppm. -6 In this case, the phase noise generated by the phase difference between LOt and LOr can lead to a severe bit error rate bottleneck. Therefore, in order to ensure the required bit error rate, it is necessary to estimate and track the change of phase difference φ(t) in the data signal S(t) and compensate for this phase difference in the data signal R(t).

[0051] The difficulty in phase noise estimation lies in the fact that the receiving module can only observe the data signal R(t) and cannot acquire the data signal S(t). Therefore, it can only estimate the phase noise by guessing the data signal S(t). If the data signal S(t) is misjudged, the phase noise estimation will be incorrect. Therefore, in a coherent communication architecture, the transmitting module intermittently inserts pilot signals P(t) into the data signal S(t) to assist the receiving module in estimating the correct phase noise at that time using the correct pilot signal P(t).

[0052] In existing technologies, Scheme 1 estimates the phase noise of the data signal R(t) using the pilot signal P(t) at both ends of the data signal R(t); Scheme 2 estimates the phase noise of the current moment using the phase noise of the previous moment, and continuously iterates to obtain the phase noise of the data signal R(t). However, the phase noise estimation in Schemes 1 and 2 has a large error, making it difficult to meet the requirement of low bit error rate.

[0053] Based on this, embodiments of this application provide a phase noise estimation method that improves the accuracy of data signal phase noise estimation while ensuring a low bit error rate. This phase noise estimation method can be applied to the receiving module in a transceiver. The transceiver can include, but is not limited to, small pluggable modules and four-channel small pluggable modules. The transceiver can be used in a TAC (Transceiver Acquisition Controller), such as the TAC described above.

[0054] Figure 1 This application provides a schematic diagram of the receiving module structure in a transceiver, as shown in the embodiment. Figure 1 As shown, the receiving module may include: a coupling structure 101, a radio frequency circuit 102, a processor 103, and an output port 104.

[0055] The coupling structure 101 is coupled between the plastic cable and the radio frequency circuit 102, and is used to receive the radio frequency signal transmitted in the plastic cable.

[0056] The radio frequency (RF) circuit 102 is mainly used to convert between high-frequency and low-frequency signals, and to process the high-frequency and low-frequency signals. The RF circuit 103 may include one or more filters, or other components associated with the receiving module's conversion and processing of the high-frequency and low-frequency signals. In this embodiment, the RF circuit 102 is used to convert high-frequency RF signals transmitted in a plastic cable into low-frequency baseband signals.

[0057] The processor 103 is the control center, executing various functions of the receiving module and processing data, thereby providing overall monitoring of the receiving module. Optionally, the processor 103 may include one or more processing units. For example, the processor 103 may include a central processing unit (CPU), an application processor (AP), a modem processor, an amplifier, a digital-to-analog converter (DAC), an analog-to-digital converter (ADC), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors. In this embodiment, the phase noise estimation method is mainly applied in the processor 103 to estimate the phase noise of the data signal.

[0058] Output port 104 provides an interface between processor 103 and peripheral interface modules, such as universal serial bus (USB) devices. For example, this output port can be connected to a USB device to send data signals to the USB device.

[0059] Figure 2 This application provides a phase noise estimation method, which is applied in the receiving module described above and specifically executed by the processor in the receiving module. Figure 2 As shown, the phase noise estimation method includes the following steps.

[0060] S201: Obtain pilot signals and data signals from the received signals.

[0061] In one possible embodiment, the received signal is received serially via the aforementioned coupling structure. The received signal is stored in a data buffer within the processor, which converts the received signal into parallel signals to obtain one or more data blocks. Each of these data blocks may include a data signal and a pilot signal. The data signal may include M consecutive data component signals. The pilot signal may include a first pilot component signal P located at the beginning of the data signal. f and the second pilot component signal P at the tail b It should be noted that M can be a positive integer greater than or equal to 1, and its specific value can be set according to actual needs or the experience of relevant technical personnel. This application embodiment does not impose specific restrictions on this.

[0062] The following example uses the data block including the first pilot component signal P. f The second pilot component signal P b The structure is illustrated using an example of a continuous signal with M data components. For instance, as shown... Figure 3 As shown, the data block includes the first pilot component signal P. f The second pilot component signal P b And M consecutive data component signals, which can be represented as R1 to R... M Among them, the first pilot component signal P f The second pilot component signal P is located at the beginning of the data signal and is adjacent to (or continuous with) the data component signal R1. b Located at the tail of the data signal and adjacent to the data component signal R M Adjacent (or consecutive).

[0063] Furthermore, the pilot signal and the data signal are separated from the data block. For example, the processor includes a signal type splitter. The data block is imported into the signal type splitter, which divides the data block according to different signal types, thereby separating the data signal and the pilot signal.

[0064] S202: Filter the pilot signal to obtain the pilot filtered signal, and compare the pilot filtered signal with the theoretical pilot signal to obtain the pilot phase noise value.

[0065] The pilot signal may include a first pilot component signal P located at the beginning of the data signal. f And the second pilot component signal P located at the tail of the data signal bPilot signal filtering can be performed by forward filtering or backward filtering. For a detailed description of forward and backward filtering, please refer to the relevant descriptions in S203, which will not be repeated here.

[0066] Furthermore, the theoretical pilot signal is the pilot signal included in the original signal corresponding to the received signal transmitted by the transmitting end (i.e., the original pilot signal). The transmitting end can be the transmitting module provided above. The theoretical pilot signal can be pre-configured for the transmitting module and the receiving module. The theoretical pilot signal will generate certain noise (for example, the noise can include random noise) during the transmission from the transmitting module to the receiving module, that is, the pilot signal obtained by the receiving module from the received signal contains noise.

[0067] In one possible embodiment, the pilot signal is filtered, i.e., noise in the pilot signal is reduced or filtered out (e.g., random noise is filtered out), to obtain a filtered pilot signal; the filtered pilot signal is compared with the theoretical pilot signal to obtain the pilot phase noise value, i.e., the phase noise value (also called phase noise value) corresponding to each pilot signal in the pilot signal is obtained. For example, as... Figure 4 As shown, the pilot signal includes a first pilot component signal P. f Second pilot component signal P b For the first pilot component signal P f Second pilot component signal P b Forward filtering is performed to obtain a first pilot filter signal and a second pilot filter signal. These signals are then compared with the first and second pilot component signals used by the transmitter when transmitting the received signal, respectively, to obtain the first pilot component signal P. f The corresponding first pilot phase noise value φ(P) f ) and the second pilot component signal P b The corresponding second pilot phase noise value φ(P) b ). Figure 4 The forward filtering method will be used as an example for explanation.

[0068] In one possible embodiment, the filtering can be Kalman filtering, that is, Kalman filtering is applied to the pilot signal.

[0069] When filtering the pilot signal, the pilot signal used by the transmitting end to send the received signal is known at the receiving end. Therefore, the phase noise value corresponding to each pilot component signal in the pilot signal can be directly calculated. Since the first pilot component signal P... f and the second pilot component signal P bThe interval is M times the interval between adjacent data component signals. Therefore, in the Wiener process corresponding to formula (1), the first pilot component signal P f and the second pilot component signal P b The power of random noise between them will also increase by a factor of M, at which point the power of the first pilot component signal P... f and the second pilot component signal P b The variance of the random noise during filtering is MG. Here, G is the variance of the random noise when filtering a single data component signal.

[0070] S203: Perform forward filtering and backward filtering on the data signal to obtain forward filtered signal and backward filtered signal, and determine the first phase noise value of the forward filtered signal and the second phase noise value of the backward filtered signal based on the pilot phase noise value.

[0071] The data signal may include multiple data component signals. Forward filtering of the data signal refers to filtering the data component signals sequentially from the first received data component signal to the last received data component signal, according to the receiving order. Forward filtering is relative to backward filtering, which refers to filtering the data signal sequentially from the last received data component signal to the last received data component signal. Forward filtering and backward filtering occur in opposite directions. In this embodiment, the only difference between forward filtering and backward filtering is the filtering direction; there are no other substantial differences.

[0072] Furthermore, the data signal is forward-filtered to obtain a forward-filtered signal, and the first phase noise value of the forward-filtered signal is determined based on the first pilot phase noise value. Specifically, as follows... Figure 5 As shown in (a), the data signal comprises M consecutive data component signals and can be represented as R1 to R2. M Among them, R1 and R M These are the first and last data component signals in the continuous M data component signals, respectively. Based on the first pilot phase noise value φ(P) f Determine the phase noise value φ of the first data component signal R1 among the M data component signals. f (1) Based on the phase noise value φ f (1) Determine the phase noise value φ of the second data component signal R2 among the M data component signals. f (2) Iterate sequentially, based on the i-th data component signal R among the M data component signals. i Phase noise value φ f (i) Determine the (i+1)th data component signal R among the M data component signals. i+1 Phase noise value φ f(i+1), based on the phase noise value φ f (i+1), determine the Mth data component signal R among the M data component signals. M Phase noise value φ f (M). This determines the phase noise value corresponding to each of the M data component signals, thus obtaining the forward phase noise value φ. f (t), the forward phase noise value φ f (t) can also be called the first phase noise value φ f (t), where M is a positive integer and the value of i ranges from 1 to M-1. Figure 5 (a) in the figure only shows a portion of the data component signal and the corresponding pilot phase noise value of the data component signal.

[0073] In one possible embodiment, the data signal is back-filtered to obtain a back-filtered signal, and the second phase noise value of the back-filtered signal is determined based on the second pilot phase noise value. Specifically, as shown... Figure 5 As shown in (b), the back-filtered signal comprises M consecutive data components and can be represented as R1 to R2. M According to the second pilot phase noise value φ(P) b Determine the last data component signal R among the M data component signals. M Phase noise value φ b (M), iterate sequentially, and based on the (j+1)th data component signal R among the M data component signals. j+1 The phase noise value φb(j+1) determines the j-th data component signal R in the M data component signals. j Phase noise value φ b (j), based on the j-th data component signal R among the M data component signals. j Phase noise value φ b (j) Determine the phase noise value φ of the second data component signal R2 among the M data component signals. b (2) Based on the phase noise value φ of the second data component signal R2 in the M data component signals. b (2) Determine the phase noise value φ of the first data component signal R1 among the M data component signals. b (1). Thus, the phase noise value corresponding to each of the M data component signals is determined, that is, the backward phase noise value φ is obtained. b (t), the backward phase noise value φ b (t) can also be called the second phase noise value φ b (t), where M is a positive integer and j ranges from 1 to M-1. Figure 5 (b) in the diagram only shows a portion of the data component signal and the corresponding pilot phase noise value.

[0074] In one possible embodiment, the filtering can be Kalman filtering, that is, performing Kalman forward filtering and Kalman backward filtering on the data signal respectively.

[0075] In another possible embodiment, the filtering can be single-signal filtering or simultaneous multi-signal filtering. Single-signal filtering refers to filtering on a unit of one data component signal; simultaneous multi-signal filtering refers to filtering at least two adjacent data component signals as a whole. For example, two adjacent data component signals can be filtered. In this case, the time interval between changes in phase noise is two data component signal periods. Therefore, the power of random noise will increase by a factor of 2. In the filtering calculation, if the variance of random noise is G when filtering on a unit of one data component signal, then the variance of random noise when filtering two adjacent data component signals as a whole is 2G.

[0076] The following explanation uses forward filtering as an example to illustrate the principle of first-phase noise estimation. When estimating the first-phase noise, the first-phase noise value φ... f (t) is the state variable, the transmitted data signal S(t) is the latent variable, and the received data signal R(t) is the observed variable. In this case, equation (1) is the state equation in the phase domain, and equation (2) is the observation equation in the complex domain. Transforming the observation equation of equation (2) to the phase domain yields equation (3):

[0077]

[0078] Where θ(t) is the phase observed through the received data signal R(t); ang{} represents the phase of the complex number. When the noise n(t) of the receiving module is superimposed on the transmitted data signal S(t), the generated noise ε(t) satisfies formula (4):

[0079]

[0080] Here, ε(t) represents the observation noise in the phase domain. In communication scenarios with low bit error rates, the phase noise of the received signal S(t) is much higher than the noise n(t) of the receiving module. In this case, when the variance of n(t) is σ... 2 At that time, according to the approximate relationship of trigonometric functions, the variance Q of ε(t) satisfies formula (5):

[0081]

[0082] Let G represent the variance of the random noise δ(t) in formula (1). Assume that the estimated phase noise value at time t-1 is φ(t-1), and the covariance that measures the confidence level of the phase noise value is C(t-1).

[0083] Since the transmitted data signal S(t) is unavailable, θ(t) and Q in formulas (3) and (4) cannot be accurately calculated. Therefore, the phase noise value φ'(t) at time t and the covariance C'(t) measuring the confidence level of the phase noise value at time t can only be predicted using the first pilot component signal. The data signal R(t) is compensated and decided using the phase noise value φ'(t) to obtain a predicted transmission signal S'(t). θ(t) and Q are then calculated using S'(t).

[0084] The transformed formulas (6) and (7) obtained from formulas (3) and (5) are shown below:

[0085]

[0086]

[0087] Calculate the phase noise value φ(t) at time t based on the obtained θ(t) and Q, and the covariance C(t) that measures the confidence level of the phase noise value at time t.

[0088] It should be noted that the process of backward filtering is the reverse of that of forward filtering, and formula (1) will be transformed into formula (8):

[0089]

[0090] The process remains a Wiener process, and the variance of the random noise δ(t) remains unchanged at G. Only the φ' required at time t changes. ( Both φ(t) and C'(t) are generated from the received signal at time t+1, while φ'(t) and C'(t) of the backward filtering are generated from the second pilot component signal. The process is similar to that of the forward filtering, and will not be described in detail here.

[0091] S204: Compensate the data signal according to the first phase noise value to obtain a first compensated signal; compensate the data signal according to the second phase noise value to obtain a second compensated signal.

[0092] In one possible embodiment, the first compensation signal and the second compensation signal can be signals after symbol decision. The first compensation signal can also be referred to as the first decision symbol, and the second compensation signal can also be referred to as the second decision symbol. Specifically, using the first phase noise value φ... f (t) Compensate the data signal to obtain a forward compensated signal, and perform a sign decision on the forward compensated signal to obtain a first decision symbol, i.e., obtain the first compensated signal D. f (t); using the second phase noise value φ b(t) Compensate the data signal to obtain a backward compensated signal, and perform a sign decision on the backward compensated signal to obtain a second decision symbol, that is, obtain the second compensated signal D. b (t). Here, sign decision is the process of approximating the integer part of the signal.

[0093] S205: Select one of the first compensation signal and the second compensation signal as the demodulation signal of the received signal.

[0094] Since the probability of both forward and backward filtering failing simultaneously is low, when the first compensation signal D... f (t) and the second compensation signal D b When different decision symbols appear in (t), there is a high probability that one of them is correct. Therefore, as long as the correct decision symbol is identified, the bit error rate of the data signal after phase noise compensation can be greatly reduced.

[0095] In one possible embodiment, since the data signal S(t) is generated after encoding with forward error correction (FEC), this embodiment uses FEC to process the first compensation signal D. f (t) and the second compensation signal D b (t) Perform FEC verification calculation. Specifically, the first compensation signal D f (t) and the second compensation signal D b (t) Perform FEC verification calculation to obtain the first compensation signal D. f (t) and the second compensation signal D b The forward error check value and the backward error check value in (t) are compared, and the compensation signal with the smaller error check value is selected as the demodulation signal of the received signal.

[0096] FEC (Fixed Error Correction) is a method to increase the reliability of data signal communication. Because FEC verification only requires binary bit-level logical operations without complex iterative decoding, its computational complexity is low and it is easy to implement. FEC verification can be performed in two ways.

[0097] In one possible embodiment, the first compensation signal D f (t) and the second compensation signal D b The two sets of codewords represented by (t) are fed into the FEC parity check matrix, and the number of error check bits corresponding to the two sets of codewords is calculated using the FEC parity check matrix, thus obtaining the first compensation signal D. f (t) and the second compensation signal D bThe forward error check value and the backward error check value in (t) are used as the demodulation signal of the received signal, and the compensation signal with the smaller forward error check value and the backward error check value are selected.

[0098] Optionally, the first compensation signal D f (t) and the second compensation signal D b Different decision symbols in (t) are cross-combined in different ways. FEC check is performed on the codewords represented by different symbol combinations. The symbol combination with the fewest error check values ​​is selected as the correct decision symbol. The compensation signal corresponding to the correct decision symbol is selected as the demodulation signal of the received signal.

[0099] Furthermore, in S203 above, since both forward and backward filtering of the data signal have the characteristic of continuous propagation, if the phase noise estimation of a data component signal at a certain position has a large deviation, this deviation will be passed on to the next data component signal through the filtering process, reducing the reliability of the filtered output of subsequent data component signals. Moreover, this deviation is difficult to accurately perceive by the decision error during symbol decision, and also difficult to accurately perceive by the confidence covariance parameter during filtering. Therefore, the method of simply using the decision error or using the covariance as a weight to weight and fuse the first and second phase noise values ​​has limited effect on improving the accuracy of phase noise estimation in the low bit error rate range.

[0100] Based on this, in the above-described S204, the embodiments of this application can also compare the first compensation signal D. f (t) and the second compensation signal D b (t), the first compensation signal D f (t) and the second compensation signal D b The inconsistent data component signals in (t) are subjected to forward and backward filtering again, thereby affecting the first compensation signal D. f (t) and the second compensation signal D b (t) is used for enhancement and improvement. A detailed explanation follows.

[0101] Furthermore, compare the first compensation signal D f (t) and the second compensation signal D b (t) is used to determine the data location of the unreliable data component signal. The unreliable data component signal may include the first compensation signal D. f (t) and the second compensation signal D bThe inconsistent data component signal in (t) may further include two or more potentially unreliable data component signals on either side of the inconsistent data component signal. For example, the potentially unreliable data component signal may include 2, 4 or 6 data component signals.

[0102] Specifically, the processor can compare the first compensation signal and the second compensation signal to identify the data positions of unreliable data component signals in the first and second compensation signals. For example, the processor may include a comparison module that sends the first and second compensation signals to the comparison module, which identifies the data positions of inconsistent data component signals in the first and second compensation signals. Since potential estimation errors can also affect subsequent data component signals, the comparison module can also identify the data positions of potentially unreliable data component signals adjacent to the data positions of the inconsistent data component signals, based on the filtering direction. After comprehensively considering the data positions of all unreliable data component signals, a sequence template is output, which can identify the data positions of all consistent data component signals as well as the data positions of unreliable data component signals.

[0103] For example, such as Figure 6 As shown, the first compensation signal D f (t) can include 12 data component signals and can be represented as D f (1) to D f (12) The second compensation signal D b (t) can include 12 data component signals and can be represented as D b (1) to D b (12), respectively D f (1) to D f (12) and D b (1) to D b (12) The data is fed into the comparison module, which identifies the data positions of all consistent data component signals and the data positions of unreliable data component signals (including inconsistent data component signals and potentially unreliable data component signals), and outputs the sequence number template M(t). In the sequence number template M(t), the data position of consistent data component signals is represented as 1, and the data position of unreliable data component signals is represented as 0. Wherein, D f (4) and D b (4) D f (9) and D b (9) is an inconsistent data component signal, D f (5) D f (10) D b (3) and Db (8) is a potentially unreliable data component signal. Figure 6 The following example illustrates the case where the potentially unreliable data component signal consists of two data component signals.

[0104] Furthermore, the first phase noise value φ can also be obtained through the sequence template M(t). f (t) and the second phase noise value φ b The phase noise values ​​corresponding to the data positions of the consistent data component signals in (t) are filtered out, and the first phase noise value φ is selected. f (t) and the second phase noise value φ b Data fusion is performed on the phase noise values ​​corresponding to the data positions of the consistent data component signals in M(t), thereby generating a single phase noise estimate φ(M) for each data component signal at the data position of the consistent data component signal identified by the sequence template M(t).

[0105] Data fusion can utilize several different data fusion methods. For example, method one can use the first phase noise value φ. f (t) and the second phase noise value φ b The covariance C corresponding to (t) f (t) and C b (t) is used as a weight for the first phase noise value φ f (t) and the second phase noise value φ b The phase noise value φ(M) is obtained by weighted averaging the phase noise values ​​of the data positions of the consistent data component signals in (t). Alternatively, the first compensation signal D can be used. f (t) and the second compensation signal D b The decision error corresponding to (t) is used as a weight for the first phase noise value φ. f (t) and the second phase noise value φ b The phase noise value φ(M) is obtained by weighted averaging the phase noise values ​​of the data positions of the consistent data component signals in (t). Alternatively, the first phase noise value φ can be directly calculated. f (t) and the second phase noise value φ b The phase noise value φ(M) is obtained by averaging the phase noise values ​​of the data positions of the consistent data component signals in (t).

[0106] Furthermore, the first compensation signal D can also be obtained through the sequence template M(t). f (t) and the second compensation signal D b The compensation signals corresponding to the data positions of the consistent data component signals in (t) are filtered out to obtain the first compensation signal D. f '(t) and the second compensation signal D b '(t).

[0107] In one possible embodiment, the sequence template M(t) is inverted to obtain another sequence template M'(t), which identifies the first compensation signal D. f (t) and the second compensation signal D b The data locations of all unreliable data component signals in S(t) are used to filter the data signal S(t) using the sequence template M'(t) to obtain the data component signal k(t). The data component signal k(t) can include one or more groups, and each group can include one or more consecutive data component signals.

[0108] Furthermore, the data component signal k(t) is subjected to forward filtering and backward filtering respectively to obtain forward component filtered signal and backward component filtered signal, and the first component phase noise value of the forward component filtered signal and the second component phase noise value of the backward component filtered signal are determined respectively.

[0109] Among them, for the phase noise value at the data position of the consistent data component signal, the phase noise value φ(M) after data fusion and the first phase noise value φ f (t) and the second phase noise value φ b Compared to the previous method, it has higher accuracy and can therefore provide more accurate phase noise values ​​for the data component signal k(t) in forward and backward filtering, reducing the probability of errors in forward or backward filtering estimation.

[0110] When performing forward and backward filtering on the data component signal k(t), the phase noise values ​​of the first component and the second component of the data component signal k(t) are determined based on the phase noise value φ(M). For example, as shown... Figure 7As shown, the example is given where the data component signal k(t) comprises two groups, each containing three consecutive data component signals. The data component signal k(t) includes a first group of data component signals k(t1) and a second group of data component signals k(t2). The first group of data component signals k(t1) and the second group of data component signals k(t2) are not adjacent. The first group of data component signals k(t1) may include data component signals k(3), k(4), and k(5), and the second group of data component signals k(t2) may include data component signals k(8), k(9), and k(10). Among these, k(4) and k(9) are inconsistent data component signals, and k(3), k(5), k(8), and k(10) are potentially unreliable data component signals. Forward filtering and backward filtering are performed on the first group of data component signals k(t1) and the second group of data component signals k(t2), respectively. Based on the phase noise values ​​φ(2) and φ(6) corresponding to the data positions of the adjacent data component signals of the first group of data component signals k(t1), the first component phase noise value φ of the first group of data component signals k(t1) is determined. f (t1) and the phase noise value of the second component φ b (t1), based on the phase noise values ​​φ(7) and φ(11) corresponding to the data positions of the adjacent data component signals of the second group of data component signals k(t2), the first component phase noise value φ of the second group of data component signals k(t2) is determined respectively. f (t2) and the phase noise value of the second component φ b (t2). Where M(t) is the sequence template and φ(M) is the phase noise value after data fusion.

[0111] Furthermore, the phase noise value φ of the first component of the first group of data component signals k(t1) is used respectively. f (t1) and the phase noise value of the second component φ b (t1) Compensate the first group of data component signals k(t1) to obtain the first data component signal D of the first group of data component signals k(t1). f (t1) and the second data component signal D b (t1); respectively using the phase noise value φ of the first component of the second set of data component signals k(t2). f (t2) and the phase noise value of the second component φ b (t2) Compensate the second set of data component signals k(t2) to obtain the first data component signal D of the second set of data component signals k(t2). f (t2) and the second data component signal D b (t2).

[0112] Furthermore, based on the first data component signal D of the first group of data component signals k(t1), respectively...f (t1) and the second data component signal D b (t1), and the first data component signal D of the second set of data component signals k(t2). f (t2) and the second data component signal D b (t2) Correct the first compensation signal D f '(t) and the second compensation signal D b '(t).

[0113] Specifically, let's take the first set of data component signal k(t1) as an example for explanation. Let's analyze the first data component signal D... f (t1) and the second data component signal D b (t1) and the first compensation signal D after being filtered by the sequence template M(t) f '(t) and the second compensation signal D b The first compensation signal D is obtained by merging the '(t) signals. f (t) and the second compensation signal D b (t), thus completing the first compensation signal D. f '(t) and the second compensation signal D b The correction of '(t). It should be noted that the first compensation signal D is performed using the second set of data component signals k(t2). f '(t) and the second compensation signal D b The correction process for '(t) is similar to the correction process for the first set of data component signals k(t1), and will not be described in detail here.

[0114] In one possible embodiment, only a portion of the unreliable data component signal in the data component signal k(t) disappears, and this unreliable data component signal is not adjacent to the remaining unreliable data component signals. For example... Figure 7 As shown, if the decision symbols output by data component signal k(4) after forward filtering and backward filtering are completely identical, then the unreliable data corresponding to the first group of data component signals k(t1) disappears; if the decision symbols output by data component signal k(9) after forward filtering and backward filtering are still different, then the unreliable data corresponding to the second group of data component signals k(t2) does not disappear. The first group of data component signals k(t1) and the second group of data component signals k(t2) are not adjacent. At this time, the first data component signal D... f (t1), the second data component signal D b (t1), the first data component signal D f (t2) and the second data component signal D b (t2) and the first compensation signal D f'(t) and the second compensation signal D b The first compensation signal D is obtained by merging the '(t) signals. f (t) and the second compensation signal D b (t). The first compensation signal D will be obtained. f (t) and the second compensation signal D b (t) The forward error check value and the backward error check value are obtained by FEC check calculation. The data component signal corresponding to the smaller error check value between the forward error check value and the backward error check value is taken as the correct transmission signal. That is, the remaining unreliable data is selected by FEC check calculation.

[0115] In another possible embodiment, only a portion of the unreliable data component signal in the data component signal k(t) disappears, and this unreliable data component signal is adjacent to the remaining unreliable data component signal. For example, as shown... Figure 8 As shown, the example is given where the data component signal k(t) comprises two groups, each containing three consecutive data component signals. The data component signal k(t) includes a first group of data component signals k(t1) and a second group of data component signals k(t2), with k(t1) and k(t2) being adjacent. The first group of data component signals k(t1) may include data component signals k(3), k(4), and k(5), and the second group of data component signals k(t2) may include data component signals k(6), k(7), and k(8). Among these, k(4) and k(7) are inconsistent data component signals, while k(3), k(5), k(6), and k(8) are potentially unreliable data component signals. Forward filtering and backward filtering are performed on the first group of data component signals k(t1) and the second group of data component signals k(t2) respectively. The phase noise values ​​corresponding to the data positions of the data component signals on both sides of the first group of data component signals k(t1) and the second group of data component signals k(t2) are phase noise values ​​φ(2) and φ(9) respectively. The first phase noise value of the first group of data component signals k(t1) and the second group of data component signals k(t2) is determined according to the phase noise value φ(2). The second phase noise value of the first group of data component signals k(t1) and the second group of data component signals k(t2) is determined according to the phase noise value φ(9). The decision symbols output by data component signal k(4) after forward filtering and backward filtering are exactly the same, but the decision symbols output by data component signal k(7) after forward filtering and backward filtering are still different. At this time, the unreliable data component signal corresponding to the first group of data component signals k(t1) disappears, but the first group of data component signals k(t1) is adjacent to the second group of data component signals k(t2). At this time, it can be as follows Figure 7Similar to the previous implementation, the remaining unreliable data is selected through FEC verification calculation, and the remaining unreliable data can also be subjected to forward filtering and backward filtering again. Here, M(t) is the sequence template, and φ(M) is the phase noise value after data fusion.

[0116] In the method provided in this application embodiment, the pilot signal is filtered to determine the pilot phase noise value, and the data signal is forward-filtered and backward-filtered. Based on the pilot phase noise value, the first phase noise value and the second phase noise value of the data signal are determined. In this process, the correlation between the phase noise values ​​on the time axis is fully utilized, which improves the accuracy of the phase noise value estimation. In addition, the independence of the forward filtering and backward filtering processes is maintained, the difference between the estimated trajectories of the first phase noise value and the second phase noise value is preserved, and the difference is used to perform symbol decision on the data signals after compensation for the first phase noise value and the second phase noise value, respectively. On this basis, the difference in the data signal is corrected by FEC check calculation, thereby improving the accuracy of phase noise estimation and further ensuring the requirement of low bit error rate of data signal.

[0117] For ease of understanding, the following will be used as an example. Figure 9 Taking the processor block diagram shown as an example, the technical solution provided in this application will be illustrated. Figure 9As shown, the processor includes: a signal buffer unit 301, a signal type segmentation unit 302, a first Kalman filter unit 303, a second Kalman filter unit 304, a third Kalman filter unit 305, a phase compensation unit 306, a symbol decision unit 307, and an FEC error correction unit 308. The signal buffer unit 301 performs serial-to-parallel conversion on the received signal to obtain a data block; the signal type segmentation unit 302 separates the pilot signal and the data signal from the data block; the first Kalman filter unit 303 performs Kalman filtering on the pilot signal to obtain a pilot filtered signal; and compares the pilot filtered signal with the theoretical pilot signal to obtain the pilot phase noise value. The pilot signal obtained from the received signal may include a first pilot component signal and a second pilot component signal located at the beginning and end of the data signal, respectively. The first pilot component signal corresponds to a first pilot phase noise value, and the second pilot component signal corresponds to a second pilot phase noise value. The second Kalman filter unit 304 is used to perform forward Kalman filtering on the data signal to obtain a forward filtered signal, and to determine the first phase noise value of the forward filtered signal based on the first pilot phase noise value; the third Kalman filter unit 305 is used to perform backward Kalman filtering on the data signal to obtain a backward filtered signal, and to determine the second phase noise value of the backward filtered signal based on the second pilot phase noise value; the phase compensation unit 306 is used to compensate the data signal based on the first phase noise value and the second phase noise value respectively; the symbol decision unit 307 is used to perform symbol decision on the data signal after compensation for the first phase noise value and the second phase noise value respectively to obtain a first compensated signal and a second compensated signal; the FEC bit error rate check unit 308 is used to perform bit error rate checks on the first compensated signal and the second compensated signal respectively to obtain a forward bit error rate check value and a backward bit error rate check value, and to use the compensation signal corresponding to the smaller bit error rate check value between the forward bit error rate check value and the backward bit error rate check value as the demodulated signal of the received signal.

[0118] The second Kalman filter unit 304, the third Kalman filter unit 305, the phase compensation unit 306, and the decision unit 307 can also be referred to as bidirectional phase noise estimation units.

[0119] In another possible embodiment, such as Figure 10The processor also includes a comparison unit 309, a data selection unit 310, a data fusion unit 311, and a data combining unit 312. The comparison unit 309 compares the first compensation signal and the second compensation signal to determine the data positions of unreliable data component signals and consistent data component signals, thereby outputting a sequence number template. The data selection unit 310 selects, according to the sequence number template, the phase noise value corresponding to the data position of the consistent data component signal in the first phase noise value and the phase noise value corresponding to the data position of the consistent data component signal in the second phase noise value. The data fusion unit 311 fuses the phase noise values ​​corresponding to the data positions of the consistent data component signals in the first and second phase noise values ​​according to the sequence number template. The data selection unit 310 is further configured to select consistent data component signals from the first compensation signal according to the sequence number template; the data selection unit 310 is further configured to select unreliable data component signals from the data signal according to the sequence number template; the bidirectional phase noise estimation unit performs forward filtering and backward filtering on the unreliable data component signals again, and obtains the first data component signal and the second data component signal respectively based on the fused phase noise value; the data merging unit 312 is configured to merge the first data component signal and the consistent data component signal respectively, and merge the second data component signal and the consistent data component signal respectively.

[0120] It is understood that, in order to achieve the above-mentioned functions, the receiving module includes the corresponding hardware structure and / or software module for performing each function. Those skilled in the art should readily recognize that, in conjunction with the phase noise estimation method steps of the various examples described in the embodiments herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0121] This application embodiment can divide the phase noise estimation device into functional modules according to the above method example. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0122] When dividing each function into modules according to its corresponding function. Figure 11A schematic diagram of a possible structure of the phase noise estimation device involved in the above embodiments is shown. The device includes: an acquisition unit 401, a first filtering estimation unit 402, a second filtering unit 403, a third filtering unit 404, a first estimation unit 405, a compensation unit 406, and a second estimation unit 407. The acquisition unit 401 can be one of the aforementioned... Figure 9 The signal buffer unit 301 and signal type segmentation unit 302 in the above-described method embodiment are used to support the device in executing S201; the first filter estimation unit 402 may be the above-described Figure 9 The first Kalman filter unit 303 is used to support the processor in executing S202 in the above method embodiment; the second filter unit 403 may be the above-described... Figure 9 The second Kalman filter unit 304 in the third filter unit 404 can be the one described above. Figure 9 The third Kalman filter unit 305 in the first estimation unit 405 can be the one described above. Figure 9 The second Kalman filter unit 304 and the third Kalman filter unit 305, the first filter estimation unit 402, the second filter unit 403 and the first estimation unit 405 are used to support the processor in executing S203 in the above method embodiment; the compensation unit 406 may be the above Figure 9 The phase compensation unit 306 and symbol decision unit 307 in the above-described method embodiment are used to support the processor in executing S204; the second estimation unit 407 may be the aforementioned Figure 9 The FEC error correction unit 308 in the above method embodiment is used to support the processor in executing S205.

[0123] Optionally, the phase noise estimation device further includes a comparison unit 408, which may be the aforementioned Figure 10 The comparison unit 309 is used to compare the first compensation signal and the second compensation signal to determine the data inconsistency location; the correction unit 409 can be the one described above. Figure 10 The data selection unit 310, data fusion unit 311, and data merging unit 312 are used to correct the first compensation signal and the second compensation signal based on the first data component signal and the second data component signal.

[0124] In terms of hardware implementation, the aforementioned confirmation unit 401, first filter estimation unit 402, second filter unit 403, third filter unit 404, first estimation unit 405, compensation unit 406, second estimation unit 407, comparison unit 408, and correction unit 409 can be processors.

[0125] Figure 12This is another possible structural schematic diagram of the phase noise estimation device involved in the above embodiments provided for the purposes of this application. The device includes a processor 501 and a memory 502, the memory 502 being used to store the device's code and data. In the embodiments of this application, the processor 501 is used to control and manage the operation of the device; for example, the processor 501 is used to support the device in executing S201 to S205 in the above method embodiments, and / or other processes used in the techniques described herein.

[0126] The processor 502 may include a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 502 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a digital signal processor and a microprocessor, etc.

[0127] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here. The various devices (such as apparatuses) provided in the embodiments of this application are used to perform the functions of the corresponding devices in the above embodiments, and therefore can achieve the same effect as the above control method.

[0128] In one aspect, embodiments of this application also provide a receiving module, which includes a processor, the processor comprising, as shown in the example below. Figure 9 The processor provided is described in the above-mentioned description, and will not be repeated here in the embodiments of this application.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0130] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0131] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause the device to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0132] Finally, it should be noted that the above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A phase noise estimation method, characterized in that, The method includes: The pilot signal and data signal are obtained from the received signal; The pilot signal is filtered to obtain the pilot filtered signal; The pilot filtered signal is compared with the theoretical pilot signal to obtain the pilot phase noise value; The data signal is subjected to forward filtering and backward filtering respectively to obtain forward filtered signal and backward filtered signal, and the first phase noise value of the forward filtered signal and the second phase noise value of the backward filtered signal are determined according to the pilot phase noise value. The data signal is compensated based on the first phase noise value to obtain a first compensated signal; The data signal is compensated based on the second phase noise value to obtain a second compensated signal; Choose one of the first compensation signal and the second compensation signal as the demodulation signal of the received signal.

2. The method according to claim 1, characterized in that, The theoretical pilot signal is the pilot signal included in the original signal corresponding to the received signal.

3. The method according to claim 1 or 2, characterized in that, The pilot signal obtained from the received signal includes a first pilot component signal and a second pilot component signal located at the head and tail of the data signal, respectively. The first pilot component signal corresponds to a first pilot phase noise value, and the second pilot component signal corresponds to a second pilot phase noise value. The step of determining the first phase noise value of the forward-filtered signal and the second phase noise value of the backward-filtered signal based on the pilot phase noise value includes: The first phase noise value of the forward filtered signal is determined based on the first pilot phase noise value; The second phase noise value of the backward filtered signal is determined based on the second pilot phase noise value.

4. The method according to claim 1 or 2, characterized in that, Both the forward-filtered signal and the backward-filtered signal include M consecutive data component signals, where M is a positive integer; For the M data component signals included in the forward-filtered signal, determining the first phase noise value of the forward-filtered signal based on the first pilot phase noise value includes: The phase noise value of the first data component signal among the M data component signals is determined based on the first pilot phase noise value, and the phase noise value of the (i+1)th data component signal among the M data component signals is determined based on the phase noise value of the i-th data component signal among the M data component signals, so as to obtain the first phase noise value, where the value of i ranges from 1 to M-1. For the M data component signals included in the backward filtered signal, determining the second phase noise value of the backward filtered signal based on the second pilot phase noise value includes: The phase noise value of the last data component signal in the M data component signals is determined based on the second pilot phase noise value, and the phase noise value of the j-th data component signal in the M data component signals is determined based on the phase noise value of the (j+1)-th data component signal in the M data component signals, so as to obtain the second phase noise value, where the value of j ranges from 1 to M-1.

5. The method according to claim 1 or 2, characterized in that, The method further includes: The first compensation signal and the second compensation signal are compared to determine the data location of the unreliable data component signal; The data component signals located at the data positions in the data signal are subjected to forward filtering and backward filtering respectively to obtain forward component filtered signals and backward component filtered signals; The phase noise values ​​of the first component of the forward component filtered signal and the second component of the backward component filtered signal are determined respectively. The data component signals are compensated based on the first component phase noise value and the second component phase noise value, respectively, to obtain the first data component signal and the second data component signal; The first compensation signal and the second compensation signal are corrected based on the first data component signal and the second data component signal.

6. The method according to claim 1 or 2, characterized in that, The step of obtaining pilot signals and data signals from the received signals includes: The received signal is converted from serial to parallel to obtain a data block; The pilot signal and the data signal are separated from the data block.

7. The method according to claim 1 or 2, characterized in that, Selecting one compensation signal from the first compensation signal and the second compensation signal as the demodulation signal of the received signal includes: Determine the forward error check value of the first compensation signal and the backward error check value of the second compensation signal; The compensation signal corresponding to the smaller of the forward error check value and the backward error check value is used as the demodulation signal of the received signal.

8. The method according to claim 1 or 2, characterized in that, The first compensation signal and the second compensation signal are signals after symbol decision.

9. The method according to claim 1 or 2, characterized in that, The filtering method is Kalman filtering.

10. The method according to claim 1 or 2, characterized in that, The filtering is either single-signal filtering or simultaneous filtering of multiple signals.

11. A phase noise estimation device, characterized in that, include: The acquisition unit is used to acquire pilot signals and data signals from the received signals; The first filtering estimation unit is used to filter the pilot signal to obtain a pilot filtered signal, and compare the pilot filtered signal with the theoretical pilot signal to obtain the pilot phase noise value; The second filtering unit is used to perform forward filtering on the data signal to obtain a forward filtered signal; The third filtering unit is used to perform backward filtering on the data signal to obtain a backward filtered signal; The first estimation unit is used to determine the first phase noise value of the forward filtered signal and the second phase noise value of the backward filtered signal based on the pilot phase noise value. The compensation unit is used to compensate the data signal according to the first phase noise value to obtain a first compensated signal, and to compensate the data signal according to the second phase noise value to obtain a second compensated signal; The second estimation unit is used to select one of the first compensation signal and the second compensation signal as the demodulation signal of the received signal.

12. The apparatus according to claim 11, characterized in that, The theoretical pilot signal is the pilot signal included in the original signal corresponding to the received signal.

13. The apparatus according to claim 11 or 12, characterized in that, The pilot signal obtained from the received signal includes a first pilot component signal and a second pilot component signal located at the beginning and end of the data signal, respectively. The first pilot component signal corresponds to a first pilot phase noise value, and the second pilot component signal corresponds to a second pilot phase noise value. The first estimation unit is used for: The first phase noise value of the forward filtered signal is determined based on the first pilot phase noise value; The second phase noise value of the backward filtered signal is determined based on the second pilot phase noise value.

14. The apparatus according to claim 11 or 12, characterized in that, Both the forward-filtered signal and the backward-filtered signal include M consecutive data component signals, where M is a positive integer. The first estimation unit is further configured to: For the M data component signals included in the forward filtered signal, the phase noise value of the first data component signal among the M data component signals is determined according to the first pilot phase noise value, and the phase noise value of the (i+1)th data component signal among the M data component signals is determined according to the phase noise value of the i-th data component signal among the M data component signals, so as to obtain the first phase noise value, where the value of i ranges from 1 to M-1; For the M data component signals included in the back-filtered signal, the phase noise value of the last data component signal in the M data component signals is determined according to the second pilot phase noise value, and the phase noise value of the j-th data component signal in the M data component signals is determined according to the phase noise value of the (j+1)-th data component signal in the M data component signals, so as to obtain the second phase noise value, where the value of i ranges from 1 to M-1.

15. The apparatus according to claim 11 or 12, characterized in that, The device also includes a comparison unit and a correction unit; The comparison unit is used to compare the first compensation signal and the second compensation signal to determine the data location of the unreliable data component signal. The second filtering unit is further configured to perform forward filtering on the data component signal located at the data position in the data signal to obtain a forward component filtered signal; The third filtering unit is further configured to perform backward filtering on the data component signal located at the data position in the data signal to obtain a backward component filtered signal; The first estimation unit is further configured to determine the first component phase noise value of the forward component filtered signal and the second component phase noise value of the backward component filtered signal, respectively. The compensation unit is further configured to compensate the data component signal according to the first component phase noise value and the second component phase noise value respectively, so as to obtain the first data component signal and the second data component signal. The correction unit is used to correct the first compensation signal and the second compensation signal based on the first data component signal and the second data component signal.

16. The apparatus according to claim 11 or 12, characterized in that, The acquisition unit is also used for: The received signal is converted from serial to parallel to obtain a data block; The pilot signal and the data signal are separated from the data block.

17. The apparatus according to claim 11 or 12, characterized in that, The second estimation unit is also used for: Determine the forward error check value of the first compensation signal and the backward error check value of the second compensation signal; The compensation signal corresponding to the smaller of the forward error check value and the backward error check value is used as the demodulation signal of the received signal.

18. The apparatus according to claim 11 or 12, characterized in that, The first compensation signal and the second compensation signal are signals after symbol decision.

19. The apparatus according to claim 11 or 12, characterized in that, The filtering method is Kalman filtering.

20. The apparatus according to claim 11 or 12, characterized in that, The filtering is either single-signal filtering or simultaneous filtering of multiple signals.

21. A transceiver, characterized in that, The transceiver includes a processor and a memory coupled together, the memory including program instructions, and the processor executing the method as described in any one of claims 1-10.

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