Detection method, chip and terminal device

Abstract

The application relates to a detection method, a chip and a terminal device. The method comprises the following steps: determining a channel matrix corresponding to a subcarrier in a plurality of subcarriers; the plurality of subcarriers are subcarriers corresponding to an OFDM symbol; obtaining first signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier; determining a target detection algorithm corresponding to the subcarrier based on a relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and a first preset threshold. The target detection algorithm is a first detection algorithm or a second detection algorithm, and the complexity of the first detection algorithm is greater than that of the second detection algorithm.

Description

Technical Field

[0001] This application relates to the field of communications, and more specifically, to a detection method, a chip, and a terminal device. Background Technology

[0002] Multiple-input multiple-output (MIMO) technology uses multiple antennas to transmit signals and is widely used in various communication systems. Spatial division multiplexing (SDM) is a transmission mode in MIMO systems that increases data transmission rate. It significantly increases data throughput without increasing system bandwidth. The minimum mean squared error (MMSE) algorithm and maximum likelihood detection with QR decomposition (QRM-MLD) are two basic detection methods in SDM systems. MMSE has lower complexity but relatively poor performance, while QRM-MLD is the optimal detection algorithm, but its complexity increases exponentially. Therefore, how to adaptively select these two detection algorithms is a problem that urgently needs to be solved. Summary of the Invention

[0003] This application provides a detection method, a chip, and a terminal device that can reduce the power consumption of the chip.

[0004] This application provides a detection method, including:

[0005] Determine the channel matrix corresponding to the subcarriers among a plurality of subcarriers; wherein, the plurality of subcarriers are the subcarriers corresponding to OFDM symbols;

[0006] Based on the channel matrix corresponding to the subcarrier, the first signal-to-noise ratio related information corresponding to the subcarrier is obtained;

[0007] The target detection algorithm corresponding to the subcarrier is determined based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and the first preset threshold.

[0008] The target detection algorithm is either a first detection algorithm or a second detection algorithm, wherein the complexity of the first detection algorithm is greater than that of the second detection algorithm.

[0009] This application provides a chip, including:

[0010] A matrix processing unit is used to determine the channel matrix corresponding to a subcarrier among multiple subcarriers; wherein the multiple subcarriers are subcarriers corresponding to OFDM symbols;

[0011] The algorithm processing unit is used to obtain the first signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier; and to determine the target detection algorithm corresponding to the subcarrier based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and a first preset threshold.

[0012] The target detection algorithm is either a first detection algorithm or a second detection algorithm, wherein the complexity of the first detection algorithm is greater than that of the second detection algorithm.

[0013] This application provides a chip for implementing the above-described detection method.

[0014] Specifically, the chip includes a processor and memory, wherein,

[0015] The memory is used to store computer programs;

[0016] The processor is configured to call and run the computer program from the memory to perform the detection method described above.

[0017] This application provides a terminal device, including a housing and a chip disposed inside the housing; wherein the chip is the chip described above.

[0018] This application provides a computer-readable storage medium for storing a computer program, which executes the detection method described above when the computer program is run by a device.

[0019] This application provides a computer program product, including computer program instructions that cause a computer to execute the detection method described above.

[0020] This application provides a computer program that, when run on a computer, causes the computer to perform the detection method described above.

[0021] The embodiments of this application can obtain a target detection algorithm for subcarriers corresponding to OFDM symbols, thus effectively reducing the overall processing complexity and chip power consumption. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of this application.

[0023] Figure 2 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 1 .

[0024] Figure 3 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 2.

[0025] Figure 4 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 3 .

[0026] Figure 5 This is a schematic block diagram of a terminal device according to an embodiment of this application. Figure 1 .

[0027] Figure 6 This is a schematic block diagram of a terminal device according to an embodiment of this application. Figure 2 .

[0028] Figure 7 This is a schematic block diagram of a communication device according to an embodiment of this application.

[0029] Figure 8 This is a schematic block diagram of a chip according to an embodiment of this application. Detailed Implementation

[0030] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0031] The technical solutions of this application embodiment can be applied to various communication systems, such as: Global System of Mobile communication (GSM) system, Code Division Multiple Access (CDMA) system, Wideband Code Division Multiple Access (WCDMA) system, General Packet Radio Service (GPRS), Long Term Evolution (LTE) system, Advanced Long Term Evolution (LTE-A) system, New Radio (NR) system, evolution of NR system, LTE-based access to unlicensed spectrum (LTE-U) system, NR-based access to unlicensed spectrum (NR-U) system, Non-Terrestrial Networks (NTN) system, Universal Mobile Telecommunication System (UMTS), Wireless Local Area Networks (WLAN), and Wireless Fidelity (WF). Fidelity (WiFi), 5th-Generation (5G) communication systems, or other communication systems.

[0032] Traditional communication systems typically support a limited number of connections and are easy to implement. However, with the development of communication technology, mobile communication systems will not only support traditional communication but also, for example, device-to-device (D2D) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), vehicle-to-vehicle (V2V) communication, or vehicle-to-everything (V2X) communication. The embodiments of this application can also be applied to these communication systems.

[0033] In one implementation, the communication system in this application embodiment can be applied to a carrier aggregation (CA) scenario, a dual connectivity (DC) scenario, or a standalone (SA) network deployment scenario.

[0034] In one embodiment, the communication system in this application can be applied to unlicensed spectrum, wherein the unlicensed spectrum can also be considered as shared spectrum; or, the communication system in this application can also be applied to licensed spectrum, wherein the licensed spectrum can also be considered as non-shared spectrum.

[0035] This application describes various embodiments in conjunction with network devices and terminal devices. The terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device, etc.

[0036] Terminal devices can be stations (STAION, ST) in WLANs, cellular phones, cordless phones, Session Initiation Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistant (PDA) devices, handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, in-vehicle devices, wearable devices, terminal devices in next-generation communication systems such as NR networks, or terminal devices in future evolved Public Land Mobile Network (PLMN) networks, etc.

[0037] In the embodiments of this application, the terminal device can be deployed on land, including indoor or outdoor, handheld, wearable or vehicle-mounted; it can also be deployed on water (such as ships); and it can also be deployed in the air (such as airplanes, balloons and satellites).

[0038] In the embodiments of this application, the terminal device may be a mobile phone, a tablet computer, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical care, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, or a wireless terminal device in a smart home, etc.

[0039] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0040] In the embodiments of this application, the network device can be a device for communicating with mobile devices. The network device can be an access point (AP) in WLAN, a base station (BTS) in GSM or CDMA, a base station (NodeB, NB) in WCDMA, an evolved base station (eNB or eNodeB) in LTE, a relay station or access point, or a vehicle-mounted device, wearable device, or a network device (gNB) in an NR network, or a network device in a future evolved PLMN network or an NTN network, etc.

[0041] By way of example and not limitation, in this embodiment, the network device may have mobility characteristics; for example, the network device may be a mobile device. Optionally, the network device may be a satellite or a balloon station. For example, the satellite may be a low Earth orbit (LEO) satellite, a medium Earth orbit (MEO) satellite, a geostationary earth orbit (GEO) satellite, a high elliptical orbit (HEO) satellite, etc. Optionally, the network device may also be a base station located on land, water, or other similar locations.

[0042] In this embodiment, the network device can provide services to a cell. The terminal device communicates with the network device through the transmission resources (e.g., frequency domain resources, or spectrum resources) used by the cell. The cell can be the cell corresponding to the network device (e.g., a base station). The cell can belong to a macro base station or to a base station corresponding to a small cell. The small cell can include: metro cell, micro cell, pico cell, femto cell, etc. These small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-speed data transmission services.

[0043] Figure 1 An exemplary communication system 100 is shown. The communication system includes a network device 110 and two terminal devices 120. In one embodiment, the communication system 100 may include multiple network devices 110, and the coverage area of ​​each network device 110 may include other numbers of terminal devices 120, which is not limited in this application embodiment.

[0044] In one embodiment, the communication system 100 may also include other network entities such as a Mobility Management Entity (MME) and an Access and Mobility Management Function (AMF), which are not limited in this application embodiment.

[0045] Network equipment can be further divided into access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks used to communicate with the access network equipment. Access network equipment can be evolved Node Bs (eNBs or e-NodeBs) in Long-Term Evolution (LTE), Next-Generation Radio (NR) (mobile communication system), or Authorized Auxiliary Access Long-Term Evolution (LAA-LTE) systems, such as macro base stations, micro base stations (also called "small base stations"), pico base stations, access points (APs), transmission points (TPs), or new generation Node Bs (gNodeBs).

[0046] It should be understood that devices with communication functions in the network / system of this application embodiment can be referred to as communication devices. Figure 1 Taking the communication system shown as an example, the communication equipment may include network devices and terminal devices with communication functions. The network devices and terminal devices may be specific devices in the embodiments of this application, which will not be described in detail here. The communication equipment may also include other devices in the communication system, such as network controllers, mobility management entities and other network entities, which are not limited in the embodiments of this application.

[0047] It should be understood that the terms "system" and "network" are often used interchangeably in this document. The term "and / or" in this document merely 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. Furthermore, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0048] It should be understood that the term "instruction" mentioned in the embodiments of this application can be a direct instruction, an indirect instruction, or an indication of a relationship. For example, A instructing B can mean that A directly instructs B, such as B being able to obtain information through A; it can also mean that A indirectly instructs B, such as A instructing C, so B can obtain information through C; or it can mean that there is a relationship between A and B.

[0049] In the description of the embodiments of this application, the term "correspondence" may indicate that there is a direct or indirect correspondence between two things, or that there is an association between two things, or that there is a relationship of instruction and being instructed, configuration and being configured, etc.

[0050] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies of the embodiments of this application are described below. The following relevant technologies are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and they all fall within the protection scope of the embodiments of this application.

[0051] Multiple-input multiple-output (MIMO) technology uses multiple antennas to transmit signals and is widely used in various communication systems such as LTE, 5G, and Wi-Fi. Spatial division multiplexing is a transmission mode in MIMO systems that increases data transmission rate. It significantly increases data throughput without increasing system bandwidth. The minimum mean squared error (MMSE) algorithm and maximum likelihood detection with QR decomposition (QRM-MLD) are two basic detection methods in spatial division multiplexing systems. The MMSE algorithm has lower complexity but relatively poor performance, while QRM-MLD is the optimal detection algorithm, but its complexity increases exponentially. Although spherical decoders or M-path algorithms have been used to simplify the number of constellation points searched in the QRM-MLD algorithm, its complexity is still significantly higher than that of the MMSE algorithm.

[0052] Therefore, it is necessary to adaptively select either the QRM-MLD algorithm or the MMSE algorithm to reduce the chip's power consumption.

[0053] In related schemes, adaptive calculation methods typically calculate the rank of the channel matrix. For example, the rank of the channel matrix can be obtained by dividing the power on the main diagonal of the channel autocorrelation matrix by the sum of the power of the elements off the main diagonal. The specific calculation formula is as follows:

[0054] ;

[0055] ;

[0056] ;

[0057] here, Represents the transmitted signal vector; Represents the received signal vector; Represents the channel matrix; This represents complex Gaussian white noise; Let represent the channel autocorrelation matrix, where Represents the channel autocorrelation matrix The main diagonal element, Represents the channel autocorrelation matrix Non-main diagonal elements, This represents singular values.

[0058] Furthermore, based on the channel autocorrelation matrix corresponding to the Orthogonal Frequency Division Multiplexing (OFDM) symbols... rank The average or minimum value is used to select either the MMSE mode or the QRM-MLD mode; that is, all subcarriers corresponding to each OFDM symbol uniformly select either the MMSE algorithm or the QRM-MLD algorithm.

[0059] For example, when the channel correlation is high, the rank of the channel autocorrelation matrix... When the average or minimum value is large, the MMSE algorithm is uniformly selected for all subcarriers corresponding to OFDM symbols; when the channel correlation is low, the rank of the channel autocorrelation matrix is... When the average or minimum value is small, the QRM-MLD algorithm is uniformly selected for all subcarriers corresponding to the OFDM symbol.

[0060] It should be noted that the rank calculation of the channel matrix is ​​relatively complex and has low processing efficiency. Moreover, for all subcarriers corresponding to the same OFDM symbol, only the same detection algorithm can be selected, which is not flexible enough. This may result in a large number of QRM-MLD algorithms being selected, leading to higher chip power consumption.

[0061] Based on this, the present invention provides an adaptive detection scheme that can effectively solve the problem that all subcarriers corresponding to the same OFDM symbol must select the same detection algorithm, thereby achieving the goal of selecting the detection algorithm based on the subcarrier dimension. In this way, the overall processing complexity is effectively reduced, and thus the chip power consumption is effectively reduced.

[0062] Figure 2 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 1 This method can optionally be applied to Figure 1 The system shown is not limited to this. The method includes at least a portion of the following.

[0063] S210. Determine the channel matrix corresponding to the subcarriers among the multiple subcarriers; wherein the multiple subcarriers are the subcarriers corresponding to OFDM symbols.

[0064] S220. Based on the channel matrix corresponding to the subcarrier, obtain the first signal-to-noise ratio related information corresponding to the subcarrier.

[0065] S230. At least based on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and the first preset threshold, determine the target detection algorithm corresponding to the subcarrier.

[0066] Here, the target detection algorithm is either a first detection algorithm or a second detection algorithm, and the complexity of the first detection algorithm is greater than that of the second detection algorithm.

[0067] In other words, based on the scheme disclosed herein, target detection algorithms for each subcarrier corresponding to an OFDM symbol can be obtained. This allows each subcarrier to independently select its corresponding detection algorithm, effectively reducing the overall proportion of the first detection algorithm, and consequently, effectively reducing processing complexity and chip power consumption overall.

[0068] In one implementation, when the target detection algorithm is the first detection algorithm, the first detection algorithm is the QRM-MLD algorithm. In this case, the QRM-MLD algorithm can more accurately reflect the signal-to-noise ratio of the system.

[0069] In another embodiment, when the target detection algorithm is the second detection algorithm, the second detection algorithm is the MMSE algorithm, which has a lower complexity than the first detection algorithm; furthermore, the complexity of the MMSE algorithm is lower than the complexity of the QRM-MLD algorithm.

[0070] In another embodiment, the first detection algorithm is the QRM-MLD algorithm, and the second detection algorithm is the MMSE algorithm.

[0071] In some possible implementations, two of the multiple subcarriers may have different target detection algorithms. That is, among all the subcarriers corresponding to an OFDM symbol, there may be cases where different subcarriers select different target detection algorithms. For example, there may be at least one subcarrier with a first detection algorithm, and at least another subcarrier with a second detection algorithm. This achieves the goal of selecting the detection algorithm based on the subcarrier dimension, improving flexibility. Simultaneously, it effectively reduces the overall proportion of the first detection algorithm, thereby effectively reducing processing complexity and chip power consumption overall.

[0072] Furthermore, in a specific example, even if the present disclosure can achieve the purpose of selecting the detection algorithm for the subcarrier dimension, in actual scenarios, the following situation may occur: the target detection algorithms corresponding to all subcarriers of the OFDM symbol determined by the present disclosure are the same, for example, all of them are the first detection algorithm, or all of them are the second detection algorithm.

[0073] In some possible implementations, the target detection algorithm corresponding to the subcarrier can be determined in the following manner; specifically, S230 above specifically includes:

[0074] Method 1: When the first signal-to-noise ratio related information is greater than or equal to the first preset threshold, the first detection algorithm is used as the target detection algorithm.

[0075] Method 2: When the first signal-to-noise ratio related information is less than the first preset threshold, the second detection algorithm is used as the target detection algorithm.

[0076] In other words, when the first signal-to-noise ratio related information is greater than or equal to the first preset threshold, the first detection algorithm with higher complexity that can more accurately reflect the system's signal-to-noise ratio is selected. When the first signal-to-noise ratio related information is less than the first preset threshold, a second detection algorithm with performance similar to the first detection algorithm but lower complexity can be selected. This reduces the overall proportion of the first detection algorithm, thereby effectively reducing the processing complexity and chip power consumption.

[0077] In some possible implementations, the first signal-to-noise ratio related information can be obtained in the following manner, specifically, Figure 3 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 2 This method can optionally be applied to Figure 1 The system shown is not limited to this. The method includes at least a portion of the following.

[0078] S310. Determine the channel matrix corresponding to the subcarriers among the multiple subcarriers; wherein the multiple subcarriers are the subcarriers corresponding to OFDM symbols.

[0079] S320. Based on the channel matrix corresponding to the subcarrier, obtain the target posterior signal-to-noise ratio of the subcarrier and the target prior signal-to-noise ratio of the subcarrier.

[0080] In a specific example, the target posterior signal-to-noise ratio (SNR) can be obtained as follows, with the specific steps including: when the subcarrier corresponds to multiple transmission layers, obtaining the posterior SNR of each transmission layer based on the channel matrix corresponding to the subcarrier; and obtaining the target posterior SNR of the subcarrier based on the posterior SNR of each transmission layer. For example, the posterior SNR of one transmission layer can be directly used as the target posterior SNR corresponding to the subcarrier.

[0081] Alternatively, in one example, after obtaining the a posteriori signal-to-noise ratio (SNR) of each of the plurality of transport layers, the minimum a posteriori SNR among the plurality of transport layers can be used as the target a posteriori SNR of the subcarrier. Alternatively, based on the a posteriori SNR of each of the plurality of transport layers, an average a posteriori SNR can be obtained, and then the average a posteriori SNR can be used as the target a posteriori SNR of the subcarrier.

[0082] For example, the posterior signal-to-noise ratio (PostSnr) of the MMSE can be obtained using the following formula:

[0083] ;

[0084] .

[0085] here, Represents the transmitted signal vector; Represents the received signal vector; Represents the channel matrix; Represents complex Gaussian white noise; I represents the identity matrix; The autocorrelation matrix representing the noise; This represents singular values. This represents the determinant operator.

[0086] Furthermore, based on the above... The formula yields the a posteriori signal-to-noise ratio of each transmission layer in the multiple transmission layers corresponding to this subcarrier. Thus, the posterior signal-to-noise ratio of the target is obtained.

[0087] In another specific example, the target prior signal-to-noise ratio (SNR) can be obtained as follows, with the specific steps including: when the subcarrier corresponds to multiple transmission layers, obtaining the prior SNR of each of the multiple transmission layers based on the channel matrix corresponding to the subcarrier; and obtaining the target prior SNR of the subcarrier based on the prior SNR of each of the multiple transmission layers. For example, the prior SNR of one transmission layer can be directly used as the target prior SNR of the subcarrier.

[0088] Alternatively, in one example, after obtaining the posterior signal-to-noise ratio (SNR) of each of the plurality of transmission layers, the minimum prior SNR among the plurality of transmission layers can be used as the target prior SNR of the subcarrier; or, based on the prior SNR of each of the plurality of transmission layers, the average prior SNR is obtained, and then the average prior SNR is used as the target prior SNR of the subcarrier.

[0089] For example, the prior signal-to-noise ratio can be obtained using the following formula. :

[0090] ;

[0091] here, Represents the channel matrix; The autocorrelation matrix represents the noise.

[0092] Furthermore, based on the aforementioned prior signal-to-noise ratio... The formula is used to obtain the prior signal-to-noise ratio of each transmission layer in the multiple transmission layers corresponding to the subcarrier, and then the target prior signal-to-noise ratio is obtained.

[0093] S330. Based on the difference between the target prior signal-to-noise ratio and the target posterior signal-to-noise ratio of the subcarrier, obtain the first signal-to-noise ratio related information corresponding to the subcarrier.

[0094] It should be noted that the above-mentioned prior signal-to-noise ratio (Also known as lossless signal-to-noise ratio), which is equivalent to considering only the channel matrix. The power value of the main diagonal, which is also the target prior signal-to-noise ratio, is equivalent to considering only the channel matrix. The power value of the main diagonal; and the aforementioned posterior signal-to-noise ratio (e.g. This is equivalent to considering the channel matrix. The power values ​​of the main diagonal and secondary diagonal, which are the target posterior signal-to-noise ratios obtained above, are equivalent to considering the channel matrix. The power values ​​of the main diagonal and secondary diagonal are considered. Based on this, the difference between the two, i.e., the difference between the target prior SNR and the target posterior SNR, is equivalent to the impact of interference on the optimal SNR of the system. Thus, the detection algorithm corresponding to the subcarrier can be determined based on the difference between the target prior SNR and the target posterior SNR. For example, when this impact (i.e., the difference between the target prior SNR and the target posterior SNR) is greater than a threshold, the first detection algorithm (e.g., using a multi-layer QRM-MLD algorithm) should be considered, as it more accurately reflects the system's SNR. When this impact (i.e., the difference between the target prior SNR and the target posterior SNR) is small, a second detection algorithm (e.g., the MMSE algorithm) with performance close to that of the first detection algorithm but lower complexity can be selected, thereby improving processing efficiency without sacrificing performance.

[0095] Furthermore, in a specific example, the first signal-to-noise ratio related information can be obtained based on one of the following methods:

[0096] Method 1: The minimum a posteriori signal-to-noise ratio (SNR) among the multiple transmission layers is used as the target a posteriori SNR of the subcarrier, and the minimum prior SNR among the multiple transmission layers is used as the target prior SNR of the subcarrier. In this case, the first SNR related information = minimum prior SNR - minimum a posteriori SNR.

[0097] Method 2: The average posterior signal-to-noise ratio is used as the target posterior signal-to-noise ratio of the subcarrier, and the minimum prior signal-to-noise ratio among the multiple transmission layers is used as the target prior signal-to-noise ratio of the subcarrier. In this case, the first signal-to-noise ratio related information = minimum prior signal-to-noise ratio - average posterior signal-to-noise ratio.

[0098] Method 3: The minimum a posteriori signal-to-noise ratio among the multiple transmission layers is used as the target a posteriori signal-to-noise ratio of the subcarrier, and the average prior signal-to-noise ratio is used as the target prior signal-to-noise ratio of the subcarrier. In this case, the first signal-to-noise ratio related information = average prior signal-to-noise ratio - minimum a posteriori signal-to-noise ratio.

[0099] Method 4: Use the average posterior signal-to-noise ratio as the target posterior signal-to-noise ratio of the subcarrier, and use the average prior signal-to-noise ratio as the target prior signal-to-noise ratio of the subcarrier. In this case, the first signal-to-noise ratio related information = average prior signal-to-noise ratio - average posterior signal-to-noise ratio.

[0100] S340. At least based on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and the first preset threshold, determine the target detection algorithm corresponding to the subcarrier.

[0101] As can be understood, the specific processing method of S340 can be found in the above description, and will not be repeated here. In this way, without reducing performance, the overall proportion of the first detection algorithm is effectively reduced, thereby effectively reducing the overall processing complexity and chip power consumption.

[0102] In some possible implementations, the first signal-to-noise ratio related information can be obtained in the following manner, specifically, Figure 4 This is an illustrative flow diagram of a detection method according to an embodiment of this application. Figure 3 This method can optionally be applied to Figure 1 The system shown is not limited to this. The method includes at least a portion of the following.

[0103] S410. Determine the channel matrix corresponding to the subcarriers among the multiple subcarriers; wherein the multiple subcarriers are the subcarriers corresponding to OFDM symbols.

[0104] S420. Based on the channel matrix corresponding to the subcarrier, obtain the first signal-to-noise ratio related information corresponding to the subcarrier.

[0105] It is understandable that the methods for determining the first signal-to-noise ratio (SNR) related information can all be applied to this scheme. In other words, the methods for determining the first SNR related information can be found above. Figure 3 The relevant descriptions will not be repeated here.

[0106] S430. Based on the channel matrix corresponding to the subcarrier, obtain the second signal-to-noise ratio related information corresponding to the subcarrier.

[0107] It is understandable that the execution order of S420 and S430 can be interchanged. This disclosed solution does not impose specific restrictions on this, as long as the first signal-to-noise ratio related information and the second signal-to-noise ratio related information are obtained before S440.

[0108] In a specific example, the second signal-to-noise ratio (SNR) related information can be obtained in the following manner, specifically S430 includes: when the subcarrier corresponds to multiple transmission layers, obtaining the posterior SNR of each transmission layer in the multiple transmission layers based on the channel matrix corresponding to the subcarrier; and then obtaining the second SNR related information corresponding to the subcarrier based on the difference between the posterior SNRs of two transmission layers (e.g., any two transmission layers). For example, the difference between the posterior SNRs of any two transmission layers in the multiple transmission layers can be used as the second SNR related information corresponding to the subcarrier.

[0109] Furthermore, in one example, the difference between the maximum and minimum a posteriori signal-to-noise ratio (SNR) among the plurality of transport layers is used as the second SNR-related information for the subcarrier. That is, after obtaining the a posteriori SNR of each of the plurality of transport layers, the maximum and minimum a posteriori SNR can be selected, and the difference between the maximum and minimum a posteriori SNR is used as the second SNR-related information.

[0110] It is understandable that the a posteriori signal-to-noise ratio of each transmission layer can be obtained in the manner described above, and will not be repeated here.

[0111] S440. Based on the relationship between the first signal-to-noise ratio related information and the first preset threshold corresponding to the subcarrier, and the relationship between the second signal-to-noise ratio related information and the second preset threshold corresponding to the subcarrier, the target detection algorithm corresponding to the subcarrier is determined.

[0112] In a specific example, S440 specifically includes:

[0113] If the first signal-to-noise ratio related information corresponding to the subcarrier is less than the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold, the second detection algorithm shall be used as the target detection algorithm.

[0114] Alternatively, the first detection algorithm may be used as the target detection algorithm if one of the following three conditions is met:

[0115] The first signal-to-noise ratio related information corresponding to the subcarrier is less than the first preset threshold, but the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold;

[0116] The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, but the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold;

[0117] The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold.

[0118] In other words, in this example, if the first signal-to-noise ratio related information corresponding to the subcarrier is less than the first preset threshold and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold, the second detection algorithm with lower complexity can be used as the target detection algorithm corresponding to the subcarrier. Otherwise, in other cases, the first detection algorithm with higher complexity can be used as the target detection algorithm corresponding to the subcarrier.

[0119] For example, the following situations exist in this example:

[0120] Scenario 1: First SNR-related information = minimum prior SNR - minimum posterior SNR, second SNR-related information = maximum posterior SNR - minimum posterior SNR; In this case, if the first SNR-related information for the subcarrier is less than a first preset threshold, and the second SNR-related information for the subcarrier is less than a second preset threshold, the second detection algorithm with lower complexity is selected as the target detection algorithm for the subcarrier. Otherwise, in other cases, the first detection algorithm with higher complexity is selected as the target detection algorithm for the subcarrier.

[0121] Method 2: The first SNR-related information = minimum prior SNR - average posterior SNR, and the second SNR-related information = maximum posterior SNR - minimum posterior SNR. In this case, if the first SNR-related information for the subcarrier is less than a first preset threshold, and the second SNR-related information for the subcarrier is less than a second preset threshold, the second detection algorithm with lower complexity is selected as the target detection algorithm for the subcarrier. Otherwise, in other cases, the first detection algorithm with higher complexity is selected as the target detection algorithm for the subcarrier.

[0122] Method 3: First SNR-related information = Average prior SNR - Minimum posterior SNR; Second SNR-related information = Maximum posterior SNR - Minimum posterior SNR. In this case, if the first SNR-related information for the subcarrier is less than a first preset threshold, and the second SNR-related information for the subcarrier is less than a second preset threshold, the second detection algorithm with lower complexity is selected as the target detection algorithm for the subcarrier. Otherwise, in other cases, the first detection algorithm with higher complexity is selected as the target detection algorithm for the subcarrier.

[0123] Method 4: First SNR-related information = Average prior SNR - Average posterior SNR; Second SNR-related information = Maximum posterior SNR - Minimum posterior SNR. In this case, if the first SNR-related information for the subcarrier is less than a first preset threshold, and the second SNR-related information for the subcarrier is less than a second preset threshold, the second detection algorithm with lower complexity is selected as the target detection algorithm for the subcarrier. Otherwise, in other cases, the first detection algorithm with higher complexity is selected as the target detection algorithm for the subcarrier.

[0124] The following detailed explanation of this disclosed solution, using a specific example, illustrates how the difference between the lossless signal-to-noise ratio (SNR) and the posterior SNR corresponding to each subcarrier can be used as the first discrimination threshold for the subcarrier, thereby determining the detection algorithm for each subcarrier. This method has the same physical meaning as calculating the rank of a matrix; in other words, this method is highly interpretable, but its algorithm complexity is simpler and less computationally intensive compared to calculating the rank of a matrix. Therefore, it effectively reduces the complexity of the processing and thus effectively reduces the chip power consumption.

[0125] Specifically, in this example, the lossless signal-to-noise ratio (SNR) (i.e., the prior SNR) is equivalent to considering only the power values ​​of the main diagonal of the channel matrix, while the posterior SNR is equivalent to considering the power values ​​of both the main and secondary diagonals of the channel matrix. The difference between the two is equivalent to the impact of interference bands on the optimal SNR of the system. Therefore, when this impact (i.e., the difference between the prior and posterior SNR) is greater than a threshold value, a multi-layer QRM-MLD algorithm can be used to more accurately reflect the system's SNR. When this impact is small, the performance of the MMSE algorithm and QRM-MLD is similar; in this case, the less complex MMSE algorithm can be used.

[0126] Based on this, this example enables each subcarrier corresponding to each symbol to independently select either the MMSE algorithm or the QRM-MLD algorithm. Then, by configuring appropriate soft bit scaling for the MMSE algorithm and the QRM-MLD algorithm, the results obtained by the two algorithms reach an appropriate size before entering the decoder. In this way, without reducing performance, the proportion of QRM-MLD can be greatly reduced, thereby reducing chip power consumption.

[0127] Here, a method for determining the first discrimination threshold (i.e., the first signal-to-noise ratio related information mentioned above) is given, and then the detection algorithm corresponding to the subcarrier is determined based on the first discrimination threshold; specifically, the first discrimination threshold = the target prior signal-to-noise ratio corresponding to the subcarrier - the target posterior signal-to-noise ratio corresponding to the subcarrier.

[0128] The target prior signal-to-noise ratio (SNR) corresponding to the subcarrier can be the minimum of the prior SNRs (PreSnr) of each of the N (positive integers greater than or equal to 2) transmission layers of that subcarrier, i.e., the minimum prior SNR PreSnr; or, it can be the average of the prior SNRs of each of the N transmission layers, i.e., the average prior SNR PreSnr. Furthermore, the prior SNR PreSnr of each transmission layer in the subcarrier can be obtained using the following formula:

[0129] ;

[0130] Here, H represents the channel matrix corresponding to the subcarrier; The autocorrelation matrix represents the noise.

[0131] Furthermore, the target posterior signal-to-noise ratio corresponding to the subcarrier can be the minimum value among the posterior signal-to-noise ratios (e.g., PostSnr) of each of the N transmission layers of the subcarrier, i.e., the minimum posterior signal-to-noise ratio PostSnr; or it can be the average value of the posterior signal-to-noise ratios of each of the N transmission layers, i.e., the average posterior signal-to-noise ratio PostSnr.

[0132] Here, the a posteriori signal-to-noise ratio (PSNR) PostSnr of each transmission layer in the subcarrier can be specifically defined as the a posteriori PSNR PostSnr of the MMSE (i.e., Its calculation formula is:

[0133] ;

[0134] ;

[0135] here, Represents the transmitted signal vector; Represents the received signal vector; Represents the channel matrix; Represents complex Gaussian white noise; I represents the identity matrix; The autocorrelation matrix representing the noise; This represents singular values. This represents the determinant operator.

[0136] The posterior signal-to-noise ratio (SNR) of the QRM-MLD algorithm (which can be denoted as...) The following requirements must be met:

[0137] 。

[0138] Based on this, if the first discrimination threshold is greater than or equal to threshold value 1 (i.e., the first preset threshold), the QRM-MLD algorithm can be selected as the detection algorithm corresponding to the subcarrier; and if the first discrimination threshold is less than threshold value 1 (i.e., the first preset threshold), the MMSE algorithm can be selected as the detection algorithm corresponding to the subcarrier.

[0139] Furthermore, a second discrimination threshold (i.e., the second signal-to-noise ratio related information mentioned above) can be set. The second discrimination threshold is equal to the maximum value of the posterior signal-to-noise ratios (i.e., the maximum posterior signal-to-noise ratio) among the transmission layers of the N transmission layers of the subcarrier and the minimum value of the posterior signal-to-noise ratios (i.e., the minimum posterior signal-to-noise ratio) among the transmission layers of the N transmission layers of the subcarrier.

[0140] At this point, if the first discrimination threshold is less than threshold 1 and the second discrimination threshold is less than threshold 2, the MMSE algorithm is selected as the detection algorithm for the subcarrier; otherwise, the QRM-MLD algorithm is selected as the detection algorithm for the subcarrier.

[0141] In this way, the disclosed solution adaptively adjusts the ratio of MMSE algorithm and QRM-MLD algorithm, thereby selecting as few QRM-MLD algorithms as possible without reducing performance, thus effectively reducing chip power consumption.

[0142] The following specific simulation examples further illustrate the effectiveness of this example. Specifically, the case in Table 1 is the simulation result of 8 transmit (referring to 8 transmit antennas), 2 receive (referring to 2 receive antennas), and 2 streams (referring to two different signals) in the AWGN channel under HESU mode. From the simulation results, it can be seen that MMSE accounts for 60% and QRM-MLD (abbreviated as MLD) accounts for 40%. At this time, it can achieve performance results close to QRM-MLD. In other words, using the scheme disclosed in this paper can effectively reduce complexity with a small performance cost.

[0143] Table 1 HESU 8 2 2 Simulation results of different MCS

[0144]

[0145] Table 2 shows the simulation results of 6 transmit, 2 receive, and 2 streams in the CHANNEL B channel under HESU mode.

[0146] Table 2 Simulation results of a certain format with different bandwidths under non-CSD conditions

[0147]

[0148] This disclosure also provides a terminal device, specifically, Figure 5 This is a schematic block diagram of a terminal device 500 according to an embodiment of this application. Figure 1 Specifically, the terminal device 500 may include:

[0149] Matrix processing unit 510 is used to determine the channel matrix corresponding to a subcarrier among a plurality of subcarriers; wherein, the plurality of subcarriers are subcarriers corresponding to OFDM symbols;

[0150] The algorithm processing unit 520 is used to obtain the first signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier; and to determine the target detection algorithm corresponding to the subcarrier based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and a first preset threshold.

[0151] The target detection algorithm is either a first detection algorithm or a second detection algorithm, wherein the complexity of the first detection algorithm is greater than that of the second detection algorithm.

[0152] In a specific example of the scheme disclosed herein, when the target detection algorithm is the first detection algorithm, the first detection algorithm is a maximum likelihood detection algorithm with QR decomposition; or...

[0153] When the target detection algorithm is the second detection algorithm, the second detection algorithm is the minimum mean square error algorithm.

[0154] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0155] If the first signal-to-noise ratio related information is greater than or equal to a first preset threshold, the first detection algorithm is used as the target detection algorithm; or,

[0156] If the first signal-to-noise ratio related information is less than the first preset threshold, the second detection algorithm will be used as the target detection algorithm.

[0157] In a specific example of the scheme disclosed herein, before determining the target detection algorithm corresponding to the subcarrier, the algorithm processing unit 520 is further configured to:

[0158] Based on the channel matrix corresponding to the subcarrier, the second signal-to-noise ratio related information corresponding to the subcarrier is obtained;

[0159] Based on the relationship between the first signal-to-noise ratio related information and the first preset threshold corresponding to the subcarrier, and the relationship between the second signal-to-noise ratio related information and the second preset threshold corresponding to the subcarrier, the target detection algorithm corresponding to the subcarrier is determined.

[0160] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0161] If the first signal-to-noise ratio related information corresponding to the subcarrier is less than the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold, the second detection algorithm shall be used as the target detection algorithm.

[0162] Alternatively, the first detection algorithm may be used as the target detection algorithm in one of the following cases:

[0163] The first signal-to-noise ratio related information corresponding to the subcarrier is less than a first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold;

[0164] The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold;

[0165] The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold.

[0166] In a specific example of the scheme disclosed herein, there are two subcarriers among the plurality of subcarriers, and the target detection algorithms corresponding to each of the two subcarriers are different.

[0167] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0168] Based on the channel matrix corresponding to the subcarrier, the target posterior signal-to-noise ratio of the subcarrier and the target prior signal-to-noise ratio of the subcarrier are obtained.

[0169] Based on the difference between the target prior signal-to-noise ratio and the target posterior signal-to-noise ratio of the subcarrier, the first signal-to-noise ratio related information corresponding to the subcarrier is obtained.

[0170] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0171] When a subcarrier corresponds to multiple transmission layers, the a posteriori signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier.

[0172] The target posterior signal-to-noise ratio of the subcarrier is obtained based on the posterior signal-to-noise ratio of each of the multiple transmission layers.

[0173] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0174] The minimum a posteriori signal-to-noise ratio among the multiple transmission layers is taken as the target a posteriori signal-to-noise ratio of the subcarrier;

[0175] Alternatively, the average posterior signal-to-noise ratio (SNR) can be obtained based on the posterior SNR of each of the multiple transmission layers; the average posterior SNR can then be used as the target posterior SNR of the subcarrier.

[0176] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0177] When a subcarrier corresponds to multiple transmission layers, the prior signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier.

[0178] The target prior signal-to-noise ratio of the subcarrier is obtained based on the prior signal-to-noise ratio of each of the multiple transmission layers.

[0179] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0180] The minimum prior signal-to-noise ratio among the multiple transmission layers is taken as the target prior signal-to-noise ratio of the subcarrier;

[0181] Alternatively, based on the prior signal-to-noise ratio of each of the multiple transmission layers, the average prior signal-to-noise ratio is obtained; the average prior signal-to-noise ratio is then used as the target prior signal-to-noise ratio of the subcarrier.

[0182] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0183] When a subcarrier corresponds to multiple transmission layers, the a posteriori signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier.

[0184] Based on the difference in a posteriori signal-to-noise ratio between two of the multiple transmission layers, the second signal-to-noise ratio related information corresponding to the subcarrier is obtained.

[0185] In a specific example of the scheme disclosed herein, the algorithm processing unit 520 is specifically used for:

[0186] The difference between the maximum and minimum a posteriori signal-to-noise ratios among the multiple transmission layers is used as the second signal-to-noise ratio related information for the subcarrier.

[0187] Figure 6 This is a schematic block diagram of a terminal device 600 according to an embodiment of this application. Figure 2 The terminal device 600 may include:

[0188] A processor 610 and a memory 620 are provided. The memory stores computer programs, and the processor calls and runs the computer programs stored in the memory to enable the terminal device to execute the detection method. The terminal device 600 of this embodiment can implement the corresponding functions of the terminal device in the foregoing method embodiments. The processes, functions, implementation methods, and beneficial effects of each module (sub-module, unit, or component, etc.) in the terminal device 600 can be found in the corresponding descriptions in the above method embodiments, and will not be repeated here. It should be noted that the functions described for each module (sub-module, unit, or component, etc.) in the terminal device 600 of this embodiment can be implemented by different modules (sub-modules, units, or components, etc.) or by the same module (sub-module, unit, or component, etc.).

[0189] In the embodiments of this application, each unit of the aforementioned terminal device may implement its function in the form of software, hardware, or a combination of software and hardware. 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 of devices or units may be electrical, mechanical, or other forms.

[0190] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0191] 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 units described above can be implemented in hardware or as software functional units. For example, at least one of the matrix processing unit and algorithm processing unit of the terminal device can be implemented by the processor of the terminal device.

[0192] Figure 7 This is a schematic structural diagram of a communication device 700 according to an embodiment of this application. The communication device 700 includes a processor 710, which can call and run computer programs from memory to enable the communication device 700 to implement the methods in the embodiments of this application.

[0193] In one embodiment, the communication device 700 may further include a memory 720. The processor 710 can retrieve and run computer programs from the memory 720 to enable the communication device 700 to implement the methods described in the embodiments of this application.

[0194] The memory 720 can be a separate device independent of the processor 710, or it can be integrated into the processor 710.

[0195] In one embodiment, the communication device 700 may further include a transceiver 730, which the processor 710 may control to communicate with other devices. Specifically, it may send information or data to other devices or receive information or data sent by other devices.

[0196] The transceiver 730 may include a transmitter and a receiver. The transceiver 730 may further include antennas, and the number of antennas may be one or more.

[0197] In one embodiment, the communication device 700 may be a network device in the embodiments of this application, and the communication device 700 may implement the corresponding processes implemented by the network device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0198] In one embodiment, the communication device 700 may be a terminal device in the embodiments of this application, and the communication device 700 may implement the corresponding processes implemented by the terminal device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0199] Figure 8 This is a schematic structural diagram of a chip 800 according to an embodiment of this application. The chip 800 includes a processor 810, which can call and run computer programs from memory to implement the methods in the embodiments of this application.

[0200] In one embodiment, chip 800 may further include memory 820. Processor 810 can retrieve and run computer programs from memory 820 to implement the methods executed by a terminal device or network device in this embodiment.

[0201] The memory 820 can be a separate device independent of the processor 810, or it can be integrated into the processor 810.

[0202] In one embodiment, the chip 800 may further include an input interface 830. The processor 810 can control the input interface 830 to communicate with other devices or chips; specifically, it can acquire information or data sent by other devices or chips.

[0203] In one embodiment, the chip 800 may further include an output interface 840. The processor 810 can control the output interface 840 to communicate with other devices or chips; specifically, it can output information or data to other devices or chips.

[0204] In one implementation, the chip can be applied to the network device in the embodiments of this application, and the chip can implement the corresponding processes implemented by the network device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0205] In one embodiment, the chip can be applied to the terminal device in the embodiments of this application, and the chip can implement the corresponding processes implemented by the terminal device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0206] The chips used in network equipment and terminal equipment can be the same chip or different chips.

[0207] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0208] The processors mentioned above can be general-purpose processors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), or other programmable logic devices, transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processors mentioned above can be microprocessors or any conventional processor.

[0209] The aforementioned memory can be volatile memory or non-volatile memory, or a combination of both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM).

[0210] It should be understood that the above-described memory is exemplary and not a limiting description. For example, the memory in the embodiments of this application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM), etc. That is to say, the memory in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0211] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0212] It should be understood that, in the various embodiments of this application, the order of the above-mentioned processes does not imply 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 this application.

[0213] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0214] 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 that can be easily conceived by those skilled in the art within the scope of the technology 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 detection method, comprising: Determine the channel matrix corresponding to the subcarriers among a plurality of subcarriers; wherein, the plurality of subcarriers are the subcarriers corresponding to OFDM symbols; Based on the channel matrix corresponding to the subcarrier, the first signal-to-noise ratio related information corresponding to the subcarrier is obtained; The target detection algorithm corresponding to the subcarrier is determined based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and the first preset threshold. The target detection algorithm is either a first detection algorithm or a second detection algorithm, wherein the complexity of the first detection algorithm is greater than that of the second detection algorithm. The step of obtaining the first signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier includes: Based on the channel matrix corresponding to the subcarrier, the target posterior signal-to-noise ratio (SNR) of the subcarrier and the target prior signal-to-noise ratio (SNR) of the subcarrier are obtained; wherein, the target posterior SNR is obtained based on the posterior SNR of multiple transmission layers corresponding to the subcarrier; the target prior SNR is obtained based on the prior SNR of multiple transmission layers corresponding to the subcarrier. Based on the difference between the target prior signal-to-noise ratio and the target posterior signal-to-noise ratio of the subcarrier, the first signal-to-noise ratio related information corresponding to the subcarrier is obtained; Before determining the target detection algorithm corresponding to the subcarrier, the method further includes: Based on the channel matrix corresponding to the subcarrier, a second signal-to-noise ratio (SNR) related information corresponding to the subcarrier is obtained; wherein, the second SNR related information corresponding to the subcarrier is obtained based on the posterior SNR of each transmission layer in the multiple transmission layers corresponding to the subcarrier; The step of determining the target detection algorithm corresponding to the subcarrier based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and the first preset threshold includes: If the first signal-to-noise ratio related information corresponding to the subcarrier is less than a first preset threshold and the second signal-to-noise ratio related information corresponding to the subcarrier is less than a second preset threshold, the second detection algorithm shall be used as the target detection algorithm. Alternatively, the first detection algorithm may be used as the target detection algorithm in one of the following cases: The first signal-to-noise ratio related information corresponding to the subcarrier is less than a first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold; The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold; The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold.

2. The method according to claim 1, further comprising: If the first signal-to-noise ratio related information is greater than or equal to the first preset threshold, the first detection algorithm is used as the target detection algorithm; or, If the first signal-to-noise ratio related information is less than the first preset threshold, the second detection algorithm will be used as the target detection algorithm.

3. The method according to claim 1 or 2, wherein, Two of the multiple subcarriers exist, and the target detection algorithms corresponding to each of the two subcarriers are different.

4. The method according to claim 1 or 2, wherein, The step of obtaining the target posterior signal-to-noise ratio of the subcarrier based on the channel matrix corresponding to the subcarrier includes: When a subcarrier corresponds to multiple transmission layers, the a posteriori signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier. The target posterior signal-to-noise ratio of the subcarrier is obtained based on the posterior signal-to-noise ratio of each of the multiple transmission layers.

5. The method according to claim 4, wherein, The step of obtaining the target posterior signal-to-noise ratio of the subcarrier based on the posterior signal-to-noise ratio of each of the plurality of transmission layers includes: The minimum a posteriori signal-to-noise ratio among the multiple transmission layers is taken as the target a posteriori signal-to-noise ratio of the subcarrier; Alternatively, the average posterior signal-to-noise ratio (SNR) can be obtained based on the posterior SNR of each of the multiple transmission layers; the average posterior SNR can then be used as the target posterior SNR of the subcarrier.

6. The method according to claim 1 or 2, wherein, The step of obtaining the target prior signal-to-noise ratio of the subcarrier based on the channel matrix corresponding to the subcarrier includes: When a subcarrier corresponds to multiple transmission layers, the prior signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier. The target prior signal-to-noise ratio of the subcarrier is obtained based on the prior signal-to-noise ratio of each of the multiple transmission layers.

7. The method according to claim 6, wherein, The step of obtaining the target prior signal-to-noise ratio of the subcarrier based on the prior signal-to-noise ratio of each of the multiple transmission layers includes: The minimum prior signal-to-noise ratio among the multiple transmission layers is taken as the target prior signal-to-noise ratio of the subcarrier; Alternatively, based on the prior signal-to-noise ratio of each of the multiple transmission layers, the average prior signal-to-noise ratio is obtained; the average prior signal-to-noise ratio is then used as the target prior signal-to-noise ratio of the subcarrier.

8. The method according to claim 1 or 2, wherein, The step of obtaining the second signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier includes: When a subcarrier corresponds to multiple transmission layers, the a posteriori signal-to-noise ratio of each transmission layer in the multiple transmission layers is obtained based on the channel matrix corresponding to the subcarrier. Based on the difference in a posteriori signal-to-noise ratio between two of the multiple transmission layers, the second signal-to-noise ratio related information corresponding to the subcarrier is obtained.

9. The method according to claim 7, wherein, The step of obtaining the second signal-to-noise ratio (SNR) related information for the subcarrier based on the difference in posterior SNR between two transmission layers among the plurality of transmission layers includes: The difference between the maximum and minimum a posteriori signal-to-noise ratios among the multiple transmission layers is used as the second signal-to-noise ratio related information for the subcarrier.

10. The method according to claim 1 or 2, wherein, When the target detection algorithm is the first detection algorithm, the first detection algorithm is a maximum likelihood detection algorithm with QR decomposition; or... When the target detection algorithm is the second detection algorithm, the second detection algorithm is the minimum mean square error algorithm.

11. A chip, comprising: A matrix processing unit is used to determine the channel matrix corresponding to a subcarrier among multiple subcarriers; wherein the multiple subcarriers are subcarriers corresponding to OFDM symbols; The algorithm processing unit is used to obtain the first signal-to-noise ratio related information corresponding to the subcarrier based on the channel matrix corresponding to the subcarrier; and to determine the target detection algorithm corresponding to the subcarrier based at least on the relationship between the first signal-to-noise ratio related information corresponding to the subcarrier and a first preset threshold. The target detection algorithm is either a first detection algorithm or a second detection algorithm, wherein the complexity of the first detection algorithm is greater than that of the second detection algorithm. Specifically, the algorithm processing unit is used for: Based on the channel matrix corresponding to the subcarrier, the target posterior signal-to-noise ratio (SNR) of the subcarrier and the target prior signal-to-noise ratio (SNR) of the subcarrier are obtained; the target posterior SNR is obtained based on the posterior SNR of multiple transmission layers corresponding to the subcarrier; the target prior SNR is obtained based on the prior SNR of multiple transmission layers corresponding to the subcarrier. Based on the difference between the target prior signal-to-noise ratio and the target posterior signal-to-noise ratio of the subcarrier, the first signal-to-noise ratio related information corresponding to the subcarrier is obtained; The algorithm processing unit is further configured to: Before determining the target detection algorithm corresponding to the subcarrier, a second signal-to-noise ratio (SNR) related information corresponding to the subcarrier is obtained based on the channel matrix corresponding to the subcarrier; wherein, the second SNR related information corresponding to the subcarrier is obtained based on the posterior SNR of each transmission layer in the multiple transmission layers corresponding to the subcarrier; Specifically, the algorithm processing unit is used for: If the first signal-to-noise ratio related information corresponding to the subcarrier is less than a first preset threshold and the second signal-to-noise ratio related information corresponding to the subcarrier is less than a second preset threshold, the second detection algorithm shall be used as the target detection algorithm. Alternatively, the first detection algorithm may be used as the target detection algorithm in one of the following cases: The first signal-to-noise ratio related information corresponding to the subcarrier is less than a first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold; The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is less than the second preset threshold; The first signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the first preset threshold, and the second signal-to-noise ratio related information corresponding to the subcarrier is greater than or equal to the second preset threshold.

12. A chip, comprising: Processor and memory, of which, The memory is used to store computer programs; The processor is configured to call and run the computer program from the memory to perform the method as described in any one of claims 1 to 10.

13. A terminal device, comprising: A housing and a chip disposed inside the housing; wherein the chip is the chip according to claim 12.

14. A computer-readable storage medium for storing a computer program that, when run by a device, causes the device to perform the method as claimed in any one of claims 1 to 10.

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