Baseband chip, receiver and signal detection method

Abstract

Provided are a baseband chip, a receiver, and a signal detection method. The baseband chip includes: a detection module for performing signal detection on a first signal, wherein the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, wherein the first signal is a MU-MIMO signal; and a decoding module for decoding the first soft decision signal based on the detection result of the signal detection. The embodiment of the present application uses linear soft bit detection and nonlinear soft bit detection simultaneously for the same MU-MIMO signal, thereby improving the detection performance of the MU-MIMO signal.

Description

Technical Field

[0001] The present application relates to the field of communications, and more specifically, to a baseband chip, a receiver, and a signal detection method. Background Art

[0002] Existing communication systems use MU-MIMO technology to improve their throughput. However, receivers currently have poor detection performance for MU-MIMO signals, resulting in poor decoding performance (e.g., high block error rate) of received signals, which degrades the performance of the communication system. Summary of the Invention

[0003] The present application provides a baseband chip, a receiver, and a signal detection method to improve the detection performance of MU-MIMO signals.

[0004] In a first aspect, a baseband chip is provided, including: a detection module for performing signal detection on a first signal, the signal detection including linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal, wherein the first signal is a MU-MIMO signal; and a decoding module for decoding the first soft decision signal according to a detection result of the signal detection.

[0005] Optionally, the detection module includes: a channel estimation module, used to perform channel estimation on the first signal to obtain channel matrix information; a demodulation module, used to perform signal detection on the first signal based on the channel matrix information, the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal.

[0006] Optionally, the channel matrix information includes a channel matrix corresponding to a target terminal device and / or a channel matrix corresponding to an interfering terminal device, wherein the target terminal device is a terminal device to which the baseband chip belongs.

[0007] Optionally, the detection module is specifically used to: perform linear soft bit detection on the first signal to obtain a second soft decision signal; perform nonlinear soft bit detection on the first signal to obtain the first soft decision signal, wherein the second soft decision signal is prior information of the nonlinear soft bit detection.

[0008] Optionally, the detection module is specifically used to: perform linear soft bit detection on the first signal to obtain a second soft decision signal; perform nonlinear soft bit detection on the first signal to obtain a third soft decision signal; and weight the second soft decision signal and the third soft decision signal to obtain the first soft decision signal.

[0009] Optionally, the detection module includes: a modulation mode detection module, used to determine the modulation mode corresponding to the interfering terminal device; and a demodulation module, used to perform linear soft bit detection and nonlinear soft bit detection on the first signal according to the modulation mode to obtain a first soft decision signal.

[0010] Optionally, the linear detection is MMSE detection; and / or the nonlinear detection is MAP detection.

[0011] In a second aspect, a receiver is provided, comprising a receiving antenna for receiving a first signal; and the baseband chip according to the first aspect, for performing baseband processing on the first signal.

[0012] According to a third aspect, a terminal device is provided, comprising the baseband chip described in the first aspect.

[0013] In a fourth aspect, a signal detection method is provided, the method comprising: performing signal detection on a first signal, the signal detection comprising linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal, wherein the first signal is a MU-MIMO signal; and decoding the first soft decision signal according to the detection result of the signal detection.

[0014] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing channel estimation on the first signal to obtain channel matrix information; and performing signal detection on the first signal according to the channel matrix information, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal.

[0015] Optionally, the channel matrix information includes a channel matrix corresponding to a target terminal device and / or a channel matrix corresponding to an interfering terminal device, wherein the target terminal device is a terminal device to which the baseband chip belongs.

[0016] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain the first soft decision signal, wherein the second soft decision signal is prior information of the nonlinear soft bit detection.

[0017] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain a third soft decision signal; and weighting the second soft decision signal and the third soft decision signal to obtain the first soft decision signal.

[0018] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: determining a modulation mode corresponding to the interfering terminal device; and performing linear soft bit detection and nonlinear soft bit detection on the first signal according to the modulation mode to obtain a first soft decision signal.

[0019] Optionally, the linear detection is MMSE detection; and / or the nonlinear detection is MAP detection.

[0020] In a fifth aspect, a terminal device is provided, comprising a memory and a processor, wherein the memory stores executable code, and the processor is configured to execute the executable code to implement the method described in the fourth aspect.

[0021] In a sixth aspect, a receiver is provided, comprising a memory and a processor, wherein the memory is used to store a program, and the processor is used to call the program in the memory to execute the method described in the fourth aspect.

[0022] In a seventh aspect, a device is provided, comprising a processor, configured to call a program from a memory to execute the method described in the fourth aspect.

[0023] In an eighth aspect, a chip is provided, comprising a processor for calling a program from a memory so that a device equipped with the chip executes the method described in the fourth aspect.

[0024] In a ninth aspect, a computer-readable storage medium is provided, on which a program is stored, wherein the program enables a computer to execute the method described in the fourth aspect.

[0025] In a tenth aspect, a computer program product is provided, comprising a program, wherein the program enables a computer to execute the method described in the fourth aspect.

[0026] In an eleventh aspect, a computer program is provided, which enables a computer to execute the method described in the fourth aspect.

[0027] Related technologies use only linear soft bit detection algorithms or nonlinear soft bit detection algorithms in the MU-MIMO signal detection process. In the embodiments of the present application, linear soft bit detection and nonlinear soft bit detection are used simultaneously for the same MU-MIMO signal to improve the detection performance of the MU-MIMO signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 Schematic diagram of the system architecture of a communication system applicable to an embodiment of the present application.

[0029] Figure 2 It is a structural diagram of a receiver in a wireless communication system.

[0030] Figure 3 This is a structural diagram of a receiver proposed in the related art.

[0031] Figure 4 This is a structural diagram of another receiver proposed in the related art.

[0032] Figure 5 This is a structural diagram of another receiver proposed in the related art.

[0033] Figure 6 This is a schematic diagram of the structure of a baseband chip provided in an embodiment of the present application.

[0034] Figure 7 This is a structural diagram of another baseband chip provided in an embodiment of the present application.

[0035] Figure 8 yes Figure 7 The simulation results of low bit rate and strong correlation corresponding to the embodiment.

[0036] Figure 9 yes Figure 7 Simulation results of low bit rate weak correlation corresponding to the embodiment.

[0037] Figure 10 yes Figure 7 The simulation results of high code rate and strong correlation corresponding to the embodiment.

[0038] Figure 11 This is a structural diagram of a receiver provided in an embodiment of the present application.

[0039] Figure 12 This is a structural diagram of another receiver provided in an embodiment of the present application.

[0040] Figure 13 It is a structural diagram of the signal detection device provided in an embodiment of the present application.

[0041] Figure 14This is a flowchart of the signal detection method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] The following will describe the technical solution in this application in conjunction with the accompanying drawings. Figures 1 to 4 Introduce the terms and communication processes involved in the embodiments of this application.

[0043] Communication System

[0044] This embodiment can be applied to Figure 1 The wireless communication system 100 is shown. The communication system 100 is a cellular communication system. The cellular communication system may be, for example, a long term evolution (LTE) system, a fifth generation (5G) system, or a new radio (NR) system.

[0045] The wireless communication system 100 may include a network device 110 and a terminal device 120. The network device 110 may be a device that communicates with the terminal device 120. The network device 110 may provide communication coverage for a specific geographical area and may communicate with the terminal device 120 located within the coverage area.

[0046] Figure 1 One network device 110 and two terminal devices 120 are shown as an example. Optionally, the wireless communication system 100 may include multiple network devices and each network device may include another number of terminal devices within its coverage area, which is not limited in this embodiment of the present application.

[0047] The terminal device in the embodiments of the present application may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station (MS), mobile terminal (MT), remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device. The terminal device in the embodiments of the present application may refer to a device that provides voice and / or data connectivity to a user and can be used to connect people, objects, and machines, such as a handheld device with wireless connection function, a vehicle-mounted device, etc. The terminal device in the embodiments of the present application can be a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile internet device (MID), a wearable device, a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc.

[0048] The network device in the embodiments of the present application may be a device for communicating with a terminal device. The network device may also be referred to as an access network device or a radio access network device. For example, the network device may be a base station. The network device in the embodiments of the present application may refer to a radio access network (RAN) node (or device) that connects the terminal device to a wireless network. The embodiments of the present application do not limit the specific technology and specific device form adopted by the network device.

[0049] MU-MIMO

[0050] MU-MIMO, also known as multi-user MIMO, improves overall system throughput by ensuring that target and interfering devices occupy the same time-frequency resources. The target device is also referred to as the target user or the original user, while the interfering device is also referred to as the interfering user.

[0051] Typically, the demodulation reference signal (DMRS) for the target terminal device and the interfering terminal device uses the same RS sequence. The data of the target terminal device and the interfering terminal device can be distinguished by using different codes. For example, orthogonal cover code (OCC) can be used to distinguish the data of different terminal devices.

[0052] The MU-MIMO system model is:

[0053] y=H U x U +H I x I +n

[0054] Among them, H U represents the channel model of the target terminal device, x U Indicates the signal of the target terminal device, H I represents the channel model of the interfering terminal device, x I = represents the signal of the interfering terminal device, and n represents noise. The system model exemplarily shows one interfering terminal device. In practice, there may be no interfering terminal device, or there may be multiple interfering terminal devices.

[0055] As can be seen, in a MU-MIMO system, the signal received by the target terminal device contains the target terminal device signal, the interfering terminal device signal, and the noise signal. The target terminal device needs to perform certain signal processing to extract the target terminal device signal from the received signal in order to obtain the required data.

[0056] Receivers in wireless communication systems

[0057] Figure 2 This is a schematic diagram of the structure of the receiver in the wireless communication system. Figure 2 Briefly describe the function of each module in the receiver.

[0058] The RF module 210 may be used to receive signals. The signals received by the RF module 210 are generally analog signals.

[0059] The analog-to-digital conversion module 220 may be configured to receive a signal from the RF module 210 and convert the received analog signal into a digital signal for subsequent processing.

[0060] The digital front-end module 230 may be configured to receive signals from the analog-to-digital conversion module 220 and process the received signals. For example, the received time-domain signals may be converted into frequency-domain signals. The frequency-domain signals may include reference signals for channel estimation.

[0061] The channel estimation module 240 may be configured to receive the signal y from the digital front-end module 230 and perform channel estimation based on the signal y. Specifically, the channel estimation module 240 may perform channel estimation based on a reference signal included in the signal y.

[0062] The demodulation module 250 may perform soft decision on the signal y according to the channel matrix H obtained by the channel estimation module 240 to obtain a soft decision signal.

[0063] The decoding module 260 may receive the soft decision signal obtained by the demodulation module 250 and decode the soft decision signal to obtain restored data, wherein the restored data may be in the form of a bit stream.

[0064] Figure 2 This is merely an example of a possible receiver implementation. The receiver may further include a receiving antenna and other modules. In practice, the receiver may add some modules or omit some of the above modules as needed.

[0065] In MU-MIMO systems, receiver signal detection is a core technology. The main process of signal detection is as follows: the demodulation module generates a decision based on the first signal and the channel estimation results. The decision result is then used by the decoding module for decoding.

[0066] The decision on the received signal can be made using either hard or soft decisions. Hard decisions are simple to implement, while soft decisions have high accuracy. For example, soft decisions can be made using the log likelihood ratio (LLR). Soft decisions can also be called soft bit detection. The result of soft decisions can also be called a soft decision signal, soft value, or soft bit.

[0067] At present, the MU-MIMO receivers proposed in related technologies can be roughly divided into three types. Figures 3 to 5 , briefly introduces the three types of receivers respectively. A receiver may refer to a terminal device, for example.

[0068] Figure 3 This is a structural diagram of a receiver proposed in the related art. Figure 3In the receiver shown, the demodulation module 250A can use linear detection or nonlinear detection. Linear detection can include, for example, minimum mean squared error (MMSE), zero forcing (ZF), and maximum ratio combining (MRC). Nonlinear detection can include, for example, maximum likelihood (ML) or maximum a posteriori estimation (MAP).

[0069] Figure 3 The signal demodulation model of the receiver shown is:

[0070] y=H U x U +I=H U x U +(H I x I +n)

[0071] From the above formula, we can see that Figure 3 The receiver shown treats both the data and noise of the interfering terminal device as interference (or noise) without distinguishing the data of the interfering terminal device. Figure 3 The receiver shown does not consider the interference caused by the interfering terminal device. Therefore, for the MU-MIMO scenario with interfering terminal devices, Figure 3 The detection performance of the receivers shown is generally poor.

[0072] In a MU-MIMO system, the target terminal device can obtain the pilot sequence of the interfering terminal device. Therefore, when there is an interfering terminal device, in order to improve detection performance, the target terminal device can perform joint detection on the target terminal device and the interfering terminal device based on the channel estimation result of the interfering terminal device.

[0073] Figure 4 This is a structural diagram of another receiver proposed in the related art. Figure 4 The demodulation module 250B of the illustrated receiver may include a linear detector 251B and a nonlinear detector 252B. Figure 4 In the detection device shown, linear detection 251B is used to suppress interference, and nonlinear detection 252B is used to obtain a soft decision signal.

[0074] Figure 4 The receiver shown in the figure can also be called a linear joint receiver. Figure 4The receiver shown is briefly introduced. When linear detection uses MMSE, Figure 4 The shown scheme can also be called joint MMSE.

[0075] like Figure 4 As shown, the demodulation module 250B first uses the MMSE algorithm to perform interference suppression on the input signal to filter out the signal of the interfering terminal device. Specifically, the channel estimation of the target terminal device and the interfering terminal device is used to obtain the MMSE weighting matrix:

[0076]

[0077] Among them, H I represents the channel estimate of the interfering terminal device, represents the conjugate transpose of the interfering terminal device channel estimate, σ 2 represents the noise power, and I represents the identity matrix.

[0078] Ideally, the output of MMSE should be the signal after filtering out interfering devices and noise. In other words, the output of MMSE should only contain the data of the target device and the channel estimation result of the target device.

[0079] The nonlinear detection 252B can make a decision on the interference suppressed signal to obtain a soft decision signal for decoding.

[0080] Figure 4 The receiver shown takes into account the signal from the interfering terminal device, so the performance is better. Figure 3 However, when there is a certain channel correlation between the channels of the interfering terminal device and the target terminal device, the linear method cannot effectively suppress the interference. Therefore, for the scenario where the channels are correlated, Figure 4 The receiver shown does not guarantee optimal detection performance.

[0081] Figure 5 This is a structural diagram of another receiver proposed in the related art. Figure 5 The demodulation module 250C of the illustrated receiver may include a mode detector 251C and a nonlinearity detector 252C. Figure 5 The receiver shown may also be referred to as a nonlinear joint receiver.

[0082] Figure 5 In the receiver shown, nonlinear detection not only considers the channel information of the interfering terminal device (such as the instantaneous channel information of the interfering terminal device), but also estimates the modulation mode of the interfering terminal device, and uses the estimated modulation mode of the interfering terminal device to perform joint detection on the data of the target terminal device.

[0083] The following uses MAP detection for nonlinear detection 252C as an example. Figure 5 The receiver shown in the figure is briefly introduced. Figure 5 The receiver shown may also be referred to as a joint MAP.

[0084] when Figure 5 When the nonlinear detection 252C of the receiver shown uses MAP detection, the LLR decision formula for the received symbol is as follows:

[0085]

[0086] Where H=[H U ,H I ], represents the channel matrix of the target terminal device and the interfering terminal device, The signals of the target terminal device and the interfering terminal device are represented by . Using the above formula, the soft decision result of the signal can be obtained.

[0087] Figure 5 The receiver shown takes into account both the instantaneous channel of the interfering terminal device and the modulation mode of the interfering terminal device. Therefore, the detection result should be better in theory.

[0088] It can be seen from the above introduction that a receiver in the prior art usually uses a linear detection algorithm or a nonlinear detection algorithm alone to obtain a soft decision result.

[0089] In fact, the demodulation module uses nonlinear detection, which should theoretically achieve optimal detection performance in all scenarios. For example, nonlinear detection should theoretically achieve the lowest block error rate (BLER) in all scenarios.

[0090] However, due to the complexity of nonlinear detection (such as MAP detection), theoretical nonlinear detection is difficult to achieve. Therefore, nonlinear detection in products is often simplified. This simplification makes it difficult to achieve the theoretically optimal performance in some scenarios (such as low signal-to-noise ratio (SNR)).

[0091] In order to improve the detection performance of MU-MIMO signals, the embodiments of the present application are introduced in detail below.

[0092] Figure 6 This is a schematic diagram of the structure of a baseband chip provided in an embodiment of the present application. Figure 6 As shown, the baseband chip 600 may include a detection module 610 and a decoding module 620 .

[0093] The detection module 610 may be configured to perform signal detection on the first signal to obtain a first soft decision signal of the first signal.

[0094] The first signal may, for example, be a MU-MIMO signal. The MU-MIMO signal may include a signal of a target terminal device and a signal of an interfering terminal device. The target terminal device may be a terminal device to which the baseband chip belongs. The first soft decision signal of the first signal may refer to a soft decision result obtained by the baseband chip performing a soft decision on the first signal. The soft decision result of the first signal may also be referred to as a soft bit or soft value of the first signal. The first soft decision signal may be used for subsequent decoding.

[0095] Signal detection of the first signal may be performed in various ways. For example, signal detection may include linear soft bit detection and nonlinear soft bit detection.

[0096] Linear soft bit detection may refer to detecting the first signal using a linear algorithm to obtain a second soft decision signal. The second soft decision signal may refer to a soft decision result obtained by the baseband chip performing a soft decision on the first signal. Linear detection methods may include at least one of the following detection methods: minimum mean squared error (MMSE), zero forcing (ZF), and maximum ratio combining (MRC).

[0097] Nonlinear soft bit detection may refer to detecting the first signal using a nonlinear algorithm to obtain a third soft decision signal. The third soft decision signal may refer to a soft decision result obtained by the baseband chip performing a soft decision on the first signal. Nonlinear soft bit detection may include at least one of the following detection algorithms: maximum likelihood detection (ML) or maximum a posteriori estimation (MAP).

[0098] It is understood that both the second soft decision result obtained by linear soft bit detection and the third soft decision result obtained by nonlinear soft bit detection can be used for subsequent decoding of the first signal. To improve detection performance, linear soft bit detection and nonlinear soft bit detection can be combined to obtain a final soft decision signal, namely, the first soft decision signal. Improving detection performance can increase the accuracy of the soft decision results for the first signal, that is, improve the accuracy of the first soft decision signal. This improved accuracy of the first soft decision signal will effectively improve subsequent decoding performance. For example, it can effectively improve the decoding accuracy and reduce the block error rate, thereby improving communication quality.

[0099] There are various ways to combine linear and nonlinear soft bit detection. In some embodiments, linear soft bit detection can be performed on a first signal to obtain a second soft decision signal. This second soft decision signal is then used as prior information for nonlinear soft bit detection, and nonlinear soft bit detection is performed on the first signal to obtain a first soft decision signal. Using the results of linear soft bit detection as prior information for nonlinear soft bit detection can compensate for performance losses in nonlinear soft bit detection due to implementation simplification. This effectively improves detection performance and enhances communication quality.

[0100] In other embodiments, linear soft bit detection can be performed on the first signal based on the channel matrix information to obtain a second soft decision signal. Furthermore, nonlinear soft bit detection can be performed on the first signal based on the channel matrix information to obtain a third soft decision signal. The first soft decision signal can then be obtained based on the second and third soft decision signals. For example, the second and third soft decision signals can be weighted to obtain the soft decision signal. Using the results of linear soft bit detection as prior information for nonlinear soft bit detection can compensate for performance losses incurred by implementation simplification in nonlinear soft bit detection. Consequently, detection performance can be effectively improved, thereby enhancing communication quality.

[0101] In some embodiments, the detection module 610 may include a channel estimation module (or EST module) and a demodulation module (or DEM module).

[0102] The channel estimation module can be used to perform channel estimation on the first signal to obtain channel matrix information. The channel matrix information can include the channel matrix corresponding to the target terminal device. In some embodiments, the channel matrix information can also include both the channel matrix corresponding to the target terminal device and the channel matrix corresponding to the interfering terminal device. The channel matrix information obtained by the channel estimation module includes both the channel matrices of the target terminal device and the interfering terminal device, which can improve detection performance.

[0103] The demodulation module can perform linear soft bit detection and nonlinear soft bit detection on the first signal according to the channel matrix information to obtain a first soft decision signal.

[0104] In other embodiments, the detection module 610 may include a demodulation mode detection module (or Mod module) and a demodulation module.

[0105] The demodulation mode detection module can be used to determine the modulation mode corresponding to the interfering terminal device. The modulation mode can refer to the modulation mode used by the signal of the interfering terminal device. For example, the modulation mode can refer to quadrature phase shift keying (QPSK) modulation, quadrature amplitude modulation (16QAM), etc.

[0106] The demodulation module may be configured to perform linear soft bit detection and nonlinear soft bit detection on the first signal according to the modulation mode to obtain a first soft decision signal.

[0107] In some embodiments, to further improve detection performance (e.g., reduce block error rate), the detection module 610 may include a channel estimation module, a demodulation mode detection module, and a demodulation module. The demodulation module may perform linear soft bit detection and nonlinear soft bit detection on the first signal based on the channel matrix information and the modulation mode to obtain a first soft decision signal.

[0108] The baseband chip 600 may further include a decoding module 620 (or DEC module). The decoding module 620 may decode the first soft decision signal according to the detection result of the signal detection.

[0109] The baseband chip provided in the embodiment of the present application uses linear soft bit detection and nonlinear soft bit detection for the same MU-MIMO signal. Compared with using only a linear soft bit detection algorithm or a nonlinear soft bit detection algorithm, the detection performance of the baseband chip for the MU-MIMO signal is effectively improved.

[0110] The following combination Figure 7 and one The baseband chip 700 provided in this application is introduced in the following specific embodiment. Figure 7 The baseband chip 700 shown includes a detection module 710 and a decoding module 720. The detection module 710 may include a channel estimation module 711 and a demodulation module 712. The demodulation module 712 may include a mode detection module 712A, an MMSE module 712B, and a MAP module 712C.

[0111] The channel estimation module 711 can perform channel estimation on the first signal y to obtain a channel matrix H. The channel matrix H may include the channel matrix H of the target terminal device. U , and the channel matrix H of the interfering terminal device I .

[0112] The MMSE module 712B calculates the channel matrix H of the target terminal device. U , and the channel matrix H of the interfering terminal deviceI , perform linear soft bit detection on the first signal y to obtain a second soft decision signal.

[0113] The goal of MMSE testing is to make The most accurate weighting matrix W. The specific formula of MMSE detection is as follows:

[0114]

[0115] Among them, the channel estimation result H=[H U ,H I ], weight matrix W = H H (HH H +σ 2 I) -1 ,σ 2 Represents the noise power.

[0116] The first signal y may include multiple layers of data streams, each of which may be represented in the form of a bit stream. The i-th layer of data stream of the first signal y may be represented by the following formula:

[0117]

[0118]

[0119] where u = ∑ j≠i (WH) ij x j +(Wn) i , (WH) ii Represents the element in the i-th row and i-th column of the WH matrix.

[0120] Linear soft bit detection can be performed on a bit-by-bit basis. For the k-th bit of the i-th layer data stream, the LLR is calculated as follows:

[0121]

[0122] Using the above formula, we can get the symbol b i,k The soft decision result Λ i,k .

[0123] Mode detection module 712A can detect the modulation mode of the interfering terminal device and input the detection result to MAP module 712C. Modulation mode detection can be implemented in various ways. For example, the modulation mode of the interfering terminal device can be detected within a specific time-frequency resource (e.g., a resource block (RB) in the frequency direction and a subframe or time slot in the time direction). Specific detection methods can use linear detection (e.g., MMSE detection) or nonlinear detection (e.g., MAP detection).

[0124] The MAP detection module 712C performs MAP detection on the first signal based on the channel matrix H obtained by the channel estimation module 711, the second soft decision signal obtained by the MMSE detection module 712B, and the modulation mode of the interfering terminal device obtained by the mode detection module 712A to obtain a first soft decision signal.

[0125] The LLR calculation formula for MAP detection is as follows:

[0126]

[0127] In the above formula, the acquisition of the first soft decision signal depends on the soft decision result of MMSE.

[0128] Specifically, the ∑ m,n≠i,k lnP(b m,n ) part,

[0129]

[0130] and is the second soft decision signal obtained by MMSE detection.

[0131] Figures 8 to 10 for Figure 7 The simulation results of the embodiment are shown. Figures 8 to 10 The basic simulation conditions are: two users (one target terminal device and one interfering terminal device), dual transmit and receive (2*2 antennas), multipath delay TDLA, and Doppler spread of 30KHz. Figures 8 to 10 In the figure, curve L101 represents Figure 3 The simulation results of the detection scheme shown, curve L102 represents Figure 4 The simulation results of the detection scheme shown in FIG. 1 are shown in FIG. 1 , where curve L103 represents Figure 5 The simulation results of the detection scheme shown in FIG. 1 are shown in FIG. 1 , where curve L104 represents Figure 7 The simulation results of the solution of the embodiment of the present application are shown.

[0132] Figure 8The corresponding simulation conditions are: the signal of the target terminal device and the signal of the interfering terminal device are both modulated using QPSK, the code rate is CR0.12, and the interference plus noise ratio (INR) is -2dB. Figure 8 In the corresponding simulation conditions, the signals of the target terminal device and the interference terminal device have a strong correlation.

[0133] like Figure 8 As shown in the above simulation conditions, the solution provided by the embodiment of the present application has the best detection performance and the lowest block error rate. Figure 5 The corresponding plan, Figure 4 The corresponding plans and Figure 3 Corresponding plan.

[0134] Figure 9 The corresponding simulation conditions are: the signal of the target terminal device is modulated using QPSK, the signal of the interfering terminal device is modulated using 16QAM, the code rate is CR0.12, and the INR is -2dB. Figure 9 In the corresponding simulation conditions, the signal correlation between the target terminal device and the interfering terminal device is weak, and the bit rate is low.

[0135] like Figure 9 As shown in the figure, under the above simulation conditions, the detection performance of the solution provided by the embodiment of the present application is still the best. Among the remaining three solutions, in the order of decreasing performance, they are: Figure 4 The corresponding plan, Figure 5 The corresponding plans and Figure 3 Corresponding plan.

[0136] Figure 10 The corresponding simulation conditions are: both the target terminal device and the interference terminal device use 16QAM modulation, the code rate is CR0.33, and the INR is 14dB. Figure 10 In the corresponding simulation conditions, the signal correlation between the target terminal device and the interference terminal device is strong, and the bit rate is high.

[0137] like Figure 10 As shown in the figure, under the above simulation conditions, the detection performance of the solution provided by the embodiment of the present application is still the best. Among the remaining three solutions, in the order of decreasing performance, they are: Figure 5 The corresponding plan, Figure 4 The corresponding plans and Figure 3 Corresponding plan.

[0138] The above simulation results show that the baseband chip provided by the embodiments of the present application can achieve relatively good detection performance in various scenarios. Therefore, the baseband chip provided by the embodiments of the present application can enable the receiver to operate stably in various scenarios, effectively preventing performance losses caused by inaccurate scene detection. In other words, the detection performance of the baseband chip provided by the embodiments of the present application is stable.

[0139] It should be understood that Figure 7 The corresponding embodiment is only a possible specific implementation method of the present application, which is used to make the solution of the present application clearer and does not limit the solution of the present application.

[0140] Figure 11 1 is a schematic diagram of the structure of a receiver provided in an embodiment of the present application. The receiver 1100 provided in an embodiment of the present application may refer to a terminal device.

[0141] like Figure 11 As shown, the receiver 1100 provided in an embodiment of the present application may include a receiving antenna 1110 and a baseband chip 1120. The receiving antenna 1110 may be used to receive a first signal. The baseband chip 1120 may be used to perform baseband processing on the first signal. Baseband processing may include, for example, signal detection and decoding as described above. Other signal processing modules (not shown in the figure) may also be provided between the baseband chip 1120 and the receiving antenna 1110, such as the RF module and analog-to-digital conversion module mentioned above.

[0142] Figure 12 This is a structural diagram of another receiver provided in an embodiment of the present application. Figure 12 As shown, the receiver 1200 may include a radio frequency module 1210, an analog-to-digital conversion module 1220, a digital front-end module 1230, a detection module 1240, and a decoding module 1250. The detection module 1240 may include a channel estimation module 1241 and a demodulation module 1242. The demodulation module 1242 may include a mode detection module 1242A, an MMSE module 1242B, and a MAP module 1242C.

[0143] The RF module 1210 sends the received RF signal to the analog-to-digital conversion module 1220 . The analog-to-digital conversion module 1220 performs analog-to-digital conversion on the RF signal and sends the converted digital signal to the digital front-end module 1230 .

[0144] The digital front-end module 1230 sends the processed signal y to the channel estimation module 1241, the mode detection module 1242A, the MMSE module 1242B, and the MAP module 1242C. The signal y may be the first signal described above.

[0145] The channel estimation module 1241 generates a channel matrix H according to the signal y. The channel matrix H may include a channel matrix corresponding to the target terminal device and a channel matrix corresponding to the interfering terminal device.

[0146] The channel estimation module 1241 sends the channel matrix H to the pattern detection module 1242A, the MMSE module 1242B, and the MAP module 1242C.

[0147] The mode detection module 1242A determines the modulation mode corresponding to the interfering terminal device according to the signal y and the channel matrix H, and sends it to the MAP module 1242C.

[0148] The MMSE module 1242B performs soft decision on the signal y according to the channel matrix H to obtain a second soft decision signal Λ, and sends the second soft decision signal Λ to the MAP module 1242C.

[0149] The MAP module 1242C performs a soft decision on the signal y according to the channel matrix H, the modulation mode corresponding to the interfering terminal device, and the second soft decision signal Λ to obtain a first soft decision signal, and sends the first soft decision signal to the decoding module 1250. The decoding module 1250 decodes the first soft decision signal.

[0150] Figure 13 It is a structural diagram of a signal detection device according to an embodiment of the present application. Figure 13 The dotted line in the figure indicates that the unit or module is optional. The apparatus 1300 can be used to implement the method described in the method embodiment of the present application. The apparatus 1300 can be a chip, a terminal device, or a network device.

[0151] The device 1300 may include one or more processors 1310. The processor 1310 may support the device 1300 to implement the method described in the method embodiment below. The processor 1310 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0152] The apparatus 1300 may further include one or more memories 1320. The memories 1320 store programs that can be executed by the processor 1310, causing the processor 1310 to perform the methods described in the above method embodiments. The memories 1320 may be independent of the processor 1310 or integrated into the processor 1310.

[0153] The apparatus 1300 may further include a transceiver 1330. The processor 1310 may communicate with other devices or chips via the transceiver 1330. For example, the processor 1310 may transmit and receive data with other devices or chips via the transceiver 1330.

[0154] The present application also provides a computer-readable storage medium for storing a program. The computer-readable storage medium can be applied to a terminal or network device provided in the present application, and the program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0155] The present application also provides a computer program product. The computer program product includes a program. The computer program product can be applied to a terminal or network device provided in the present application, and the program causes a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0156] The embodiments of the present application also provide a computer program. The computer program can be applied to the terminal or network device provided in the embodiments of the present application, and the computer program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0157] Combined with the previous article Figures 6 to 13 , describes in detail the device embodiment of this application. Figure 14 , the method embodiment of the present application is described in detail. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment. Therefore, for parts not described in detail, reference can be made to the previous device embodiment.

[0158] Figure 14 This is a flowchart of the signal detection method provided in an embodiment of the present application. Figure 14 The method shown may include step S1410 and step S1420.

[0159] In step S1410, signal detection is performed on the first signal, where the signal detection includes linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal.

[0160] In step S1420, the first soft decision signal is decoded according to the detection result of the signal detection.

[0161] Optionally,

[0162] The signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing channel estimation on the first signal to obtain channel matrix information; and performing signal detection on the first signal according to the channel matrix information, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal.

[0163] Optionally, the channel matrix information includes a channel matrix corresponding to a target terminal device and / or a channel matrix corresponding to an interfering terminal device, wherein the target terminal device is a terminal device to which the baseband chip belongs.

[0164] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain the first soft decision signal, wherein the second soft decision signal is prior information of the nonlinear soft bit detection.

[0165] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain a third soft decision signal; and weighting the second soft decision signal and the third soft decision signal to obtain the first soft decision signal.

[0166] Optionally, the signal detection is performed on the first signal, and the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, including: determining a modulation mode corresponding to the interfering terminal device; and performing linear soft bit detection and nonlinear soft bit detection on the first signal according to the modulation mode to obtain a first soft decision signal.

[0167] Optionally, the linear detection is MMSE detection; and / or the nonlinear detection is MAP detection.

[0168] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0169] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any other combination. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode to another website, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0170] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments of the present application can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0171] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0173] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0174] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A baseband chip, characterized in that: include: a detection module, configured to simultaneously perform signal detection on a first signal using linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal, wherein the first signal is a MU-MIMO signal; A decoding module is used to decode the first soft decision signal according to the detection result of the signal detection.

2. The baseband chip according to claim 1, wherein: The detection module includes: a channel estimation module, configured to perform channel estimation on the first signal to obtain channel matrix information; The demodulation module is used to perform signal detection on the first signal according to the channel matrix information, where the signal detection includes linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal.

3. The baseband chip according to claim 2, wherein: The channel matrix information includes a channel matrix corresponding to a target terminal device and / or a channel matrix corresponding to an interfering terminal device, wherein the target terminal device is a terminal device to which the baseband chip belongs.

4. The baseband chip according to claim 1, wherein: The detection module is specifically used for: Performing linear soft bit detection on the first signal to obtain a second soft decision signal; Nonlinear soft bit detection is performed on the first signal to obtain the first soft decision signal, wherein the second soft decision signal is prior information of the nonlinear soft bit detection.

5. The baseband chip according to claim 1, wherein: The detection module is specifically used for: Performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain a third soft decision signal; The second soft decision signal and the third soft decision signal are weighted to obtain the first soft decision signal.

6. The baseband chip according to claim 1, characterized in that: The detection module includes: Modulation mode detection module, used to determine the modulation mode corresponding to the interfering terminal device; The demodulation module is used to perform linear soft bit detection and nonlinear soft bit detection on the first signal according to the modulation mode to obtain a first soft decision signal.

7. The baseband chip according to claim 1, wherein: The linear soft bit detection is MMSE detection; and / or The nonlinear soft bit detection is MAP detection.

8. A receiver, characterized in that: include: a receiving antenna, configured to receive a first signal; as well as The baseband chip according to any one of claims 1 to 7, configured to perform baseband processing on the first signal.

9. A signal detection method, characterized in that: The method comprises: Performing signal detection on the first signal using linear soft bit detection and nonlinear soft bit detection simultaneously to obtain a first soft decision signal of the first signal, wherein the first signal is a MU-MIMO signal; The first soft decision signal is decoded according to a detection result of the signal detection.

10. The method according to claim 9, characterized in that The simultaneously performing signal detection on the first signal using linear soft bit detection and nonlinear soft bit detection to obtain a first soft decision signal of the first signal includes: performing channel estimation on the first signal to obtain channel matrix information; Signal detection is performed on the first signal according to the channel matrix information, where the signal detection includes linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal.

11. The method according to claim 10, characterized in that: The channel matrix information includes a channel matrix corresponding to a target terminal device and / or a channel matrix corresponding to an interfering terminal device, wherein the target terminal device is a terminal device to which a baseband chip belongs.

12. The method according to claim 9, characterized in that The performing signal detection on the first signal, wherein the signal detection includes linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal, includes: Performing linear soft bit detection on the first signal to obtain a second soft decision signal; Nonlinear soft bit detection is performed on the first signal to obtain the first soft decision signal, wherein the second soft decision signal is prior information of the nonlinear soft bit detection.

13. The method according to claim 9, characterized in that The performing signal detection on the first signal, wherein the signal detection includes linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal, includes: Performing linear soft bit detection on the first signal to obtain a second soft decision signal; performing nonlinear soft bit detection on the first signal to obtain a third soft decision signal; The second soft decision signal and the third soft decision signal are weighted to obtain the first soft decision signal.

14. The method according to claim 9, characterized in that The performing signal detection on the first signal, wherein the signal detection includes linear soft bit detection and nonlinear soft bit detection, to obtain a first soft decision signal of the first signal, includes: Determine the modulation mode corresponding to the interfering terminal device; According to the modulation mode, linear soft bit detection and nonlinear soft bit detection are performed on the first signal to obtain a first soft decision signal.

15. The method according to claim 9, wherein: The linear soft bit detection is MMSE detection; and / or The nonlinear soft bit detection is MAP detection.

16. A receiver, characterized in that: The system comprises a memory and a processor, wherein the memory is used to store a program, and the processor is used to call the program in the memory to execute the method according to any one of claims 9 to 15.

Images