DTX detection method of UCI and related device

Abstract

The invention discloses a DTX detection method of UCI and a related device, and relates to the technical field of communication. In the application, after an initial PUSCH signal sent by a terminal and a target PUSCH signal received by a base station are obtained, the initial PUSCH signal is reconstructed, and amplitude information removal processing is performed on the reconstructed PUSCH signal, so that the UCI measurement of the initial PUSCH signal is determined according to known signals such as a constant modulus PUSCH signal and the target PUSCH signal, and the UCI measurement of the initial PUSCH signal is determined according to the known signals such as the constant modulus PUSCH signal and the target PUSCH signal. The influence factors of the UCI measurement calculation are reduced, and the influence of the inconstant modulus on the UCI measurement calculation is eliminated; moreover, the measurement threshold value is set corresponding to the UCI measurement, so that the technical defect that the measurement threshold value obtained by multiple times of fitting is easily influenced by scenes in the related technology is avoided, the robustness of the detection method is improved, and the DTX detection accuracy for the UCI in the PUSCH channel is also improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a UCI DTX detection method and related devices. Background Art

[0002] In the fifth generation mobile communication (English: 5th Generation Mobile Networks, abbreviation: 5G) new air interface (English: New Radio, abbreviation: NR), in order to improve the flexibility of the communication system, when the data transmission situations of the data plane and the control plane are different, the uplink control information (English: Uplink Control Information, abbreviation: UCI) is multiplexed into the physical uplink shared channel (English: Physical Uplink Shared Channel, abbreviation: PUSCH) for transmission instead of the physical uplink control channel (English: Physical Uplink Control Channel, abbreviation: PUCCH).

[0003] Among them, UCIs of different lengths will have different encoding formats, and UCI within 11 bits does not have a cyclic redundancy check (CRC), so the correctness of the transmission cannot be detected through the CRC check of LDPC or Polar decoding.

[0004] Therefore, for the discontinuous transmission (DTX) activation detection of UCI within 11 bits, it is usually necessary to perform a probability distribution analysis based on the probability or even the coding rule of the relevant metric (such as DTX Metric) to distinguish or determine whether only the PUSCH signal is sent in the PUSCH channel or the PUSCH signal carrying the UCI is sent.

[0005] For example, see Figure 1 As shown in the distribution diagram of the probability density function (PDF) of the metric corresponding to the channel state information (CSI) 1, it can be found that the current DTX activation detection method has the following two problems:

[0006] 1. In the same scenario (e.g., the same signal-to-noise ratio (SNR)), when the PUSCH signal carries UCI or does not carry UCI, the probability density functions of the corresponding metrics will have a high probability of overlapping and confusion. In this way, if a suitable metric decision threshold value cannot be found, abnormal situations such as judgment errors will occur, resulting in a low accuracy rate of DTX detection for UCI.

[0007] 2. Regardless of whether it is a PUSCH signal with UCI or a PUSCH signal without UCI, the expectation of the corresponding measurement will change with the change of the scenario (such as SNR), resulting in the change of the measurement decision threshold value in different scenarios, which makes the above DTX activation detection method less robust.

[0008] Therefore, the above DTX activation detection method has low robustness because the metric and the metric decision threshold are greatly affected by the scene (that is, the metric and the metric decision threshold have many influencing factors). Summary of the invention

[0009] The embodiments of the present application provide a UCI DTX detection method and related devices to improve the robustness of the detection method, thereby improving the accuracy of DTX detection for UCI in a PUSCH channel.

[0010] In a first aspect, an embodiment of the present application provides a method for detecting discontinuous transmission DTX of uplink control information UCI, the method comprising:

[0011] An initial physical uplink shared channel PUSCH signal sent by the terminal and a target PUSCH signal received by the base station are respectively obtained; wherein the target PUSCH signal is obtained after performing channel equalization processing on the initial PUSCH signal;

[0012] Reconstructing the initial PUSCH signal to obtain a reconstructed PUSCH signal, and performing amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal;

[0013] Based on the modulation symbol sequences respectively included in the target PUSCH signal and the constant modulus PUSCH signal, a UCI metric of the initial PUSCH signal is obtained;

[0014] Based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, a UCI DTX detection is performed on the initial PUSCH signal.

[0015] In an optional embodiment, obtaining a UCI metric of an initial PUSCH signal based on a modulation symbol sequence respectively included in a target PUSCH signal and a constant modulus PUSCH signal includes:

[0016] Determine a first symbol sequence correlation between the target PUSCH signal and the constant modulus PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the constant modulus PUSCH signal;

[0017] A UCI metric of the initial PUSCH signal is obtained based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal.

[0018] Through the above embodiments, since the modulation symbol sequence included in the target PUSCH signal, the modulation symbol sequence included in the constant modulus PUSCH signal, and the modulation symbol sequence included in the initial PUSCH signal are all known and determined symbol sequences, thus, based on the first symbol sequence correlation obtained based on the modulation symbol sequence included in the target PUSCH signal and the modulation symbol sequence included in the constant modulus PUSCH signal, and the modulation symbol sequence included in the initial PUSCH signal, the UCI metric of the initial PUSCH signal is obtained, which is less affected by the environment and improves the robustness of the detection method.

[0019] In an optional embodiment, obtaining a UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal includes:

[0020] Obtaining a biased estimation deviation between an initial PUSCH signal and a target PUSCH signal; wherein the biased estimation deviation represents: a signal transmission quality of a frequency domain channel transmitting the initial PUSCH signal;

[0021] A UCI metric of the initial PUSCH signal is obtained based on the biased estimation deviation, the correlation of the first symbol sequence, and a modulation symbol sequence included in the initial PUSCH signal.

[0022] Through the above embodiments, in the calculation process of the UCI metric, the biased estimation deviation (usually a fixed value) between the initial PUSCH signal and the target PUSCH signal, that is, the system deviation, is taken into account, and the influence on the accuracy of the UCI metric calculation is taken into account. Therefore, by adopting this method, on the basis of improving the robustness of the detection method, the accuracy of the UCI metric calculation is also ensured to a certain extent.

[0023] In an optional embodiment, based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, performing DTX detection of UCI on the initial PUSCH signal includes:

[0024] respectively determining a first correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI, and a second correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI;

[0025] Perform amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution respectively to obtain a first metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a second metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0026] A metric threshold corresponding to the UCI metric is determined based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution, and a UCI DTX detection is performed on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0027] Through the above embodiment, the amplitude information of the first correlation normal distribution and the second correlation normal distribution is normalized to obtain the first metric normal distribution and the second metric normal distribution, and since the first metric expectation in the first metric normal distribution and the second metric expectation in the second metric normal distribution are both fixed values, the obtained metric threshold is also a fixed value (a constant or a fixed value related to the biased estimation deviation), that is, the metric threshold is basically not affected by the scene, thereby improving the robustness of the detection method.

[0028] In an optional embodiment, obtaining a UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal includes:

[0029] Determine a second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the reconstructed PUSCH signal;

[0030] Based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, and the second symbol sequence correlation, a UCI metric of the initial PUSCH signal is obtained.

[0031] Through the above embodiment, in the process of calculating the UCI metric, by constructing the second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal, the UCI metric of the initial PUSCH signal is obtained only based on the first symbol sequence correlation and the modulation symbol sequence contained in the initial PUSCH signal, and the second symbol sequence correlation, thereby eliminating the influence of the biased estimation deviation related to noise on the UCI metric calculation, that is, further improving the robustness of the detection method.

[0032] In an optional embodiment, based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, performing DTX detection of UCI on the initial PUSCH signal includes:

[0033] Determine respectively a third metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a fourth metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0034] Based on the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution, a metric threshold corresponding to the UCI metric is determined, and based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0035] Through the above embodiments, since the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution are both fixed values, the obtained metric threshold is also a fixed value (a constant or a fixed value related to the biased estimation deviation), that is, the obtained metric threshold is basically not affected by the scene, thereby improving the robustness of the detection method.

[0036] In an optional embodiment, obtaining a UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal includes:

[0037] Obtaining a target signal-to-noise ratio based on a modulation symbol sequence included in the initial PUSCH signal and a noise symbol sequence included in the target PUSCH signal;

[0038] A UCI metric of the initial PUSCH signal is obtained based on a biased estimation deviation and a target signal-to-noise ratio between the initial PUSCH signal and the target PUSCH signal, and a first symbol sequence correlation.

[0039] Through the above embodiments, since the biased estimation deviation is related to the noise, the UCI metric in the sense of the signal-to-noise ratio can be obtained according to the biased estimation deviation and the target signal-to-noise ratio, as well as the correlation of the first symbol sequence. Moreover, the UCI metric in the sense of the signal-to-noise ratio is only related to two known and determined symbol sequences, namely, the modulation symbol sequence contained in the target PUSCH signal and the modulation symbol sequence contained in the initial PUSCH signal, thereby improving the robustness of the detection method.

[0040] In an optional embodiment, based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, performing DTX detection of UCI on the initial PUSCH signal includes:

[0041] Performing metric threshold fitting on a fifth metric normal distribution of the UCI metric when the sample PUSCH signal carries UCI under multiple sample signal-to-noise ratios, and a sixth metric normal distribution of the UCI metric when the sample PUSCH signal does not carry UCI, to determine a metric threshold corresponding to the UCI metric;

[0042] Based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0043] Through the above embodiments, since the UCI metric is a metric in the sense of signal-to-noise ratio, it is relatively easy to fit a better metric threshold (eg, a robust metric threshold adapted to each SNR) to accurately distinguish or determine whether the PUSCH signal carries UCI.

[0044] In an optional embodiment, based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, performing DTX detection of UCI on the initial PUSCH signal includes:

[0045] If the UCI metric is greater than the metric threshold, it is determined that the initial PUSCH signal carries the UCI;

[0046] If the UCI metric is not greater than the metric threshold, it is determined that the initial PUSCH signal does not carry UCI.

[0047] Through the above embodiment, by judging the magnitude relationship between the UCI metric and the metric threshold, the DTX detection of the UCI of the initial PUSCH signal can be completed.

[0048] In a second aspect, an embodiment of the present application further provides a discontinuous transmission DTX detection device for uplink control information UCI, the device comprising:

[0049] A signal acquisition module, used to respectively acquire an initial physical uplink shared channel PUSCH signal sent by the terminal and a target PUSCH signal received by the base station; wherein the target PUSCH signal is obtained after performing channel equalization processing on the initial PUSCH signal;

[0050] A signal processing module, used for reconstructing the initial PUSCH signal to obtain a reconstructed PUSCH signal, and performing amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal;

[0051] A metric calculation module, used for obtaining a UCI metric of an initial PUSCH signal based on a modulation symbol sequence respectively included in a target PUSCH signal and a constant modulus PUSCH signal;

[0052] The signal detection module is used to perform DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric.

[0053] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the modulation symbol sequences respectively included in the target PUSCH signal and the constant modulus PUSCH signal, the metric calculation module is specifically used to:

[0054] Determine a first symbol sequence correlation between the target PUSCH signal and the constant modulus PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the constant modulus PUSCH signal;

[0055] A UCI metric of the initial PUSCH signal is obtained based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal.

[0056] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module is specifically used to:

[0057] Obtaining a biased estimation deviation between an initial PUSCH signal and a target PUSCH signal; wherein the biased estimation deviation represents: a signal transmission quality of a frequency domain channel transmitting the initial PUSCH signal;

[0058] A UCI metric of the initial PUSCH signal is obtained based on the biased estimation deviation, the correlation of the first symbol sequence, and a modulation symbol sequence included in the initial PUSCH signal.

[0059] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module is specifically used to:

[0060] respectively determining a first correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI, and a second correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI;

[0061] Perform amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution respectively to obtain a first metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a second metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0062] A metric threshold corresponding to the UCI metric is determined based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution, and a UCI DTX detection is performed on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0063] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module is specifically used to:

[0064] Determine a second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the reconstructed PUSCH signal;

[0065] Based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, and the second symbol sequence correlation, a UCI metric of the initial PUSCH signal is obtained.

[0066] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module is specifically used to:

[0067] Determine respectively a third metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a fourth metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0068] Based on the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution, a metric threshold corresponding to the UCI metric is determined, and based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0069] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module is specifically used to:

[0070] Obtaining a target signal-to-noise ratio based on a modulation symbol sequence included in the initial PUSCH signal and a noise symbol sequence included in the target PUSCH signal;

[0071] A UCI metric of the initial PUSCH signal is obtained based on a biased estimation deviation and a target signal-to-noise ratio between the initial PUSCH signal and the target PUSCH signal, and a first symbol sequence correlation.

[0072] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module is specifically used to:

[0073] Performing metric threshold fitting on a fifth metric normal distribution of the UCI metric when the sample PUSCH signal carries UCI under multiple sample signal-to-noise ratios, and a sixth metric normal distribution of the UCI metric when the sample PUSCH signal does not carry UCI, to determine a metric threshold corresponding to the UCI metric;

[0074] Based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0075] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module is specifically used to:

[0076] If the UCI metric is greater than the metric threshold, it is determined that the initial PUSCH signal carries the UCI;

[0077] If the UCI metric is not greater than the metric threshold, it is determined that the initial PUSCH signal does not carry UCI.

[0078] In a third aspect, the present application provides an electronic device comprising a processor and a memory, wherein the memory stores a program code, and when the program code is executed by the processor, the processor executes the steps of the UCI DTX detection method described in the first aspect above.

[0079] In a fourth aspect, the present application provides a computer-readable storage medium, which includes a program code. When the program code is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the UCI DTX detection method described in the first aspect above.

[0080] In a fifth aspect, the present application provides a computer program product, which, when called by a computer, enables the computer to execute the steps of the UCI DTX detection method as described in the first aspect.

[0081] The beneficial effects of this application are as follows:

[0082] In the DTX detection method of UCI provided in the embodiment of the present application, after obtaining the initial PUSCH signal sent by the terminal and the target PUSCH signal received by the base station, the initial PUSCH signal is reconstructed, and the amplitude information of the reconstructed PUSCH signal is removed. In this way, the UCI metric of the initial PUSCH signal is determined according to known signals such as the constant modulus PUSCH signal and the target PUSCH signal, which not only reduces the influencing factors of the UCI metric calculation, but also eliminates the influence of the non-constant modulus on the UCI metric calculation; and, the metric threshold is set corresponding to the UCI metric, avoiding the technical drawback in the related technology that the metric threshold obtained by multiple fittings is easily affected by the scene. Therefore, not only the robustness of the detection method is improved, but also the accuracy of DTX detection for UCI in the PUSCH channel is improved.

[0083] In addition, other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0085] Figure 1 A schematic diagram of PDF distribution of a metric corresponding to CSI1 provided in an embodiment of the present application;

[0086] Figure 2 A schematic diagram of a network system architecture applicable to an embodiment of the present application;

[0087] Figure 3 A schematic diagram of an implementation flow of a UCI DTX detection method provided in an embodiment of the present application;

[0088] Figure 4 A logical schematic diagram of obtaining a UCI metric of an initial PUSCH signal provided in an embodiment of the present application;

[0089] Figure 5 A logical schematic diagram of obtaining a UCI metric of an initial PUSCH signal provided in an embodiment of the present application;

[0090] Figure 6A logical schematic diagram of obtaining a UCI metric of an initial PUSCH signal provided in an embodiment of the present application;

[0091] Figure 7 A logical schematic diagram of obtaining a UCI metric of an initial PUSCH signal provided in an embodiment of the present application;

[0092] Figure 8 A schematic diagram of an implementation flow of a method for performing DTX detection of UCI on an initial PUSCH signal provided in an embodiment of the present application;

[0093] Fig. 9 A schematic diagram of a first metric normal distribution and a second metric normal distribution of an initial PUSCH signal provided in an embodiment of the present application;

[0094] Fig.10 A schematic diagram of a measured normal distribution of a sample PUSCH signal under multiple sample signal-to-noise ratios provided in an embodiment of the present application;

[0095] Fig.11 A schematic diagram of the structure of a UCI DTX detection device provided in an embodiment of the present application;

[0096] Fig.12 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0097] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the technical solution of the present application, rather than all of the embodiments. Based on the embodiments recorded in the application documents, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the technical solution of the present application.

[0098] It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone. A and B are connected, which can represent two situations: A and B are directly connected and A and B are connected through C. In addition, in the description of this application, words such as "first" and "second" are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0099] In addition, the collection, dissemination, and use of data in the technical solution of this application comply with the requirements of relevant national laws and regulations.

[0100] Some technical terms in the embodiments of the present application are explained below to facilitate understanding by those skilled in the art.

[0101] (1) LDPC code: It is a block error correction code with a sparse check matrix. It is applicable to almost all channels. Its performance is close to the Shannon limit. It is simple to describe and implement, easy to perform theoretical analysis and research, simple to decode and can be operated in parallel, and suitable for hardware implementation.

[0102] (2) Polar code: Polar code is a forward error correction coding method used for signal transmission. The core of its construction is channel polarization processing. On the coding side, a method is used to make each sub-channel present different reliability. As the code length continues to increase, some channels will tend to perfect channels with a capacity close to 1 (error-free), while other channels will tend to pure noise channels with a capacity close to 0. Information is directly transmitted on channels with a capacity close to 1 to approach the channel capacity. Therefore, it is the only method that can be strictly proven to reach the Shannon limit.

[0103] (3) Cumulative Distribution Function (CDF): Also called the distribution function, it is the integral of the PDF and can fully describe the probability distribution of a real random variable X.

[0104] (4) CSI: It is the channel property of the communication link, which describes the attenuation factor of the signal on each transmission path, that is, the value of each element in the channel gain matrix H, such as signal scattering, environmental attenuation, distance attenuation and other information. It can enable the communication system to adapt to the current channel conditions and provide a guarantee for high-reliability and high-speed communication in a multi-antenna system.

[0105] (5) Linear Minimum Mean Square Error (LMMSE) estimation: Also known as optimal linear estimation, it is a parameter estimator that has the smallest mean square error among linear estimators.

[0106] (6) Quadrature Phase Shift Keying (QPSK): It is a quaternary phase modulation with good noise immunity and bandwidth utilization. It is widely used in satellite links, digital clusters and other communication services. It is a digital modulation method.

[0107] (7) Quadrature Amplitude Modulation (QAM): It is a non-dedicated modulation method that encodes digital information on wireless, wired or optical fiber transmission links and combines amplitude and phase modulation methods. It is also an extension of polyphase shift keying. The most basic difference between the two is that QAM does not have a fixed envelope, while phase shift keying does. In addition, it has high spectrum utilization and can have any number of discrete digital levels, including: 16QAM, 64QAM and 256QAM.

[0108] Further, based on the above-mentioned nouns and related terminology explanations, the design concept of the embodiments of the present application is briefly introduced below:

[0109] In the related art, the following method is usually used to distinguish whether only a PUSCH signal is sent or a PUSCH signal carrying UCI is sent in a PUSCH channel:

[0110]

[0111] in, Indicates the DTX Metric for the PUSCH signal. It represents the variance of the distance between the constellation point after channel equalization and the distance between the reference constellation point. represents the variance in the channel equalization process, which is affected by the signal (interference) noise ratio. Represents the variance in the channel estimation process.

[0112] It should be noted that the above constellation points or constellation diagrams correspond to modulation symbols or modulation symbol sequences.

[0113] Furthermore, the threshold can be selected (i.e., the metric decision threshold or the set metric threshold), and perform UCI DTX detection on the PUSCH signal, where the threshold It is achieved by measuring (i.e. )’s PDF analysis and fitting.

[0114] For example, if but That is, the measurement result is that in the PUSCH channel, only the PUSCH signal is sent, and no UCI is carried; on the contrary, if but That is, a PUSCH signal carrying UCI is sent in the PUSCH channel.

[0115] Based on the above The calculation method of Figure 1It is not difficult to find that the current DTX detection of UCI in the PUSCH channel is due to the measurement and metric decision threshold Affected by the scene (ie, there are many influencing factors on the measurement and measurement decision threshold), the robustness is low.

[0116] In view of this, in an embodiment of the present application, in order to improve the robustness of the UCI DTX detection method and improve the accuracy of UCI DTX detection in the PUSCH channel, a UCI DTX detection method is proposed, which specifically includes: respectively obtaining an initial PUSCH signal sent by the terminal and a target PUSCH signal received by the base station; wherein the target PUSCH signal is obtained after channel equalization processing is performed on the initial PUSCH signal; then, the initial PUSCH signal is reconstructed to obtain a reconstructed PUSCH signal, and the reconstructed PUSCH signal is subjected to amplitude information removal processing to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal; further, based on the modulation symbol sequence contained in the target PUSCH signal and the constant modulus PUSCH signal, respectively, a UCI metric of the initial PUSCH signal is obtained; finally, based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the initial PUSCH signal is subjected to UCI DTX detection.

[0117] In particular, the preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application, and the embodiments of the present application and the features in the embodiments may be combined with each other if there is no conflict.

[0118] See also Figure 2 As shown, it is a schematic diagram of a network system architecture applicable to an embodiment of the present application, and the system architecture includes: a terminal 201, a base station 202, and a server 203. The terminal 201, the base station 202, and the server 203 can all exchange information through a communication network, wherein the communication mode adopted by the communication network may include: a wireless communication mode and a wired communication mode.

[0119] Exemplarily, the server 203 can access the network through cellular mobile communication technology, and communicate with the terminal 201 and the base station 202 respectively, wherein the cellular mobile communication technology, for example, includes 5G technology.

[0120] Optionally, the server 203 may access the network via short-range wireless communication to communicate with the terminal 201 and the base station 202 respectively, wherein the short-range wireless communication method, for example, includes Wireless Fidelity (English: Wireless Fidelity, abbreviated: Wi-Fi) technology.

[0121] The embodiment of the present application does not impose any restriction on the number of communication devices involved in the above application scenario. For example, there may be multiple terminals 201 and / or multiple base stations 202, or there may be no terminal 201 and / or base station 202, or other network devices may be included, such as Figure 2 As shown, only the terminal 201, the base station 202 and the server 203 are described as examples, and the above devices and their respective functions are briefly introduced below.

[0122] Terminal 201 is a device that can provide voice and / or data connectivity to users, and can be a device that supports wired and / or wireless connection modes, that is, it can be a wireless terminal or a wired terminal.

[0123] Among them, the wireless terminal may refer to a communication device that provides voice services and / or data services, a handheld device with wireless connection function, a wearable device or other processing device connected to a wireless modem; and the wireless terminal can communicate with one or more core networks via a radio access network (English: Radio Access Network, abbreviated: RAN), and the wireless terminal may be a mobile terminal, such as a mobile phone (or called a "cellular" phone) and a computer with a mobile terminal.

[0124] Exemplary, wireless terminals include, but are not limited to: mobile phones, tablet computers, laptop computers, PDAs, mobile Internet devices (English: Mobile Internet Device, abbreviated: MID), wearable devices, virtual reality (English: Virtual Reality, abbreviated: VR) devices, augmented reality (English: Augmented Reality, abbreviated: AR) devices, wireless terminal devices in industrial control, wireless terminal devices in unmanned driving, wireless terminal devices in smart grids, wireless terminal devices in transportation safety, wireless terminal devices in smart cities, or wireless terminal devices in smart homes, etc.

[0125] Base station 202 may be a device in an access network that communicates with a wireless terminal on an air interface through one or more sectors. It may be used to convert received air frames into and from Internet Protocol (IP) packets, and serve as a router between the wireless terminal and the rest of the access network, wherein the rest of the access network may include an IP network.

[0126] In addition, the base station 202 can also coordinate the attribute management of the air interface. Therefore, the base station 202 can be a base station in each generation of mobile communication systems (such as a 5G base station), and in the embodiments of the present application, there is no specific limitation on the type of base station.

[0127] Exemplarily, the base station 202 can be a macro base station (Macro eNB, MeNB), a remote radio head (RRH), a micro / small base station (Pico eNodeB, Pico eNB), a home base station (Home eNodeB, HeNB), a relay device (RN), an access point (AP), etc.

[0128] It should be noted that there are multiple channels between the terminal 201 and the base station 202, which can be divided into uplink logical channels and downlink logical channels; among them, the uplink logical channel is the channel through which the terminal 201 sends signals and the base station 202 receives signals, and the downlink logical channel is the channel through which the base station 202 sends signals and the terminal 201 receives signals.

[0129] Specifically, the uplink logical channel includes: a transmission channel and a physical channel. The transmission channel refers to a digital transmission path from the terminal 201 to the base station 202, which is used to transmit user data and signaling. The physical channel refers to a radio wave transmission path, which is used to transmit a bit stream.

[0130] In the uplink logical channel, there are three types of transmission channels: random access channel, paging channel and shared control channel. The random access channel is used for terminal 201 to request connection to base station 202, the paging channel is used for base station 202 to send control signaling to terminal 201, and the shared control channel is used to exchange control information between terminal 201 and base station 202; there are also three types of physical channels: main lobe channel, side lobe channel and pilot channel. The main lobe channel is used to transmit user data and signaling, the side lobe channel is used to transmit auxiliary information, and the pilot channel is used to provide reference signals to help base station 202 lock the signal source. Exemplarily, physical channels include but are not limited to: PUSCH and PUCCH.

[0131] Server 203 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (English: Content Delivery Network, abbreviation: CDN), as well as big data and artificial intelligence platforms.

[0132] It is worth mentioning that in the embodiment of the present application, the server 203 is used to respectively obtain the initial PUSCH signal sent by the terminal 201 and the target PUSCH signal received by the base station 202, and then reconstruct the initial PUSCH signal to obtain the reconstructed PUSCH signal, and perform amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal, thereby obtaining a UCI measurement of the initial PUSCH signal based on the modulation symbol sequence contained in the target PUSCH signal and the constant modulus PUSCH signal, and then based on the obtained UCI measurement and the measurement threshold set for the corresponding UCI measurement, the initial PUSCH signal is subjected to UCI DTX detection.

[0133] The following describes the UCI DTX detection method provided by the exemplary embodiment of the present application in combination with the above-mentioned system architecture and with reference to the accompanying drawings. It should be noted that the above-mentioned system architecture is only shown to facilitate understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this regard.

[0134] See also Figure 3 As shown, it is a schematic diagram of an implementation process of a UCI DTX detection method provided in an embodiment of the present application. The execution subject takes a server as an example. The specific implementation process of the method is as follows:

[0135] S301: Acquire an initial PUSCH signal sent by a terminal and a target PUSCH signal received by a base station respectively.

[0136] The target PUSCH signal is obtained after performing channel equalization processing on the initial PUSCH signal.

[0137] It should be noted that when the base station receives the target PUSCH signal, the receiver algorithm generally uses LMMSE frequency domain channel estimation. However, LMMSE channel estimation is a biased estimation and needs to be corrected according to the bias factor. The bias factor of LMMSE channel estimation is a function of SNR, and SNR estimation often has deviations, especially at low SNR. The deviation is greater, which causes the constellation point symbols after equalization to always have a deviation (i.e., bias), resulting in inaccuracy.

[0138] Exemplarily, assuming that the channel estimation and equalization algorithms are correct, the constellation symbols received by the base station satisfy the following formula:

[0139] Y EQ =ξ·S+N

[0140] That is, each subcarrier is:

[0141] Y EQ(k) = ξ·S(k) + n(k)

[0142] Among them, S(k) is the transmitted modulation symbol at time k, Y EQ (k) is the constellation point symbol after receiver equalization, n(k) is the noise, and ξ is the deviation caused by the bias of LMMSE estimation (if unbiased estimation is used, such as zero forcing (ZF) equalization, then ξ=1).

[0143] It should be noted that the above S = (s(0), s(1), ..., s(N-1)) is the modulation symbol sequence contained in the initial PUSCH signal, that is, the real constellation point signal. EQ It is the modulation symbol sequence contained in the target PUSCH signal, that is, the constellation point signal after equalization by the base station (receiver).

[0144] S302: reconstructing the initial PUSCH signal to obtain a reconstructed PUSCH signal, and performing amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal.

[0145] The reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal, that is, the real part is the same and the imaginary part is opposite.

[0146] Exemplarily, assuming that the modulation symbol sequence included in the initial PUSCH signal is represented by S, the modulation symbol sequence included in the reconstructed PUSCH signal is represented by S H , that is, when the modulation symbol contained in the initial PUSCH signal on the subcarrier is s(k), the modulation symbol contained in the reconstructed PUSCH signal is s * (k).

[0147] Furthermore, the modulation symbol sequence contained in the constant modulus PUSCH signal can be expressed as in,

[0148] can also be It is considered as constant modulus processing of the modulation symbol sequence S contained in the initial PUSCH signal.

[0149] S303: Obtain a UCI metric of the initial PUSCH signal based on the modulation symbol sequences respectively included in the target PUSCH signal and the constant modulus PUSCH signal.

[0150] It should be noted that in the embodiment of the present application, the calculation method of the UCI measurement based on the initial PUSCH signal effectively avoids the additional changes in the UCI measurement caused by various situations (such as different modulation modes and different bit probabilities) in the related technology due to the non-constant modulus of the PUSCH signal.

[0151] Exemplarily, in the related art, the target PUSCH signal and the reconstructed PUSCH signal are directly correlated and calculated, and the specific formula can be expressed as follows:

[0152]

[0153] From the above formula, we can see that the correlation operation result is determined by assuming that the channel equalization and channel estimation are correct. and a random process associated with the noise It consists of two parts.

[0154] However, since the constellations of other QAM modulations except QPSK are not constant modulus, that is, |s(k)| 2 is not constant, then, The noise scaling at different amplitudes at the constellation points of each UCI modulation symbol is different, and the constellation points of different modulation symbols in UCI multiplexing are not necessarily consistent. Therefore, the original Gaussian distribution n(k) after equalization is distorted to a certain extent, and the calculation of its statistical characteristics will become more complex, non-Gaussian and non-robust.

[0155] Therefore, in the embodiment of the present application, the method of obtaining the UCI measurement of the initial PUSCH signal based on the modulation symbol sequence contained in the target PUSCH signal and the constant modulus PUSCH signal eliminates the additional changes in various situations caused by the non-constant modulus of the PUSCH signal to the UCI measurement.

[0156] In an alternative implementation, see Figure 4 As shown, when executing step S303, after the server obtains the constant modulus PUSCH signal, it can determine the first symbol sequence correlation between the target PUSCH signal and the constant modulus PUSCH signal based on the modulation symbol sequence included in the target PUSCH signal and the modulation symbol sequence included in the constant modulus PUSCH signal, thereby obtaining the UCI measurement of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal; in this way, the UCI measurement of the initial PUSCH signal can be obtained only based on the known and determined PUSCH signal.

[0157] Exemplarily, the correlation of the first symbol sequence can be expressed as:

[0158]

[0159] Wherein, angle(s(k)) represents the phase of the modulation symbol at time k in the initial PUSCH signal.

[0160] In particular, when the server obtains the UCI metric of the initial PUSCH signal based on the correlation of the first symbol sequence and the modulation symbol sequence included in the initial PUSCH signal, the server may specifically adopt the following three methods:

[0161] Method A: See Figure 5 As shown, after the server obtains the biased estimation deviation between the initial PUSCH signal and the target PUSCH signal, it can obtain the UCI metric of the initial PUSCH signal based on the biased estimation deviation, the correlation of the first symbol sequence and the modulation symbol sequence included in the initial PUSCH signal.

[0162] The biased estimation deviation represents: the signal transmission quality of the frequency domain channel that transmits the initial PUSCH signal, for example, the biased estimation deviation is the deviation ξ caused by the bias of the LMMSE estimation.

[0163] Obviously, in the calculation process of the UCI metric, the biased estimation deviation (usually a fixed value) between the initial PUSCH signal and the target PUSCH signal, that is, the system deviation, is taken into account, which affects the accuracy of the UCI metric calculation. Therefore, this method not only improves the robustness of the detection method, but also ensures the accuracy of the UCI metric calculation to a certain extent.

[0164] Exemplarily, the server obtains the calculation formula of the UCI metric of the initial PUSCH signal based on mode A as follows:

[0165]

[0166] Wherein, Corr represents the UCI metric of the initial PUSCH signal, represents the correlation of the first symbol sequence, ξ represents the biased estimation deviation, It represents the sum of the amplitudes of each modulation symbol in the modulation symbol sequence contained in the initial PUSCH signal.

[0167] Optionally, since ξ is a variable that needs to be calculated, the denominator can be omitted (the value of ξ is actually very close to 1, so it is replaced by 1 when used to find the probabilistic threshold, which generally has little impact on performance). The UCI metric obtained by removing ξ when sending UCI and when not sending UCI can be expressed as follows:

[0168]

[0169] Wherein, Corr represents the UCI metric of the initial PUSCH signal, represents the correlation of the first symbol sequence, ξ represents the biased estimation deviation, It represents the sum of the amplitudes of each modulation symbol in the modulation symbol sequence contained in the initial PUSCH signal.

[0170] Method B: See Figure 6 As shown, the server can determine the second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal based on the modulation symbol sequence contained in the target PUSCH signal and the modulation symbol sequence contained in the reconstructed PUSCH signal, thereby obtaining the UCI measurement of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence contained in the initial PUSCH signal, as well as the second symbol sequence correlation.

[0171] Obviously, the above method B is an optimization based on method A, that is, on the basis of method A, the decoupling of the biased estimation deviation ξ or the signal-to-noise ratio SNR is achieved.

[0172] Exemplarily, the server obtains the calculation formula of the UCI metric of the initial PUSCH signal based on mode B as follows:

[0173]

[0174] Among them, real() means taking the real part operation, represents the correlation of the first symbol sequence, Y EQ ·S H represents the correlation of the second symbol sequence, Indicates the square sum of the amplitudes of each modulation symbol in the modulation symbol sequence contained in the initial PUSCH signal. It represents the sum of the amplitudes of each modulation symbol in the modulation symbol sequence contained in the initial PUSCH signal.

[0175] It can be seen that in the process of calculating the UCI metric, by constructing the second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal, the UCI metric of the initial PUSCH signal is obtained only based on the first symbol sequence correlation and the modulation symbol sequence contained in the initial PUSCH signal, as well as the second symbol sequence correlation, thereby eliminating the influence of the biased estimation deviation related to noise on the UCI metric calculation, thereby further improving the robustness of the detection method.

[0176] Method C: See Figure 7As shown, the server can obtain the target signal-to-noise ratio based on the modulation symbol sequence contained in the initial PUSCH signal and the noise symbol sequence contained in the target PUSCH signal, and thereby obtain the UCI measurement of the initial PUSCH signal based on the biased estimation deviation and the target signal-to-noise ratio between the initial PUSCH signal and the target PUSCH signal, and the correlation of the first symbol sequence.

[0177] Exemplarily, the server obtains the calculation formula of the UCI metric of the initial PUSCH signal based on mode C in the following manner:

[0178] Due to the above Y EQ =ξ·S+N or Y EQ (k) = ξ·S(k) + n(k), and according to the physical meaning of the signal-to-noise ratio, we have:

[0179]

[0180] Among them, SNR represents the target signal-to-noise ratio, Indicates the square sum of the amplitudes of each modulation symbol in the modulation symbol sequence contained in the initial PUSCH signal. represents the square sum of the amplitudes of the noise symbols in the noise symbol sequence contained in the initial PUSCH signal, s(k) represents the modulation symbol at time k in the modulation symbol sequence contained in the initial PUSCH signal, and Y EQ (k) represents the modulation symbol at time k in the modulation symbol sequence included in the target PUSCH signal, and ξ represents the biased estimation deviation between the initial PUSCH signal and the target PUSCH signal.

[0181] Furthermore, due to

[0182]

[0183] Therefore, the UCI metric of the initial PUSCH signal can be constructed according to the biased estimation deviation and the target signal-to-noise ratio. The specific calculation formula can be expressed as follows:

[0184]

[0185] Wherein, Metric represents the UCI metric of the initial PUSCH signal.

[0186] Furthermore, when N is large enough, It is approximately equal to 1, so the calculation formula of the above UCI metric can be expressed as follows:

[0187]

[0188] Optionally, the above relationship can also be used:

[0189]

[0190] Also, since the phase of the equalized Gaussian noise n(k) satisfies the uniform distribution between [0,2π], n(k)·e -i·angle(s(k)) The phase of still satisfies the uniform distribution between [0,2π], and n(k)·e -i·angle(s(k)) The magnitude of n(k) remains the same and unchanged, so n(k)·e -i·angle(s(k)) It still satisfies the Gaussian distribution, and the expectation is 0. Obviously, when N is large enough, the second term of the above formula approaches 0, then:

[0191]

[0192] It should be noted that Indicates the modulation symbols contained in the constant modulus PUSCH signal at time k.

[0193] The above UCI metric can be further simplified (i.e., the UCI metric obtained according to the biased estimation deviation and the target signal-to-noise ratio is optimized according to the first symbol sequence correlation), and its calculation formula is expressed as follows:

[0194]

[0195] Based on the above-mentioned method C, since the biased estimation deviation is related to the noise, the UCI measurement in the sense of the signal-to-noise ratio can be obtained according to the biased estimation deviation and the target signal-to-noise ratio, as well as the correlation of the first symbol sequence. Moreover, the UCI measurement in the sense of the signal-to-noise ratio is only related to two known and determined symbol sequences, namely the modulation symbol sequence contained in the target PUSCH signal and the modulation symbol sequence contained in the initial PUSCH signal, thereby improving the robustness of the detection method.

[0196] S304: Based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, perform UCI DTX detection on the initial PUSCH signal.

[0197] Specifically, when executing step S304, after obtaining the UCI measurement of the initial PUSCH signal, the server can perform UCI DTX detection on the initial PUSCH signal according to the UCI measurement and the measurement threshold determined by the calculation method of the corresponding UCI measurement (i.e., the measurement threshold set corresponding to the UCI measurement).

[0198] Case 1: If the server obtains the UCI metric based on the above method A, then refer to Figure 8 As shown, the metric threshold is obtained in the following manner, and the UCI DTX detection of the initial PUSCH signal is performed according to the obtained metric threshold and the UCI metric:

[0199] S801: respectively determining a first correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI, and a second correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI.

[0200] Exemplarily, the calculation formula of the correlation of the first symbol sequence is:

[0201]

[0202] Moreover, since the phase of the equalized Gaussian noise n(k) satisfies the uniform distribution between [0,2π], and each modulation symbol (constellation point) s(k) of the reconstructed UCI sequence is a fixed value, n(k)·e -i·angle(s(k)) The phase of still satisfies the uniform distribution between [0,2π], and n(k)·e -i·angle(s(k)) The magnitude of n(k) remains the same and unchanged, so n(k)·e -i·angle(s(k)) It still satisfies the Gaussian distribution, and the expectation is 0. The variance remains unchanged compared to n(k). According to the law of normal distribution, The variance of is N times the variance of n(k), that is, the result of the correlation operation Corr under the condition of sending the UCI with the road TxUCI The normal distribution is:

[0203]

[0204] Obviously, the above Corr TxUCI The normal distribution of ˜N is the first correlation normal distribution that the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI.

[0205] Similarly, the result of the correlation operation without UCI is Corr NoUCI The normal distribution is

[0206]

[0207] The above Corr NoUCI The normal distribution of ˜N is the second correlation normal distribution that the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI.

[0208] S802: Perform amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution respectively to obtain a first metric normal distribution of UCI metric when the initial PUSCH signal carries UCI, and a second metric normal distribution of UCI metric when the initial PUSCH signal does not carry UCI.

[0209] It should be noted that since S is a deterministic signal, when UCI is sent along the channel, the expectation of the correlation operation metric is determined under a certain reconstructed local sequence, but it is related to the normalized scaling factor ξ of the constellation diagram after equalization of the receiving algorithm. When ξ is known, its normalized standard probability distribution is:

[0210]

[0211] However, in order to improve the robustness of the DTX detection method of UCI, the specific value of the variance is usually not of concern, but the variance of the UCI sent and the UCI not sent is preferably symmetrical, and the absolute value is preferably expected; for example, see Fig. 9 As shown, the expected distance to 0.5 of UCI sent and UCI not sent is the same and the variance is the same, that is, the normal distribution of the two correlations of UCI sent and UCI not sent is symmetric about 0.5.

[0212] Therefore, the server can normalize both sides with the sum of the amplitude moduli, that is, normalize the amplitude information, and then:

[0213]

[0214] Therefore, when executing step S802, the server performs amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution, respectively, to obtain a first metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a second metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI, which can be specifically expressed as follows:

[0215]

[0216]

[0217] Among them, Corr TxUCI ~N represents the first metric normal distribution, Corr NoUCI ~N represents the second metric normal distribution.

[0218] Optionally, as mentioned above, ξ is a variable that needs to be calculated, and the denominator can be omitted. Therefore, the Gaussian distribution (i.e., the first metric normal distribution and the second metric normal distribution) of the UCI metric obtained by removing ξ when UCI is issued and when UCI is not issued is:

[0219]

[0220]

[0221] S803: Determine a metric threshold corresponding to the UCI metric based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution, and perform UCI DTX detection on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0222] Specifically, when executing step S803, after obtaining the first metric normal distribution and the second metric normal distribution, the server may determine a metric threshold corresponding to the UCI metric based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution.

[0223] Exemplarily, if the first metric normal distribution and the second metric normal distribution are:

[0224]

[0225]

[0226] It can be seen that according to the first metric expectation 1 in the first metric normal distribution and the second metric expectation 0 in the second metric normal distribution, the metric threshold corresponding to the UCI metric is 0.5, that is, the average of the first metric expectation and the second metric expectation is used as the metric threshold corresponding to the UCI metric.

[0227] For another example, if the first metric normal distribution and the second metric normal distribution are:

[0228]

[0229]

[0230] It can be seen that according to the first metric expectation ξ in the first metric normal distribution and the second metric expectation 0 in the second metric normal distribution, the metric threshold corresponding to the UCI metric is

[0231] Therefore, after determining the metric threshold corresponding to the UCI metric, the server can perform UCI DTX detection on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0232] Obviously, based on the UCI metric calculation method of the above-mentioned method A and the corresponding UCI DTX detection method steps, the amplitude information of the initial PUSCH signal can be removed, and only the constant modulus phase is retained to obtain a transverse mode PUSCH signal with a constant modulus of 1; then, the UCI metric of the initial PUSCH signal is calculated by performing a correlation operation (conjugate multiplication) between the equalized target PUSCH signal and the transverse mode PUSCH signal, and combining the biased estimation deviation between the initial PUSCH signal and the target PUSCH signal; further, the initial PUSCH signal modulation symbol sequence (the sum of the moduli at each moment) is used for normalization, and the metric threshold corresponding to the UCI metric is determined according to the first metric normal distribution and the second metric normal distribution of the UCI metric; finally, according to the obtained UCI metric and the threshold (i.e., metric threshold) 0.5 obtained by removing ξ, or, more accurately, the threshold calculated by the threshold analytical expression obtained by the accurate analytical expression of ξ, i.e., (metric threshold) Perform a size comparison to determine whether the currently detected initial PUSCH signal has sent UCI or not.

[0233] Therefore, since the first metric expectation in the first metric normal distribution and the second metric expectation in the second metric normal distribution are both fixed values, the obtained metric threshold is also a fixed value (a constant or a fixed value related to the biased estimation deviation), that is, the metric threshold is basically not affected by the scene. Therefore, the robustness of the detection method is improved to a certain extent.

[0234] Case 2: If the server obtains the UCI metric based on the above method B, the metric threshold can be obtained in the following manner, and the UCI DTX detection of the initial PUSCH signal can be performed according to the obtained metric threshold and UCI metric:

[0235] It should be noted that, based on the derivation process of the calculation formula for obtaining the UCI metric of the initial PUSCH signal in mode B, the third metric normal distribution of the UCI metric when the initial PUSCH signal carries UCI and the fourth metric normal distribution of the UCI metric when the initial PUSCH signal does not carry UCI can be determined respectively, as follows:

[0236] Method A ensures that the normal distribution (Gaussian distribution) of the noise term after the mathematical transformation of the related operation of the metric is maintained, and the threshold of the threshold decision is made robust by the absolute value through normalization. However, the probability distribution of this designed metric with or without the UCI associated signal is still a function of the constellation scaling factor (i.e., the biased estimation deviation ξ). Therefore, in order to further decouple the designed metric and decision threshold from the constellation scaling factor ξ and further improve the detection performance, further optimization and design based on method A are required.

[0237] The analytical expression of the designed metric (i.e., the correlation of the first symbol sequence) without amplitude normalization is as follows:

[0238]

[0239] As mentioned above, since the phase of the equalized Gaussian noise n(k) satisfies the uniform distribution between [0 2π], and each modulation symbol (constellation point) s(k) of the reconstructed UCI sequence is a fixed value, n(k)·e -i·angle(s(k)) The phase of still satisfies the uniform distribution between [0 2π], and n(k)·e -i·angle(s(k)) The magnitude of n(k) remains the same and unchanged, so n(k)·e -i·angle(s(k)) It still satisfies the Gaussian distribution, and the expectation is 0, and the variance remains unchanged compared to n(k).

[0240] Therefore, the expectation of the entire above formula is a real number, and the above formula can be optimized as follows:

[0241]

[0242] So there is

[0243]

[0244] In addition, the above formula is an approximate equality after all, and because

[0245] Y EQ =ξ·S+N

[0246] That is, each subcarrier is

[0247] Y EQ (k) = ξ·S(k) + n(k)

[0248] but

[0249]

[0250] When N is large enough, although s(k) has different amplitudes, because s(k) is unrelated to n(k), in the above formula will approach approximately 0.

[0251] So, if Then we have:

[0252]

[0253] Therefore, the measurement and calculation of the scaling factor (biased estimation deviation ξ) depends on the estimation accuracy of the SNR, and the correlation of the second symbol sequence

[0254]

[0255] When N is large enough, although s(k) has different amplitudes, because s(k) is unrelated to n(k), the above formula When N is large enough, it approaches approximately 0.

[0256] Therefore, when a UCI associated signal is sent (i.e., an initial PUSCH signal carrying UCI is sent),

[0257]

[0258] Therefore, we can also try to normalize it with the above formula. Substituting the above formula into the previous formula (i.e., the calculation formulas of the first correlation normal distribution and the second correlation normal distribution), the Gaussian distributions satisfied by the metrics with and without UCI are respectively

[0259]

[0260] However, when no UCI associated signal is sent (i.e., an initial PUSCH signal without UCI is sent), the (constellation diagram) scaling factor does not satisfy the above formula, so the relevant operation is modified as follows:

[0261]

[0262] Among them, Corr TxUCI ~N represents the third metric normal distribution, Corr NoUCI ~N represents the fourth metric normal distribution.

[0263] Of course, for QPSK, This factor needs to be calculated in advance for other QAM modulation methods. In addition, considering the statistical characteristics, the metric can be further optimized as follows:

[0264]

[0265]

[0266] Among them, Corr TxUCI ~N represents the third metric normal distribution, Corr NoUCI ~N represents the fourth metric normal distribution.

[0267] That is, the UCI metric corresponding to method B is:

[0268]

[0269] Based on the above method, after obtaining the third metric normal distribution and the fourth metric normal distribution, the server can determine the metric threshold corresponding to the UCI metric based on the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution.

[0270] Exemplarily, no matter which of the two the third metric normal distribution and the fourth metric normal distribution are, it can be known that: the third metric expectation in the third metric normal distribution is 1 and the fourth metric expectation in the fourth metric normal distribution is 0, and the metric threshold corresponding to the UCI metric is 0.5, that is, the average of the third metric expectation and the fourth metric expectation is used as the metric threshold corresponding to the UCI metric.

[0271] Obviously, since the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution are both fixed values, the obtained metric threshold is also a fixed value (a constant or a fixed value related to the biased estimation deviation), that is, the obtained metric threshold is basically not affected by the scene, thereby improving the robustness of the detection method.

[0272] Further, after determining the metric threshold corresponding to the UCI metric, the server may perform UCI DTX detection on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0273] Case 3: If the server obtains the UCI metric based on the above method C, then refer to Fig.10 As shown, the fifth metric normal distribution of the UCI metric when the sample PUSCH signal carries UCI under multiple sample signal-to-noise ratios, and the sixth metric normal distribution of the UCI metric when the sample PUSCH signal does not carry UCI are fitted with a metric threshold, and the metric threshold corresponding to the UCI metric is determined, so as to perform UCI DTX detection on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0274] In this way, by Fig.10 From the normal distribution of each metric in (i.e., the integral CDF of PDF), we can see that: the area of ​​UCI metric corresponding to not sending UCI represented by the dotted line is actually very small, that is, the corresponding PDF integral area divided by the PDF integral area for sending UCI (i.e., DCF) is also very small (i.e., the PDF overlap of UCI metric is small when the PUSCH signal carries UCI and does not carry UCI). Therefore, it is easy to find a robust absolute threshold (i.e., metric threshold) that adapts to each SNR, cut the integral area of ​​PDF, and obtain robust and good false alarm and missed alarm performance, that is, the fitting difficulty is low, and the obtained metric threshold effect is good. For example, Fig.10 As shown, it is sufficient to set the detection threshold (ie, measurement threshold) to 1.

[0275] In an optional implementation, when executing step S304, the server can complete the DTX detection of the UCI of the initial PUSCH signal by judging the size relationship between the UCI metric and the metric threshold, that is, if the UCI metric is greater than the metric threshold, it is determined that the initial PUSCH signal carries the UCI; conversely, if the UCI metric is not greater than the metric threshold, it is determined that the initial PUSCH signal does not carry the UCI.

[0276] In summary, in the DTX detection method of UCI provided in the embodiment of the present application, after obtaining the initial PUSCH signal sent by the terminal and the target PUSCH signal received by the base station, the initial PUSCH signal is reconstructed, and the reconstructed PUSCH signal is subjected to amplitude information removal processing. In this way, the UCI metric of the initial PUSCH signal is determined according to known signals such as the constant modulus PUSCH signal and the target PUSCH signal, which not only reduces the influencing factors of the UCI metric calculation, but also eliminates the influence of the non-constant modulus on the UCI metric calculation; and, the metric threshold is set corresponding to the UCI metric, which avoids the technical drawback in the related technology that the metric threshold obtained by multiple fittings is extremely susceptible to the influence of the scene. Therefore, not only the robustness of the detection method is improved, but also the accuracy of DTX detection for UCI in the PUSCH channel is improved.

[0277] Further, based on the same technical concept, the embodiment of the present application provides a UCI DTX detection device, and the UCI DTX detection device is used to implement the above method flow of the embodiment of the present application. Fig.11 As shown, the UCI DTX detection device includes: a signal acquisition module 1101, a signal processing module 1102, a metric calculation module 1103 and a signal detection module 1104, wherein:

[0278] The signal acquisition module 1101 is used to respectively acquire an initial physical uplink shared channel PUSCH signal sent by the terminal and a target PUSCH signal received by the base station; wherein the target PUSCH signal is obtained after performing channel equalization processing on the initial PUSCH signal;

[0279] The signal processing module 1102 is used to reconstruct the initial PUSCH signal to obtain a reconstructed PUSCH signal, and perform amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal;

[0280] The metric calculation module 1103 is used to obtain the UCI metric of the initial PUSCH signal based on the modulation symbol sequence respectively included in the target PUSCH signal and the constant modulus PUSCH signal;

[0281] The signal detection module 1104 is configured to perform UCI DTX detection on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric.

[0282] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the modulation symbol sequences respectively included in the target PUSCH signal and the constant modulus PUSCH signal, the metric calculation module 1103 is specifically used to:

[0283] Determine a first symbol sequence correlation between the target PUSCH signal and the constant modulus PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the constant modulus PUSCH signal;

[0284] A UCI metric of the initial PUSCH signal is obtained based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal.

[0285] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module 1103 is specifically used to:

[0286] Obtaining a biased estimation deviation between an initial PUSCH signal and a target PUSCH signal; wherein the biased estimation deviation represents: a signal transmission quality of a frequency domain channel transmitting the initial PUSCH signal;

[0287] A UCI metric of the initial PUSCH signal is obtained based on the biased estimation deviation, the correlation of the first symbol sequence, and a modulation symbol sequence included in the initial PUSCH signal.

[0288] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module 1104 is specifically used to:

[0289] respectively determining a first correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI, and a second correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI;

[0290] Perform amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution respectively to obtain a first metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a second metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0291] A metric threshold corresponding to the UCI metric is determined based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution, and a UCI DTX detection is performed on the initial PUSCH signal based on the UCI metric and the metric threshold.

[0292] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module 1103 is specifically used to:

[0293] Determine a second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the reconstructed PUSCH signal;

[0294] Based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, and the second symbol sequence correlation, a UCI metric of the initial PUSCH signal is obtained.

[0295] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module 1104 is specifically used to:

[0296] Determine respectively a third metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a fourth metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI;

[0297] Based on the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution, a metric threshold corresponding to the UCI metric is determined, and based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0298] In an optional embodiment, when obtaining the UCI metric of the initial PUSCH signal based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, the metric calculation module 1103 is specifically used to:

[0299] Obtaining a target signal-to-noise ratio based on a modulation symbol sequence included in the initial PUSCH signal and a noise symbol sequence included in the target PUSCH signal;

[0300] A UCI metric of the initial PUSCH signal is obtained based on a biased estimation deviation and a target signal-to-noise ratio between the initial PUSCH signal and the target PUSCH signal, and a first symbol sequence correlation.

[0301] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module 1104 is specifically used to:

[0302] Performing metric threshold fitting on a fifth metric normal distribution of the UCI metric when the sample PUSCH signal carries UCI under multiple sample signal-to-noise ratios, and a sixth metric normal distribution of the UCI metric when the sample PUSCH signal does not carry UCI, to determine a metric threshold corresponding to the UCI metric;

[0303] Based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

[0304] In an optional embodiment, when performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and the metric threshold set corresponding to the UCI metric, the signal detection module 1104 is specifically used to:

[0305] If the UCI metric is greater than the metric threshold, it is determined that the initial PUSCH signal carries the UCI;

[0306] If the UCI metric is not greater than the metric threshold, it is determined that the initial PUSCH signal does not carry UCI.

[0307] Based on the same technical concept, the embodiment of the present application also provides an electronic device, which can implement the UCI DTX detection method flow provided in the above embodiment of the present application. In one embodiment, the electronic device can be a server, or a terminal device or other electronic device. Fig.12 As shown, the electronic device may include:

[0308] At least one processor 1201, and a memory 1202 connected to the at least one processor 1201. The specific connection medium between the processor 1201 and the memory 1202 is not limited in the embodiment of the present application. Fig.12 In the example, the processor 1201 and the memory 1202 are connected via the bus 1200. The bus 1200 is Fig.12 The connections between other components are shown in bold lines, and are not intended to be limiting. The bus 1200 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.12 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 1201 can also be called a controller, and there is no limitation on the name.

[0309] In the embodiment of the present application, the memory 1202 stores instructions that can be executed by at least one processor 1201. The at least one processor 1201 can execute a UCI DTX detection method discussed above by executing the instructions stored in the memory 1202. The processor 1201 can implement Fig.11 The functions of each module in the device shown.

[0310] Among them, the processor 1201 is the control center of the device, which can use various interfaces and lines to connect the various parts of the entire control device, and monitor the device as a whole by running or executing instructions stored in the memory 1202 and calling the data stored in the memory 1202, the various functions of the device and processing data.

[0311] In one possible design, the processor 1201 may include one or more processing units, and the processor 1201 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 1201. In some embodiments, the processor 1201 and the memory 1202 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0312] The processor 1201 may be a general-purpose processor, such as a CPU, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of a UCI DTX detection method disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0313] The memory 1202 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 1202 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (English: Random Access Memory, abbreviated: RAM), a static random access memory (English: Static Random Access Memory, abbreviated: SRAM), a programmable read-only memory (English: Programmable Read Only Memory, abbreviated: PROM), a read-only memory (English: Read Only Memory, abbreviated: ROM), an electrically erasable programmable read-only memory (English: Electrically Erasable Programmable Read-Only Memory, abbreviated: EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 1202 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 1202 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0314] By designing and programming the processor 1201, the code corresponding to the DTX detection method of a UCI introduced in the above embodiment can be fixed into the chip, so that the chip can execute it when running. Figure 3 The steps of a UCI DTX detection method in the embodiment shown are as follows: How to design and program the processor 1201 is a technology well known to those skilled in the art and will not be described in detail here.

[0315] Based on the same inventive concept, an embodiment of the present application further provides a storage medium, which stores computer instructions. When the computer instructions are executed on a computer, the computer executes a UCI DTX detection method discussed above.

[0316] In some possible implementations, the present application also provides various aspects of a UCI DTX detection method, which can also be implemented in the form of a program product, which includes a program code. When the program product is run on an apparatus, the program code is used to enable the control device to execute the steps of a UCI DTX detection method according to various exemplary implementations of the present application described above in this specification.

[0317] It should be noted that, although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided into multiple units to be embodied.

[0318] In addition, although the operations of the method of the present application are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0319] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0320] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a server, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0321] Program code for performing the operations of the present application may be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0322] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0323] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for detecting discontinuous transmission (DTX) of uplink control information (UCI), characterized in that: include: Respectively acquiring an initial physical uplink shared channel PUSCH signal sent by the terminal and a target PUSCH signal received by the base station; wherein the target PUSCH signal is obtained after performing channel equalization processing on the initial PUSCH signal; Reconstructing the initial PUSCH signal to obtain a reconstructed PUSCH signal, and performing amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal; Obtaining a UCI metric of the initial PUSCH signal based on a modulation symbol sequence respectively included in the target PUSCH signal and the constant modulus PUSCH signal; Based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric, DTX detection of UCI is performed on the initial PUSCH signal.

2. The method according to claim 1, characterized in that The obtaining, based on the modulation symbol sequences respectively included in the target PUSCH signal and the constant modulus PUSCH signal, the UCI metric of the initial PUSCH signal comprises: Determine a first symbol sequence correlation between the target PUSCH signal and the constant modulus PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the constant modulus PUSCH signal; A UCI metric of the initial PUSCH signal is obtained based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal.

3. The method according to claim 2, characterized in that The obtaining, based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, a UCI metric of the initial PUSCH signal includes: Obtaining a biased estimation deviation between the initial PUSCH signal and the target PUSCH signal; wherein the biased estimation deviation represents: a signal transmission quality of a frequency domain channel transmitting the initial PUSCH signal; A UCI metric of the initial PUSCH signal is obtained based on the biased estimation deviation, the first symbol sequence correlation, and a modulation symbol sequence included in the initial PUSCH signal.

4. The method according to claim 3, characterized in that The performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric includes: respectively determining a first correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal carries UCI, and a second correlation normal distribution to which the first symbol sequence correlation obeys when the initial PUSCH signal does not carry UCI; Performing amplitude information normalization processing on the first correlation normal distribution and the second correlation normal distribution respectively, to obtain a first metric normal distribution of UCI metric when the initial PUSCH signal carries UCI, and a second metric normal distribution of UCI metric when the initial PUSCH signal does not carry UCI; Based on a first metric expectation in the first metric normal distribution and a second metric expectation in the second metric normal distribution, a metric threshold corresponding to the UCI metric is determined, and based on the UCI metric and the metric threshold, UCI DTX detection is performed on the initial PUSCH signal.

5. The method according to claim 2, characterized in that The obtaining, based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, a UCI metric of the initial PUSCH signal includes: Determine a second symbol sequence correlation between the target PUSCH signal and the reconstructed PUSCH signal based on a modulation symbol sequence included in the target PUSCH signal and a modulation symbol sequence included in the reconstructed PUSCH signal; A UCI metric of the initial PUSCH signal is obtained based on the first symbol sequence correlation and a modulation symbol sequence included in the initial PUSCH signal, and the second symbol sequence correlation.

6. The method according to claim 5, characterized in that The performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric includes: Respectively determine a third metric normal distribution of the UCI metric when the initial PUSCH signal carries the UCI, and a fourth metric normal distribution of the UCI metric when the initial PUSCH signal does not carry the UCI; Based on the third metric expectation in the third metric normal distribution and the fourth metric expectation in the fourth metric normal distribution, a metric threshold corresponding to the UCI metric is determined, and based on the UCI metric and the metric threshold, UCI DTX detection is performed on the initial PUSCH signal.

7. The method according to claim 2, characterized in that The obtaining, based on the first symbol sequence correlation and the modulation symbol sequence included in the initial PUSCH signal, a UCI metric of the initial PUSCH signal includes: Obtaining a target signal-to-noise ratio based on a modulation symbol sequence included in the initial PUSCH signal and a noise symbol sequence included in the target PUSCH signal; A UCI metric of the initial PUSCH signal is obtained based on a biased estimation deviation between the initial PUSCH signal and the target PUSCH signal, the target signal-to-noise ratio, and the first symbol sequence correlation.

8. The method according to claim 7, characterized in that The performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric includes: Performing metric threshold fitting on a fifth metric normal distribution of the UCI metric when the sample PUSCH signal carries UCI under multiple sample signal-to-noise ratios, and a sixth metric normal distribution of the UCI metric when the sample PUSCH signal does not carry UCI, to determine a metric threshold corresponding to the UCI metric; Based on the UCI metric and the metric threshold, DTX detection of UCI is performed on the initial PUSCH signal.

9. The method according to any one of claims 1 to 8, characterized in that The performing DTX detection of UCI on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric includes: If the UCI metric is greater than the metric threshold, determining that the initial PUSCH signal carries the UCI; If the UCI metric is not greater than the metric threshold, it is determined that the initial PUSCH signal does not carry UCI.

10. A discontinuous transmission DTX detection device for uplink control information UCI, characterized in that: include: A signal acquisition module, used to respectively acquire an initial physical uplink shared channel PUSCH signal sent by the terminal and a target PUSCH signal received by the base station; wherein the target PUSCH signal is obtained after channel equalization processing is performed on the initial PUSCH signal; A signal processing module, used to reconstruct the initial PUSCH signal to obtain a reconstructed PUSCH signal, and perform amplitude information removal processing on the reconstructed PUSCH signal to obtain a constant modulus PUSCH signal; wherein the reconstructed PUSCH signal is a conjugate frequency domain signal of the initial PUSCH signal; A metric calculation module, configured to obtain a UCI metric of the initial PUSCH signal based on a modulation symbol sequence respectively included in the target PUSCH signal and the constant modulus PUSCH signal; The signal detection module is used to perform UCI DTX detection on the initial PUSCH signal based on the obtained UCI metric and a metric threshold set corresponding to the UCI metric.

11. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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