DTX detection method and device, electronic equipment and storage medium

Abstract

The invention discloses a DTX detection method and device, electronic equipment and a storage medium, and relates to the technical field of communication. In the application, a receiving end can obtain at least one group of soft information sequences of first information sent by a sending end, thereby obtaining a polar code sequence based on a decoding information sequence determined by the at least one group of soft information sequences, and further detecting whether the sending end is in a DTX state according to the sequence similarity between the polar code sequence and the at least one group of soft information sequences. Optionally, if the sequence similarity is smaller than a similarity threshold value, it can be determined that the sending end is in a DTX state. By adopting the mode, as the polar code sequence is decoded information, the reliability is high, and the DTX state detection (or discrimination) effect is more obvious through the sequence similarity; therefore, the accuracy of DTX detection can be improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a DTX detection method, apparatus, electronic device and storage medium. Background Technology

[0002] In communication systems, the use of discontinuous transmission (DTX) technology can save power consumption at both the signal transmitting end (e.g., terminal) and the signal receiving end (e.g., network equipment).

[0003] Specifically, when the signal transmitter is not in DTX state (i.e., the signal transmitter is in non-DTX state), the signal receiver can receive control information from the signal transmitter. When the signal transmitter is in DTX state, the information received by the signal receiver will no longer be control information but noise.

[0004] In order to accurately determine whether the received information is control information or noise, the signal receiver needs to detect whether the signal transmitter is in DTX state. Currently, DTX state detection methods are mainly divided into two categories: DTX detection methods based on demodulated constellation symbols and DTX detection methods based on demodulated soft information.

[0005] However, the two DTX detection methods mentioned above are usually performed after simple processing of the received signal, which is easily affected by communication quality (e.g., signal to noise ratio, SNR), resulting in a high false positive rate and low accuracy of DTX detection. Summary of the Invention

[0006] This application provides a DTX detection method, apparatus, electronic device, and storage medium to improve the accuracy of DTX detection.

[0007] In a first aspect, embodiments of this application provide a DTX detection method applied at a receiving end, the method comprising:

[0008] Obtain at least one set of soft information sequences of the first information sent by the sender; wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information;

[0009] Based on the decoding information sequence determined by at least one set of soft information sequences, a polarity code sequence is obtained;

[0010] The DTX state of the sending end is determined based on the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0011] Secondly, embodiments of this application provide a DTX detection device applied at a receiving end, the device comprising:

[0012] An information acquisition module is used to acquire at least one set of soft information sequences of the first information sent by the sending end; wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information;

[0013] The sequence processing module is used to obtain a polar code sequence based on a decoding information sequence determined by at least one set of soft information sequences.

[0014] The state detection module is used to determine the DTX state of the sending end based on the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0015] Optionally, each soft information sequence is determined by the information acquisition module sequentially performing soft information conversion and de-rate matching on the first information.

[0016] Optionally, at least one set of soft information sequences is obtained by the information acquisition module by grouping multiple soft information sequences.

[0017] Optionally, the information acquisition module is further configured to:

[0018] If among multiple soft information sequences, there exists a target soft information sequence with a number of sequence elements less than the element count threshold, then the target soft information sequence is padded with sequence elements until the number of sequence elements in the target soft information sequence reaches the element count threshold.

[0019] Optionally, the element quantity threshold is determined by the information acquisition module based on the information encoding method corresponding to the first information.

[0020] Optionally, when obtaining a polar code sequence based on a decoding information sequence determined from at least one set of soft information sequences, the sequence processing module is specifically used for:

[0021] Decode at least one set of soft information sequences to obtain a decoded information sequence, and recode the decoded information sequence to obtain a recoded decoded information sequence;

[0022] The polar code sequence is obtained based on the recoded decoded information sequence.

[0023] Optionally, the polar code sequence is a normalized polar code sequence.

[0024] Optionally, the sequence similarity between the polar code sequence and at least one set of soft information sequences is determined as follows:

[0025] Sequence merging is performed on at least one set of soft information sequences to obtain at least one merged soft information sequence; wherein the number of sequence elements in each merged soft information sequence is a threshold number of elements;

[0026] The first similarity between at least one merged soft information sequence and the polar code sequence is used as the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0027] Optionally, when using the first similarity between at least one merged soft information sequence and the polar code sequence as the sequence similarity between the polar code sequence and at least one set of soft information sequences, the sequence processing module is specifically used to:

[0028] Determine the first sub-similarity between each of at least one merged soft information sequence and the polar code sequence;

[0029] The first similarity is determined based on at least one first sub-similarity, and the first similarity is used as the sequence similarity.

[0030] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module is specifically used to:

[0031] For at least one merged soft information sequence, perform the following operations respectively:

[0032] Multiple sequence element matching pairs are obtained based on a merged soft information sequence and a polar code sequence; wherein, the element position of the soft information sequence element in each sequence element matching pair in a merged soft information sequence is the same as the element position of the polar code sequence element in the polar code sequence.

[0033] Based on the element distances of multiple sequence element matching pairs, the sequence distance between a merged soft information sequence and a polar code sequence is determined.

[0034] Sequence distance is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

[0035] Optionally, the element distance can be any one of Euclidean distance, Manhattan distance, and Chebyshev distance.

[0036] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module is specifically used to:

[0037] For at least one merged soft information sequence, perform the following operations respectively:

[0038] Sequence correlation is calculated between a merged soft information sequence and a polar code sequence to obtain the similarity coefficient between them.

[0039] The similarity coefficient is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

[0040] Optionally, the similarity coefficient can be any one of the following: Pearson correlation coefficient, Spearman rank correlation coefficient, cosine coefficient, Kendall rank correlation coefficient, and Jacquard similarity coefficient.

[0041] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module is specifically used to:

[0042] For at least one merged soft information sequence, perform the following operations respectively:

[0043] Based on the product results of the sequence elements of multiple sequence element matching pairs, the sum of the sequence element products between a merged soft information sequence and a polar code sequence is determined; wherein, the sum of the element products represents the correlation between the merged soft information sequence and the polar code sequence;

[0044] The first sub-similarity between a merged soft information sequence and a polar code sequence is determined based on the sum of the product of sequence elements.

[0045] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module is specifically used to:

[0046] For at least one merged soft information sequence, perform the following operations respectively:

[0047] A domain transformation is performed on the correlation sequence between a merged soft information sequence and a polar code sequence to obtain a domain-transformed correlation sequence; wherein, the correlation sequence includes: the product of multiple sequence element matching pairs with their respective sequence element products;

[0048] Based on the domain transformation coefficients determined by the correlation sequence after domain transformation, the first sub-similarity between a merged soft information sequence and a polar code sequence is determined.

[0049] Optionally, when determining the DTX state of the sending end based on the sequence similarity between the polar code sequence and at least one set of soft information sequences, the state detection module is further configured to:

[0050] If the sequence similarity is less than the similarity threshold, then the sender is determined to be in DTX state;

[0051] If the sequence similarity is greater than or equal to the similarity threshold, it is determined that the sender is not in the DTX state.

[0052] Thirdly, an electronic device provided in this application includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of any of the above-described DTX detection methods.

[0053] Fourthly, embodiments of this application provide a computer-readable storage medium including a computer program, which, when run on an electronic device, causes the electronic device to perform the steps of any of the above-described DTX detection methods.

[0054] Fifthly, embodiments of this application provide a computer program product, the computer program product including a computer program stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to perform the steps of any of the above-described DTX detection methods.

[0055] The beneficial effects of this application are as follows:

[0056] In the DTX detection method provided in this application, the receiving end can obtain at least one set of soft information sequences of the first information sent by the sending end, and then obtain a polar code sequence based on the decoded information sequence determined by the at least one set of soft information sequences. Furthermore, the receiving end detects whether the sending end is in a DTX state based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences. Optionally, if the sequence similarity is less than a similarity threshold, the sending end can be determined to be in a DTX state. Using this method, since the polar code sequence is decoded information, its reliability is high, and the effect of DTX state discrimination (or detection) through sequence similarity is more obvious; therefore, the accuracy of DTX detection can be improved.

[0057] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0059] Figure 1This is a schematic diagram of the architecture of a communication system applicable to the embodiments of this application;

[0060] Figure 2 A schematic flowchart of a DTX detection method provided in an embodiment of this application;

[0061] Figure 3 A logical diagram illustrating how to obtain a polarity code sequence, as provided in an embodiment of this application;

[0062] Figure 4 A schematic diagram illustrating the generation of a merged soft information sequence, provided as an embodiment of this application;

[0063] Figure 5 A schematic diagram of DTX detection based on distance measurement is provided for an embodiment of this application;

[0064] Figure 6 A schematic diagram of DTX detection based on similarity measurement is provided for an embodiment of this application;

[0065] Figure 7 A schematic diagram of DTX detection based on correlation measurement is provided for an embodiment of this application;

[0066] Figure 8 A schematic diagram of DTX detection based on correlation domain transformation measurement is provided for an embodiment of this application;

[0067] Figure 9 This is a schematic diagram of the structure of a DTX detection device provided in an embodiment of this application;

[0068] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this application. Obviously, the described embodiments are only some embodiments of the technical solutions of this application, and not all embodiments. Based on the embodiments recorded in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the technical solutions of this application.

[0070] It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0071] Furthermore, the data collection, dissemination, and use in the technical solution of this application all comply with the requirements of relevant national laws and regulations.

[0072] The following explanations of some technical terms used in the embodiments of this application are provided to facilitate understanding by those skilled in the art.

[0073] (1) Hard decision: is a technology in digital communication systems, mainly used to quantize the signal output by the demodulator.

[0074] Specifically, hard decision compares the signal waveform output by the demodulator with a set decision threshold. If the signal component is higher than the threshold, it is decided as 1; if it is lower than the threshold, it is decided as 0.

[0075] (2) Soft decision: This is a general term for a class of methods in communication signal processing that use probability (also known as soft information or loglikelihood ratio (LLR)) instead of hard decision as bits or constellation symbols. The output of soft decision is often the loglikelihood ratio (i.e. bit likelihood ratio).

[0076] (3) Reed-Muller (RM) code: It is a coding method that can correct single-bit errors, that is, an error control coding technique that can be generated by simple linear algebra equations.

[0077] (4) Polar code: a forward error correction coding method used for signal transmission. Its core construction is through channel polarization, which makes each sub-channel exhibit different reliability. As the code length continues to increase, some channels will tend to become perfect channels with a capacity close to 1 (error-free), while other channels will tend to become pure noise channels with a capacity close to 0.

[0078] (5) Rate matching refers to the retransmission or puncturing of bits on the transmission channel to match the carrying capacity of the physical channel, so that the bit rate required by the transmission format can be achieved during channel mapping.

[0079] The rate-matching algorithm, on the other hand, recovers the eliminated bits or eliminates duplicate bits.

[0080] Furthermore, based on the above explanations of terms and related terminology, the design concept of the embodiments of this application will be briefly introduced below:

[0081] In (wireless) communication systems, DTX plays a crucial role in saving power consumption at signal transmitters (e.g., terminals) and / or signal receivers (e.g., network equipment such as base stations). For example, when the terminal's wireless transmitter is turned off during call breaks, it can save up to 50% of the terminal's transmission, thereby reducing battery wear, system interference, and extending the terminal's battery life. It also reduces the power consumption of the base station.

[0082] When the signal transmitter is not in DTX state, the signal receiver can receive control information from the signal transmitter at a specific location (e.g., time-frequency location). However, when the signal transmitter is in DTX state, the information received by the signal receiver at the aforementioned specific location will no longer be control information but noise.

[0083] Therefore, in order to accurately determine whether the received information is control information or noise, the signal receiver needs to detect whether the signal transmitter is in DTX state. Currently, DTX state detection methods are mainly divided into two categories: DTX detection methods based on demodulated constellation symbols and DTX detection methods based on demodulated soft information.

[0084] For example, in the DTX detection method based on demodulated constellation symbols described above, if there is a correlation between the constellation symbol of the recovered information and the received constellation symbol, the correlation metric between the constellation symbol of the recovered information and the received constellation symbol is relatively large; if the received constellation symbol is a noise symbol, and even if the constellation symbol of the recovered information is erroneous information, the correlation metric between the constellation symbol of the recovered information and the received constellation symbol is relatively small; furthermore, the correlation metric can be compared with a preset threshold. If the correlation metric is greater than the aforementioned threshold, it is determined that the signal transmitter is not in the DTX state; if the aforementioned correlation metric is less than or equal to the aforementioned threshold, it is determined that the signal transmitter is in the DTX state.

[0085] In the aforementioned DTX detection method based on demodulated soft information, the demodulated constellation symbols are typically converted into soft information to obtain a set of soft information sequences that have not undergone rate matching. Then, rate matching is performed on these soft information sequences. Generally, the information bits after rate matching at the signal transmitter are a set of two or more sets of information bits from the previous rate matching. Therefore, after rate matching, the signal receiver can obtain two or more sets of soft information sequences. Furthermore, since the positions of the sequence elements in each set of soft information sequences are fixed, all sets of soft information sequences can be linearly merged using the superposition operation (average, weighted average, summation) of sequence elements at the same positions. For example, all sets of soft information sequences can be divided into two clusters, and linear merging can be performed within each cluster to obtain two new sets of soft information sequences. Then, these two sets of soft information sequences are directly correlated to obtain a correlation metric, which is compared with a preset threshold. If the correlation metric is greater than the threshold, the signal transmitter is determined not to be in a DTX state; if the correlation metric is less than or equal to the threshold, the signal transmitter is determined to be in a DTX state.

[0086] For example, all groups of soft information sequences are linearly merged to obtain a new set of soft information sequences. Then, a hard decision is made on the merged soft information sequences (classified by positive or negative sign) to obtain a set of sequences with distinct polarities (containing only 0 / 1). Simultaneously, the merged soft information sequences are decoded (e.g., RM code, Polar code, etc.) to obtain a decoded information sequence, and the decoded information sequence is recoded to obtain a recoded sequence. Next, the Hamming distance between the polarity sequence after the hard decision and the recoded sequence is compared with a preset threshold value. If the Hamming distance is greater than the threshold value, the signal transmitter is determined to be in the DTX state; if the Hamming distance is less than or equal to the threshold value, the signal transmitter is determined not to be in the DTX state.

[0087] However, the two DTX detection methods mentioned above are usually performed after simple processing of the received signal, which is easily affected by communication quality (e.g., SNR), resulting in a high false positive rate and low accuracy of DTX detection. Furthermore, using hard decision and / or Hamming distance for DTX detection is also difficult to ensure accuracy due to the unclear decision effect.

[0088] In view of this, to improve the accuracy of DTX detection, this application proposes a DTX detection method, specifically including: acquiring at least one set of soft information sequences of first information transmitted by the sending end, wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information; then, obtaining a polar code sequence based on the decoded information sequence determined by the at least one set of soft information sequences; finally, determining the DTX state of the sending end based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences, for example, the sending end is in a DTX state, or the sending end is not in a DTX state (i.e., the sending end is in a non-DTX state). Using this method, since the decoded information sequence has high reliability, and DTX state discrimination (or detection) based on sequence similarity is more effective than hard decision and / or Minghan distance, the accuracy of DTX detection can be improved.

[0089] It should be noted that the above-mentioned signal transmitting end not being in DTX state or the transmitting end being in non-DTX state can also be understood as the signal transmitting end being in continuous transmission state, and this application embodiment does not limit this.

[0090] In particular, the preferred embodiments of this application will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments of this application and the features in the embodiments can be combined with each other without conflict.

[0091] The technical solutions in this application embodiment can be applied to various communication systems, such as the 5th generation (5G) mobile communication system (e.g., 5G new radio (NR) system) and / or the non-terrestrial network (NTN) communication system in the future evolution of communication systems (e.g., the 6th generation (6G) mobile communication system).

[0092] See Figure 1 The diagram shown illustrates the architecture of a communication system applicable to an embodiment of this application. The communication system may include two signal transmitters 101 and one signal receiver 102. Each signal transmitter 101 can interact with the signal receiver 102 via a communication network. The communication network may employ wireless communication or wired communication methods.

[0093] For example, the signal transmitter 101 can access the network and communicate with the signal receiver 102 via cellular mobile communication technology, such as 5G technology or next-generation mobile communication technology. Optionally, the signal transmitter 101 can access the network and communicate with the signal receiver 102 via short-range wireless communication, such as wireless fidelity (Wi-Fi) technology.

[0094] This application embodiment does not limit the number of communication devices involved in the above application scenarios. For example, there may be more signal transmitters 101, or only one signal transmitter 101, or other devices may be included, such as... Figure 1 As shown, only two signal transmitting ends 101 and signal receiving ends 102 are used as examples for description. The following is a brief introduction to the above communication devices and their respective functions.

[0095] Signal transmitter 101 is used to send information to signal receiver 102. Correspondingly, signal receiver 102 can receive the aforementioned information from signal transmitter 101. Optionally, signal receiver 102 can also feed back the response to the aforementioned information to signal transmitter 101. It can be seen that the roles of signal transmitter 101 and signal receiver 101 are relative. That is, when signal receiver 102 feeds back the aforementioned information to signal transmitter 101, it is sending the response to signal transmitter 101 as an information sender. At this time, signal receiver 102 can be regarded as signal transmitter, and signal transmitter 101 can be regarded as signal receiver.

[0096] This application does not limit the types of signal transmitter 101 and signal receiver 102. For example, signal transmitter 101 can be a terminal and signal receiver 102 can be a network device; or, for another example, signal transmitter 101 can be a network device and signal receiver 102 can be a terminal.

[0097] The terminal can be a device that provides wireless communication capabilities, such as a handheld device or vehicle-mounted device with wireless connectivity. For example, terminals may include: mobile phones, satellite mobile terminals, cellular phones, smartphones, computers, mobile internet devices (MIDs), wearable devices (e.g., smartwatches, smart bracelets), in-vehicle equipment (e.g., cars, ships, trains), virtual reality (VR) devices, augmented reality (AR) devices, smart point-of-sale (POS) machines, customer-premises equipment (CPE), wireless terminals in industrial control, wireless terminals in self-driving vehicles, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes (e.g., refrigerators, televisions, air conditioners, electricity meters), smart robots, robotic arms, cellular phones, session initiation protocol (SIP) phones, and wireless local loops. The embodiments of this application do not limit the scope to local loop (WLL) stations, personal digital assistants (PDAs), computing devices or other processing devices connected to wireless modems, flying devices (e.g., hot air balloons, drones, airplanes), terminals in 5G networks or terminals in future evolved public land mobile networks (PLMNs).

[0098] In the embodiments of this application, a terminal may also be referred to as user equipment (UE), access terminal, subscriber unit, user station, mobile station, mobile station (MS), remote station, remote terminal, mobile device, user terminal, terminal equipment, wireless communication equipment, user agent, or user device.

[0099] This application does not limit the device form of the terminal. The device used to implement the terminal's functions can be the terminal itself, or it can be any device that supports the terminal in implementing those functions, such as a chip system. This device can be installed in the terminal or used in conjunction with the terminal. In this application, the chip system can be composed of chips, or it can include chips and other discrete components.

[0100] Network equipment includes, for example, access network equipment and / or core network equipment. Access network equipment is a device with wireless transceiver capabilities used to communicate with terminals. Access network equipment includes, but is not limited to, base stations (base transceiver stations (BTS), Node B, evolved Node B (eNodeB) / eNB, or the next generation Node B (gNodeB) / gNB), transmission reception points (TRPs), base stations evolved under the 3rd Generation Partnership Project (3GPP), access nodes in Wi-Fi systems, wireless relay nodes, wireless backhaul nodes, etc. Base stations can be: macro base stations, micro base stations, pico base stations, small cells, relay stations, etc. Multiple base stations can support networks using the same access technology or networks using different access technologies. A base station can contain one or more co-located or non-co-located transmit / receive points. Access network equipment can also be radio controllers, centralized units (CUs), and / or distributed units (DUs) in cloud radio access network (CRAN) scenarios, or other equipment in the access network such as base station control equipment or servers; this application does not limit this. For example, network equipment in V2X technology can be roadside units (RSUs). Core network equipment is used to implement functions such as mobility management, data processing, session management, policy and charging. The names of the equipment implementing core network functions may differ in systems with different access technologies; this application does not limit this. Taking a 5G system as an example, core network equipment includes: access and mobility management function (AMF), session management function (SMF), policy control function (PCF), or user plane function (UPF), etc.

[0101] In one optional application scenario, since the aforementioned communication system can be an NTN system, and NTN can include, but is not limited to, networks that use spectrum resources on communication platforms such as satellite platforms, unmanned aerial vehicle (UAV) platforms, or high altitude platform stations (HAPS) to provide communication services, the aforementioned NTN system can include, but is not limited to, satellite communication systems, UAV communication systems, and HAPS systems. Taking satellite communication systems as an example, according to the different altitudes of the satellite above the Earth's surface (i.e., satellite orbital altitude), satellite communication systems can be divided into geostationary orbit (GEO) satellite systems or geostationary orbit (GEO or GSO) satellite systems, highly elliptical orbit (HEO) satellite systems, medium Earth orbit (MEO) satellite systems, and low Earth orbit (LEO) satellite systems, etc.

[0102] GEO satellite systems can also be called geostationary orbit satellite systems. HEO, MEO, and LEO satellite systems can also be collectively referred to as non-geostationary earth orbit (NGEO or NGSO) satellite systems, or non-geostationary orbit satellite systems. Correspondingly, according to the type of satellite communication system, the satellites in the satellite communication system can also be divided into GEO satellites, HEO satellites, MEO satellites, LEO satellites, etc. Therefore, network equipment can also include the aforementioned types of satellites.

[0103] In this application embodiment, the communication device used to implement the network device function can be a network device itself, or it can be a device capable of supporting the network device in implementing that function, such as a chip system. This device can be installed within the network device. In the technical solutions provided in this application embodiment, the example of a network device being used to implement the network device function is used to describe the technical solutions provided in this application embodiment.

[0104] Of course, in this embodiment, the signal transmitting end 101 and the signal receiving end 102 can be other devices. This embodiment does not limit them. For ease of description and understanding, the signal transmitting end 101 will be referred to as the transmitting end and the signal receiving end 102 will be referred to as the receiving end.

[0105] It is worth noting that, in the embodiments of this application, the receiving end can be used to obtain at least one set of soft information sequences of the first information sent by the sending end, thereby obtaining a polar code sequence based on the decoding information sequence determined by at least one set of soft information sequences, and then determining whether the sending end is in the DTX state based on the sequence similarity between the polar code sequence and at least one set of soft information sequences; optionally, if the sequence similarity is less than the similarity threshold, it can be determined that the sending end is in the DTX state, and if the sequence similarity is greater than or equal to the similarity threshold, it can be determined that the sending end is not in the DTX state.

[0106] The DTX detection method provided by the exemplary embodiments of this application will be described below in conjunction with the above system architecture and with reference to the accompanying drawings. It should be noted that the above system architecture is only shown for the purpose of understanding the spirit and principles of this application, and the embodiments of this application are not limited in any way.

[0107] See Figure 2 The diagram shown is a flowchart of a DTX detection method provided in an embodiment of this application. Taking the receiving end as the execution subject as an example, the specific implementation process of this method is as follows:

[0108] S201: Obtain at least one set of soft information sequences of the first information sent by the sender.

[0109] Each set of soft information sequences may include at least one soft information sequence. For example, each set of soft information sequences may include three soft information sequences, each of which can be determined based on the first information. Optionally, the number of bits in each soft information sequence is the same as the number of bits in the data information (unmatched information) corresponding to the first information (information after rate matching).

[0110] For example, assuming the above data information is a 32-bit sequence, the first information is a 96-bit sequence after being repeated 3 times in rate matching. Therefore, after receiving the first information sent by the transmitter, the receiver can obtain 3 soft information sequences based on the first information. Each soft information sequence can be a sequence composed of LLR values, that is, a soft information sequence can be considered as an LLR sequence or an LLR vector. For example, each soft information sequence is a sequence composed of 32 LLR values.

[0111] In one optional implementation, when performing step S201, the receiving end can obtain the first information after soft information conversion by performing soft information conversion on the first information, and then perform rate matching on the first information after soft information conversion to obtain multiple soft information sequences. That is, each soft information sequence is determined by performing soft information conversion and rate matching on the first information in sequence.

[0112] The first information after soft information conversion can also be called demodulated soft information, or it can have other names. This application embodiment does not limit this.

[0113] Optionally, to ensure the smooth progress of subsequent DTX detection, the sending end can also group the obtained multiple soft information sequences, that is, divide the aforementioned multiple soft information sequences into at least one group of soft information sequences.

[0114] For example, the first information can be a demodulated constellation symbol sequence. The receiving end can perform soft information conversion on the demodulated constellation symbol sequence to obtain a set of soft information sequences that have not been rate-matched (i.e., the first information after soft information conversion or the demodulated soft information). Then, rate-matching is performed on the aforementioned set of soft information sequences. It should be noted that the embodiments of this application do not limit the specific method of how to divide multiple soft information sequences into at least one set of soft information sequences.

[0115] Generally, the information bits after rate matching at the transmitting end are a set of two or more fixed-length information bits before rate matching. The aforementioned fixed length is determined by the specific encoding specification. For example, the fixed length can be 32 bits or 64 bits, etc. This application embodiment does not limit this.

[0116] To ensure that the number of sequence elements in each soft information sequence is consistent when the receiving end merges the multiple soft information sequences, when there is a soft information sequence among the multiple soft information sequences that does not meet the above fixed length, the sequence elements of the soft information sequence can be padded. Therefore, in an optional implementation, this application embodiment may further include: if there is a target soft information sequence among the multiple soft information sequences whose number of sequence elements is less than the element number threshold, then the target soft information sequence is padded with sequence elements until the number of sequence elements of the target soft information sequence reaches the element number threshold.

[0117] The aforementioned element quantity threshold can be determined based on the information encoding method (or information encoding specification) corresponding to the first information. Optionally, the element quantity threshold can be determined based on the number of bits used to encode the non-mask bits in the information encoding method corresponding to the first information. For example, if the number of bits used to encode the non-mask bits is 6, then the aforementioned element quantity threshold can be 2. 6-1 =32.

[0118] For example, suppose the receiving end obtains M soft information sequences after rate matching of the first information after soft information conversion, where each soft information sequence has a preset fixed length L. If there is a target soft information sequence among the M soft information sequences whose sequence length does not meet the preset fixed length L, the target soft information sequence can be padded with "0"s until the length of the target sequence elements reaches the preset fixed length L. In this way, the receiving end can then perform subsequent sequence merging of the padded target soft information sequence with the other M-1 soft information sequences. Here, the sequence length of each soft information sequence represents the number of sequence elements in the corresponding soft information sequence.

[0119] It should be noted that the reason for using "adding 0" to pad the sequence elements is that the sequence elements of the soft information sequence are LLR values. When the LLR value is greater than 0, the probability of the bit encoding before the soft information conversion being 1 is high, and when the LLR value is less than 0, the probability of the bit encoding before the soft information conversion being 0 is high. Therefore, the soft information sequence padded by "adding 0" has higher reliability.

[0120] Optionally, in order to save system overhead and reduce the complexity of DTX detection, the multiple soft information sequences mentioned above can be left ungrouped. Instead, the multiple soft information sequences can be directly treated as a large set for subsequent soft information sequence merging and DTX detection operations.

[0121] S202: Obtain the polar code sequence based on the decoding information sequence determined by at least one set of soft information sequences.

[0122] In one alternative implementation, see [link to relevant documentation]. Figure 3 As shown, when performing step S202, the receiving end can decode at least one set of soft information sequences obtained in S201 to obtain a decoded information sequence, and then re-encode the decoded information sequence to obtain a re-encoded decoded information sequence. Based on the re-encoded decoded information sequence, a polarity code sequence can be obtained. In this way, after obtaining a polarity code sequence with higher reliability and more obvious discrimination effect, the receiving end can improve the accuracy of DTX detection.

[0123] Optionally, to improve the discrimination effect of DTX detection, the aforementioned polarity code sequence can be a normalized polarity code sequence (e.g., a sequence encoded with -1 and 1). Therefore, the receiving end decodes the soft information after rate matching (i.e., at least one set of soft information sequences or multiple soft information sequences) to obtain decoded information bits (i.e., the aforementioned decoded information sequence); then, it can re-encode the decoded information bits according to the protocol coding specification to obtain recoded information bits (i.e., the aforementioned recoded decoded information sequence); finally, it polarizes the recoded information bits (the polarization value of 0 is 1, and the polarization value of 1 is -1) to generate a normalized true polarity sequence (i.e., the aforementioned normalized polarity code sequence).

[0124] Since at least one set of soft information sequences is obtained based on the first information after the aforementioned soft information conversion (i.e. demodulated soft information), in order to obtain the polar code sequence more quickly, the first information after the aforementioned soft information conversion can be directly decoded to obtain the decoded information sequence, thereby improving the speed of DTX detection.

[0125] S203: Determine the DTX state of the sending end based on the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0126] Optionally, when performing step S203, if the sequence similarity is less than the similarity threshold, it can be determined that the transmitter is in DTX state. For example, assuming the similarity threshold is 90%, if the sequence similarity between the polar code sequence and at least one set of soft information sequences is 88.7%, the receiver can determine that the sequence similarity (i.e., 88.7%) is less than the similarity threshold (i.e., 90%), and thus determine that the transmitter is in DTX state. Furthermore, it can be determined that the first information transmitted by the transmitter is noise rather than control information.

[0127] Optionally, if the sequence similarity is greater than or equal to the similarity threshold, it can be determined that the transmitter is not in a DTX state. For example, still assuming the similarity threshold is 90%, if the sequence similarity between the polar code sequence and at least one set of soft information sequences is 93.8%, the receiver can determine that the sequence similarity (i.e., 93.8%) is greater than the similarity threshold (i.e., 90%), and thus determine that the transmitter is not in a DTX state. Consequently, it can be determined that the first information transmitted by the transmitter is control information rather than noise.

[0128] Based on the DTX detection method described in steps S201 to S203 above, the receiving end determines or detects the DTX state based on the sequence similarity between the decoded polar code sequence and at least one set of soft information sequences, thereby improving the reliability or accuracy of DTX detection.

[0129] In order to fully utilize the merging gain of all LLR clusters (i.e., at least one set of soft information sequences mentioned above) to improve the accuracy of DTX detection, in this embodiment of the application, the receiving end can perform sequence merging on at least one set of soft information sequences to obtain at least one merged soft information sequence (i.e., the merged soft information sequence corresponding to each of the at least one set of soft information sequences).

[0130] For example, see Figure 4 As shown, it is still assumed that the receiving end converts the soft information into the first information (i.e., Figure 4 After demodulation rate matching of the demodulated soft information, M soft information sequences are obtained. Optionally, these M soft information sequences can be diversified or grouped, for example, to obtain N clusters (i.e., N groups of soft information sequences). Then, the N clusters are linearly merged to finally generate N merged soft information sequences, such as... Figure 4 The merged soft information sequences shown are 1 to N, where M and N are both positive integers.

[0131] Optionally, since the merged soft information sequence can be determined by linearly merging the sequence elements at the same position of each soft information sequence in a set of soft information sequences through superposition operations (such as weighted average, summation, etc.), the number of sequence elements of each merged soft information sequence is the element number threshold. That is, the merged soft information sequence has the same number of sequence elements as the soft information sequence that meets the element number threshold, or the merged soft information sequence has the same sequence length as the soft information sequence that meets the preset fixed length.

[0132] Furthermore, after the receiving end obtains at least one merged soft information sequence, it can use the first similarity between the at least one merged soft information sequence and the polar code sequence as the sequence similarity between the polar code sequence and at least one set of soft information sequences. Here, the term "first similarity" is used only for ease of description; the naming of the similarity between the at least one merged soft information sequence and the polar code sequence is not limited in this embodiment, meaning that the similarity between the at least one merged soft information sequence and the polar code sequence can also have other names.

[0133] In one alternative implementation, the receiving end can determine at least one merged soft information sequence and the first sub-similarity between each sequence and the polar code sequence, thereby determining the first similarity based on at least one first sub-similarity and using the first similarity as the sequence similarity. In this way, since the computational cost of each first sub-similarity is much less than the computational cost of directly determining the first similarity between at least one merged soft information sequence and the polar code sequence, the computational complexity of the first similarity is reduced to a certain extent.

[0134] Optionally, for the above-mentioned at least one merged soft information sequence, the receiving end may perform the following operations respectively: obtain multiple sequence element matching pairs based on a merged soft information sequence and a polar code sequence; then, determine the sequence distance between a merged soft information sequence and a polar code sequence based on the element distances corresponding to the multiple sequence element matching pairs; finally, use the sequence distance as the first sub-similarity between the aforementioned merged soft information sequence and the polar code sequence. Wherein, the element position of the soft information sequence element in each sequence element matching pair within the aforementioned merged soft information sequence is the same as the element position of the polar code sequence element within the polar code sequence, and the element distance can be any one of Euclidean distance, Manhattan distance, and Chebyshev distance; of course, other distances are also possible, and this embodiment of the application does not limit this.

[0135] Based on the above-mentioned first sub-similarity calculation method based on distance measurement, see [link / reference]. Figure 5 As shown, the receiving end can determine the sequence distance between each of the N merged soft information sequences and the (normalized) polar code sequence. Optionally, to make the subsequent DTX discrimination effect more obvious, the aforementioned N merged soft information sequences can also be normalized. Then, after determining the sequence distance corresponding to each of the aforementioned N merged soft information sequences, the N sequence distances (representing the first sub-similarity) can be merged by a linear superposition operation such as weighted average to obtain the merged distance (representing the first similarity or sequence similarity). Finally, the terminal's DTX detection is performed based on the merged distance and the distance threshold (i.e., the similarity threshold). The larger the merged distance, the smaller the first similarity. Therefore, if the merged distance is not less than the distance threshold (i.e., the first similarity is not less than the similarity threshold), the terminal can be determined to be in a DTX state; if the merged distance is less than the distance threshold (i.e., the first similarity is less than the similarity threshold), the terminal can be determined not to be in a DTX state.

[0136] Optionally, for at least one of the above-mentioned merged soft information sequences, the receiving end may also perform the following operations respectively: calculate the sequence correlation between a merged soft information sequence and a polar code sequence to obtain the similarity coefficient between the aforementioned merged soft information sequence and the polar code sequence, and then use the similarity coefficient as the first sub-similarity between the aforementioned merged soft information sequence and the polar code sequence.

[0137] The similarity coefficient can be any one of the Pearson correlation coefficient, Spearman rank correlation coefficient, cosine coefficient, Kendall rank correlation coefficient, and Jacquard similarity coefficient, used to measure the degree of similarity between the above-mentioned merged soft information sequence and the polar code sequence; of course, it can also be other similarity coefficients, and this application embodiment does not limit it.

[0138] Based on the above-mentioned first sub-similarity calculation method based on similarity coefficient measurement, please refer to... Figure 6As shown, the receiving end can determine the similarity coefficients between each of the N merged soft information sequences and the (normalized) polar code sequence. Then, after determining the similarity coefficients for each of the aforementioned N merged soft information sequences, the N similarity coefficients (i.e., the first sub-similarity) can be merged using a weighted average or other linear superposition operation to obtain the first merge coefficient (i.e., the first similarity or sequence similarity). Finally, the terminal performs DTX detection based on the first merge coefficient and the similarity coefficient threshold (i.e., the similarity threshold). For example, if the first merge coefficient is less than the similarity coefficient threshold, it can be determined that the terminal is in a DTX state; if the first merge coefficient is not less than the similarity coefficient threshold, it can be determined that the terminal is not in a DTX state.

[0139] Optionally, for the above-mentioned at least one merged soft information sequence, the receiving end may also perform the following operations respectively: based on the product results of the sequence elements of multiple sequence element matching determined by the above-mentioned merged soft information sequence and the polar code sequence, determine the sum of the sequence element products between the above-mentioned merged soft information sequence and the polar code sequence, and then based on the sum of the sequence element products, determine the first sub-similarity between the above-mentioned merged soft information sequence and the polar code sequence; wherein, the sum of the element products can characterize the correlation between the above-mentioned merged soft information sequence and the polar code sequence.

[0140] Based on the above-mentioned first sub-similarity calculation method based on correlation measurement, see [link / reference]. Figure 7 As shown, the receiving end can perform a one-to-one correlation between each of the N merged soft information sequences and the (normalized) polar code sequence. Based on the correlation results of the N merged soft information sequences, the sum of the product of their respective sequence elements (i.e., the correlation coefficient) can be determined. Optionally, the correlation coefficient can be calculated using methods including, but not limited to, direct summation, weighted summation, or linear polynomial summation. Next, after determining the correlation coefficients for each of the aforementioned N merged soft information sequences, the N correlation coefficients (i.e., the first sub-similarity) can be merged using a linear superposition operation such as weighted averaging to obtain a second merging coefficient (i.e., the first similarity or sequence similarity). Finally, the terminal performs DTX detection based on the second merging coefficient and the correlation coefficient threshold (i.e., the similarity threshold). For example, if the second merging coefficient is less than the correlation coefficient threshold, the terminal can be determined to be in a DTX state; if the second merging coefficient is not less than the correlation coefficient threshold, the terminal can be determined not to be in a DTX state.

[0141] Optionally, for the above-mentioned at least one merged soft information sequence, the receiving end may also perform the following operations respectively: perform a domain transformation on the correlation sequence between the above-mentioned merged soft information sequence and the polar code sequence to obtain the domain-transformed correlation sequence, and then determine the first sub-similarity between the above-mentioned merged soft information sequence and the polar code sequence based on the domain transformation coefficients determined by the domain-transformed correlation sequence; wherein, the correlation sequence may include: the product result of the above-mentioned multiple sequence element matching pairs of their respective sequence elements.

[0142] Based on the above-mentioned first sub-similarity calculation method based on relevance domain transformation measurement, see [link / reference]. Figure 8 As shown, the receiving end can perform domain transformation on the correlation results corresponding to the N merged soft information sequences mentioned above, obtaining N transformed analysis sequences (i.e., correlation sequences after domain transformation). Next, based on the N transformed analysis sequences, the domain transformation coefficients (i.e., the first sub-similarity) corresponding to each of the aforementioned N merged soft information sequences can be determined. Furthermore, after determining the domain transformation coefficients corresponding to each of the aforementioned N merged soft information sequences, the N domain transformation coefficients can be merged using a weighted average or other linear superposition operation to obtain a third merging coefficient (i.e., the first similarity or sequence similarity). Finally, the terminal's DTX detection is performed based on the third merging coefficient and the domain transformation coefficient threshold (i.e., the similarity threshold). For example, if the third merging coefficient is less than the domain transformation coefficient, it can be determined that the terminal is in a DTX state; if the third merging coefficient is not less than the domain transformation coefficient, it can be determined that the terminal is not in a DTX state.

[0143] The aforementioned domain transformation methods may include, but are not limited to, orthogonal domain transformation methods such as Hadamard transform, Fourier transform, cosine transform, and wavelet transform, and may also include other domain transformation methods. This application embodiment does not limit these methods.

[0144] Optionally, the receiving end can obtain the domain transformation coefficients by extracting the maximum value of the transform analysis sequence and comparing it with the remaining values, such as by dividing the maximum value by the average of the remaining values, dividing the maximum value by the average of all values, or dividing the square of the maximum value by the average of the squares of all values; or by calculating the variance of the transform analysis sequence. This embodiment of the application does not limit this.

[0145] Based on the four methods for determining sequence similarity mentioned above, the receiving end can not only obtain relatively accurate sequence similarity to ensure the accuracy of DTX detection, but also be applicable to DTX detection under different performance requirements or implementation complexities, that is, it can be adapted to a variety of DTX detection scenarios.

[0146] In summary, in the DTX detection method provided in this application embodiment, the receiving end can obtain at least one set of soft information sequences of the first information sent by the sending end, thereby obtaining a polar code sequence based on the decoded information sequence determined by the at least one set of soft information sequences. Then, it detects whether the sending end is in a DTX state based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences. Optionally, if the sequence similarity is less than a similarity threshold, it can be determined that the sending end is in a DTX state. Using this method, since the polar code sequence is decoded information, its reliability is high, and the effect of DTX state discrimination (or detection) through sequence similarity is more obvious; therefore, the accuracy of DTX detection can be improved.

[0147] Furthermore, based on the same technical concept, embodiments of this application provide a DTX detection device for implementing the above-described method flow of embodiments of this application. See also... Figure 9 As shown, the DTX detection device includes: an information acquisition module 901, a sequence processing module 902, and a state detection module 903, wherein:

[0148] The information acquisition module 901 is used to acquire at least one set of soft information sequences of the first information sent by the sending end; wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information;

[0149] The sequence processing module 902 is used to obtain a polar code sequence based on a decoding information sequence determined by at least one set of soft information sequences.

[0150] The state detection module 903 is used to determine the DTX state of the sending end based on the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0151] Optionally, each soft information sequence is determined by the information acquisition module 901 sequentially performing soft information conversion and de-rate matching on the first information.

[0152] Optionally, at least one set of soft information sequences is obtained by the information acquisition module 901 by grouping multiple soft information sequences.

[0153] Optionally, the information acquisition module 901 is further configured to:

[0154] If among multiple soft information sequences, there exists a target soft information sequence with a number of sequence elements less than the element count threshold, then the target soft information sequence is padded with sequence elements until the number of sequence elements in the target soft information sequence reaches the element count threshold.

[0155] Optionally, the element quantity threshold is determined by the information acquisition module 901 based on the information encoding method corresponding to the first information.

[0156] Optionally, when obtaining a polar code sequence based on a decoding information sequence determined by at least one set of soft information sequences, the sequence processing module 902 is specifically used for:

[0157] Decode at least one set of soft information sequences to obtain a decoded information sequence, and recode the decoded information sequence to obtain a recoded decoded information sequence;

[0158] The polar code sequence is obtained based on the recoded decoded information sequence.

[0159] Optionally, the polar code sequence is a normalized polar code sequence.

[0160] Optionally, the sequence similarity between the polar code sequence and at least one set of soft information sequences is determined as follows:

[0161] Sequence merging is performed on at least one set of soft information sequences to obtain at least one merged soft information sequence; wherein the number of sequence elements in each merged soft information sequence is a threshold number of elements;

[0162] The first similarity between at least one merged soft information sequence and the polar code sequence is used as the sequence similarity between the polar code sequence and at least one set of soft information sequences.

[0163] Optionally, when using the first similarity between at least one merged soft information sequence and the polar code sequence as the sequence similarity between the polar code sequence and at least one set of soft information sequences, the sequence processing module 902 is specifically used to:

[0164] Determine the first sub-similarity between each of at least one merged soft information sequence and the polar code sequence;

[0165] The first similarity is determined based on at least one first sub-similarity, and the first similarity is used as the sequence similarity.

[0166] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module 902 is specifically used to:

[0167] For at least one merged soft information sequence, perform the following operations respectively:

[0168] Multiple sequence element matching pairs are obtained based on a merged soft information sequence and a polar code sequence; wherein, the element position of the soft information sequence element in each sequence element matching pair in a merged soft information sequence is the same as the element position of the polar code sequence element in the polar code sequence.

[0169] Based on the element distances of multiple sequence element matching pairs, the sequence distance between a merged soft information sequence and a polar code sequence is determined.

[0170] Sequence distance is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

[0171] Optionally, the element distance can be any one of Euclidean distance, Manhattan distance, and Chebyshev distance.

[0172] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module 902 is specifically used to:

[0173] For at least one merged soft information sequence, perform the following operations respectively:

[0174] Sequence correlation is calculated between a merged soft information sequence and a polar code sequence to obtain the similarity coefficient between them.

[0175] The similarity coefficient is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

[0176] Optionally, the similarity coefficient can be any one of the following: Pearson correlation coefficient, Spearman rank correlation coefficient, cosine coefficient, Kendall rank correlation coefficient, and Jacquard similarity coefficient.

[0177] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module 902 is specifically used to:

[0178] For at least one merged soft information sequence, perform the following operations respectively:

[0179] Based on the product results of the sequence elements of multiple sequence element matching pairs, the sum of the sequence element products between a merged soft information sequence and a polar code sequence is determined; wherein, the sum of the element products represents the correlation between the merged soft information sequence and the polar code sequence;

[0180] The first sub-similarity between a merged soft information sequence and a polar code sequence is determined based on the sum of the product of sequence elements.

[0181] Optionally, when determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence, the sequence processing module 902 is specifically used to:

[0182] For at least one merged soft information sequence, perform the following operations respectively:

[0183] A domain transformation is performed on the correlation sequence between a merged soft information sequence and a polar code sequence to obtain a domain-transformed correlation sequence; wherein, the correlation sequence includes: the product of multiple sequence element matching pairs with their respective sequence element products;

[0184] Based on the domain transformation coefficients determined by the correlation sequence after domain transformation, the first sub-similarity between a merged soft information sequence and a polar code sequence is determined.

[0185] Optionally, when determining the DTX state of the transmitting end based on the sequence similarity between the polar code sequence and at least one set of soft information sequences, the state detection module 903 is further configured to:

[0186] If the sequence similarity is less than the similarity threshold, then the sender is determined to be in DTX state;

[0187] If the sequence similarity is greater than or equal to the similarity threshold, it is determined that the sender is not in the DTX state.

[0188] Based on the same technical concept, embodiments of this application also provide an electronic device that can implement the DTX detection method flow provided in the above embodiments of this application. In one embodiment, the electronic device can be a server, a terminal device, or other electronic equipment. Figure 10 As shown, the electronic device may include:

[0189] At least one processor 1001 and a memory 1002 connected to at least one processor 1001. In this embodiment, the specific connection medium between the processor 1001 and the memory 1002 is not limited. Figure 10 The example shown is the connection between processor 1001 and memory 1002 via bus 1000. Bus 1000 is... Figure 10 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. The Bus 1000 can be divided into address bus, data bus, control bus, etc., for ease of representation. Figure 10 The term 1001 is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, the processor 1001 can also be called a controller; there are no restrictions on the name.

[0190] In this embodiment, memory 1002 stores instructions executable by at least one processor 1001. By executing the instructions stored in memory 1002, at least one processor 1001 can perform a DTX detection method as described above. Processor 1001 can implement... Figure 9 The functions of each module in the device shown.

[0191] The processor 1001 is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory 1002 and calling data stored in memory 1002, the processor can perform various functions and process data, thereby monitoring the device as a whole.

[0192] In one possible design, processor 1001 may include one or more processing units. Processor 1001 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 1001. In some embodiments, processor 1001 and memory 1002 may be implemented on the same chip; in some embodiments, they may also be implemented on separate chips.

[0193] The processor 1001 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of a DTX detection method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0194] Memory 1002, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 1002 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. Memory 1002 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 1002 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0195] By designing and programming the processor 1001, the code corresponding to the DTX detection method described in the foregoing embodiments can be embedded into the chip, thereby enabling the chip to execute the code during operation. Figure 2 The illustrated embodiment presents the steps of a DTX detection method. How to design and program the processor 1001 is a technique well-known to those skilled in the art and will not be described further here.

[0196] Based on the same inventive concept, embodiments of this application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a DTX detection method described above.

[0197] In some possible implementations, this application also provides that various aspects of a DTX detection method can be implemented as a program product including program code, which, when the program product is run on a device, causes the control device to perform the steps in a DTX detection method according to various exemplary embodiments of this application described above.

[0198] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this 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 and embodied by multiple units.

[0199] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0200] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0201] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0202] Program code for performing the operations of this application can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0203] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0204] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0205] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for detecting discontinuous DTX transmission, characterized in that, Applied to the receiving end, including: Acquire at least one set of soft information sequences of the first information sent by the sending end; wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information; Based on the decoding information sequence determined by the at least one set of soft information sequences, a polarity code sequence is obtained; The DTX state of the transmitting end is determined based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences.

2. The method as described in claim 1, characterized in that, Each soft information sequence is determined by sequentially performing soft information transformation and de-rate matching on the first information.

3. The method as described in claim 1, characterized in that, The at least one set of soft information sequences is obtained by grouping multiple soft information sequences.

4. The method as described in claim 3, characterized in that, The method further includes: If, among the plurality of soft information sequences, there exists a target soft information sequence with a number of sequence elements less than the element number threshold, then the target soft information sequence is padded with sequence elements until the number of sequence elements of the target soft information sequence reaches the element number threshold.

5. The method as described in claim 4, characterized in that, The threshold for the number of elements is determined based on the information encoding method corresponding to the first information.

6. The method as described in claim 1, characterized in that, The process of obtaining a polar code sequence based on the decoding information sequence determined by the at least one set of soft information sequences includes: The at least one set of soft information sequences is decoded to obtain the decoded information sequence, and the decoded information sequence is re-encoded to obtain the re-encoded decoded information sequence. Based on the recoded decoding information sequence, the polar code sequence is obtained.

7. The method as described in claim 6, characterized in that, The polar code sequence is a normalized polar code sequence.

8. The method according to any one of claims 1 to 7, characterized in that, The sequence similarity between the polar code sequence and the at least one set of soft information sequences is determined in the following manner: Sequence merging is performed on the at least one set of soft information sequences to obtain at least one merged soft information sequence; wherein the number of sequence elements in each merged soft information sequence is a threshold number of elements; The first similarity between the at least one merged soft information sequence and the polar code sequence is taken as the sequence similarity between the polar code sequence and the at least one set of soft information sequences.

9. The method as described in claim 8, characterized in that, The step of using the first similarity between at least one merged soft information sequence and the polar code sequence as the sequence similarity between the polar code sequence and the at least one set of soft information sequences includes: Determine the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence; The first similarity is determined based on at least one first sub-similarity, and the first similarity is used as the sequence similarity.

10. The method as described in claim 9, characterized in that, Determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence includes: For each of the at least one merged soft information sequence, perform the following operations: Multiple sequence element matching pairs are obtained based on a merged soft information sequence and the polar code sequence; wherein, the element position of the soft information sequence element in each sequence element matching pair in the merged soft information sequence is the same as the element position of the polar code sequence element in the polar code sequence. Based on the element distances corresponding to the multiple sequence element matching pairs, the sequence distance between the merged soft information sequence and the polar code sequence is determined. The sequence distance is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

11. The method as described in claim 10, characterized in that, The element distance is any one of Euclidean distance, Manhattan distance, and Chebyshev distance.

12. The method as described in claim 10, characterized in that, Determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence includes: For each of the at least one merged soft information sequence, perform the following operations: Sequence correlation calculation is performed on the merged soft information sequence and the polar code sequence to obtain the similarity coefficient between the merged soft information sequence and the polar code sequence; The similarity coefficient is used as the first sub-similarity between the merged soft information sequence and the polar code sequence.

13. The method as described in claim 12, characterized in that, The similarity coefficient is any one of the following: Pearson correlation coefficient, Spearman rank correlation coefficient, cosine coefficient, Kendall rank correlation coefficient, and Jacquard similarity coefficient.

14. The method as described in claim 10, characterized in that, Determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence includes: For each of the at least one merged soft information sequence, perform the following operations: Based on the product results of the sequence elements of the multiple sequence element matching pairs, the sum of the sequence element products between the merged soft information sequence and the polar code sequence is determined; wherein, the sum of the element products represents the correlation between the merged soft information sequence and the polar code sequence; Based on the sum of the product of the sequence elements, the first sub-similarity between the merged soft information sequence and the polar code sequence is determined.

15. The method as described in claim 14, characterized in that, Determining the first sub-similarity between each of the at least one merged soft information sequence and the polar code sequence includes: For each of the at least one merged soft information sequence, perform the following operations: A domain transformation is performed on the correlation sequence between the merged soft information sequence and the polar code sequence to obtain a domain-transformed correlation sequence; wherein, the correlation sequence includes: the product results of the multiple sequence element matching pairs with their respective sequence elements; Based on the domain transformation coefficients determined by the correlation sequence after the domain transformation, the first sub-similarity between the merged soft information sequence and the polar code sequence is determined.

16. The method according to any one of claims 1 to 7, characterized in that, Determining the DTX state of the transmitting end based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences includes: If the sequence similarity is less than the similarity threshold, then the sending end is determined to be in the DTX state; If the sequence similarity is greater than or equal to the similarity threshold, then it is determined that the sending end is not in the DTX state.

17. A DTX detection device, characterized in that, Applied to the receiving end, including: An information acquisition module is used to acquire at least one set of soft information sequences of the first information sent by the sending end; wherein each set of soft information sequences includes at least one soft information sequence, and each soft information sequence is determined based on the first information; A sequence processing module is used to obtain a polar code sequence based on the decoding information sequence determined by the at least one set of soft information sequences; A state detection module is used to determine the DTX state of the sending end based on the sequence similarity between the polar code sequence and the at least one set of soft information sequences.

18. 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, it implements the method as described in any one of claims 1 to 16.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 16.

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