Communication method and apparatus

Abstract

A communication method and apparatus, which are used for aligning the quantization bit widths of a sending device and a receiving device. The method comprises: a first device obtaining a first bit sequence; the first device performing, on the basis of a quantization bit width w, distribution matching on the first bit sequence, so as to obtain a second bit sequence, wherein the quantization bit width w is related to the length N of the second bit sequence or the maximum length Nmax of the second bit sequence; and the first device also being capable of performing channel coding and modulation on the basis of the second bit sequence, so as to obtain first information.

Description

A communication method and apparatus

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411774382.3, filed on December 2, 2024, entitled "A Communication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of mobile communication technology, and in particular to a communication method and apparatus. Background Technology

[0004] Distribution matching, also known as probabilistic shaping, is a common shaping technique. Based on distribution matching, a precoder can be cascaded before channel coding to map information bits to a bit sequence that follows a specific distribution. Then, during channel coding, systematic coding is used so that the aforementioned sequence satisfying the specific distribution ultimately appears directly in the coded sequence, thus shaping the final modulation symbol. Correspondingly, the receiver can perform dedistribution matching.

[0005] The correspondence between the input and output sequences of the distribution matching, as well as the correspondence between the input and output sequences of the solution distribution matching, is affected by the quantization bit width. If the transmitting and receiving devices use different quantization bit widths, the input bit sequence of the distribution matching will be inconsistent with the output bit sequence obtained by the solution matching. The receiving and transmitting devices will be unable to align the bit sequences, resulting in transmission failure.

[0006] Therefore, how to align the quantization bit widths of the transmitting and receiving devices has become an urgent technical problem to be solved. Summary of the Invention

[0007] This application provides a communication method and apparatus for aligning the quantization bit widths of a transmitting device and a receiving device.

[0008] Firstly, embodiments of this application provide a communication method, which can be executed by a first communication device, or in other words, the method can be applied to a first communication device. Unless otherwise specified, the "first communication device" in this application can refer to the first device itself, a component within the first device, or a logic module or software capable of implementing all or part of the first device. The first device can be a transmitting device. Specifically, the first device can be a terminal or a network device such as a base station. The components in this application may include, for example, at least one of a chip, a chip system, a processor, a transceiver, a processing unit, a transceiver unit, or other functional modules. Taking the first device as the executing entity as an example, the method includes:

[0009] A first device obtains a first bit sequence; the first device performs distribution matching on the first bit sequence according to the quantization bit width w to obtain a second bit sequence, wherein w is matched with the length N of the second bit sequence or the maximum length N of the second bit sequence. max The first device can also perform channel coding and modulation based on the second bit sequence to obtain the first information.

[0010] Based on this implementation, the first device can determine the length N of the second bit sequence or the maximum length N of the second bit sequence. max Determine the quantization bit width w. Similarly, the second device, i.e., the receiving device, can determine the quantization bit width w based on the length N of the second bit sequence or the maximum length N of the second bit sequence. max Determine the quantization bit width w to align the quantization bit widths of both the transmitting and receiving devices.

[0011] Where N and N max The integers are positive integers, and N ≤ N max w is a positive integer.

[0012] In this application, "distribution matching" can be replaced by names such as "probability shaping", "shaping", "precoding" or "information bit mapping".

[0013] In one possible implementation, the first device may perform distribution matching on the first bit sequence according to w to obtain a symbol sequence; the first device may also obtain the second bit sequence based on the symbol sequence through a first transformation.

[0014] Based on this implementation, the first device can output a symbol sequence through distribution matching and then transform the symbol sequence to obtain a second bit sequence. This symbol sequence can be converted from a symbol sequence to a bit sequence to obtain the second bit sequence. This symbol sequence can then be used as the output sequence of distribution matching.

[0015] In one possible implementation, w is also related to M, which is the maximum number of distinct values ​​in the distributed matching symbol sequence.

[0016] In other words, M is the size of the alphabet for distribution matching. Based on this implementation, the first device can determine the quantization bit width w according to M. The size of the alphabet for distribution matching is also the maximum number of symbols that the output sequence of distribution matching can contain.

[0017] In one possible implementation, w is positively correlated with M.

[0018] Based on this implementation, w increases as M increases.

[0019] In one possible implementation, w corresponds to the number of a symbol in the symbol sequence.

[0020] Based on this implementation, the symbol number is the output order of the symbols in the symbol sequence. It can be assumed that bits in a distributed, matched input sequence or symbols in an output sequence can correspond to multiple different quantization bit widths. For example, as the output order of symbols in the output sequence progresses from front to back, the value of w can be considered to decrease.

[0021] In one possible implementation, the first device may also acquire payload bits, the payload bits including the first bit sequence and the third bit sequence; the first device may also perform channel coding and modulation based on the second bit sequence and the third bit sequence.

[0022] Based on this implementation, it is possible to identify the distribution matching of the first bit vector in the payload bits, and to perform channel coding and modulation on the second and third bit vectors obtained after matching.

[0023] In one possible implementation, w is positively correlated with N, or w is positively correlated with N. max They are positively correlated.

[0024] Based on this implementation, w increases as N increases, or as N increases... max As w increases, w also increases.

[0025] In one possible implementation, w, N, and M satisfy: Δ is a constant;

[0026] Alternatively, the w, the N max And M satisfies: Δ is a constant.

[0027] Based on this implementation method, w can be accurately determined. Here, log represents the logarithmic operation to base 2. This indicates rounding up.

[0028] In one possible implementation, w is also related to the bit loss q of the first bit sequence.

[0029] Based on this implementation, when there is a loss in the input bit vector that allows for distribution matching, w can be determined based on the amount of loss during operation, i.e., q.

[0030] In one possible implementation, q is negatively correlated with w.

[0031] Based on this implementation, w decreases as q increases.

[0032] In one possible implementation, q and w satisfy the following relationship:

[0033] Alternatively, w = logM + log(1 / (2) q / N -1)).

[0034] Based on this implementation method, w can be accurately determined. Here, log represents the logarithmic operation to the base 2.

[0035] In one possible implementation, the first device may also receive second information, which is used to indicate w; or, the first device may also send second information, which is used to indicate w.

[0036] Based on this implementation, the second information can serve as an indication of w. That is, the first device can send or receive the indication of w to support the alignment of the value of w between the first device and the second device.

[0037] In one possible implementation, the first device may also receive third information, which is used to indicate one or more of N, M, Δ, or q; or, the first device may also send third information, which is used to indicate one or more of N, M, Δ, or q.

[0038] Based on this implementation, the first device can determine w according to one or more of N, M, Δ, or q. The third information can serve as indication information for one or more of N, M, Δ, or q. That is, the first device can send or receive indication information for one or more of N, M, Δ, or q to support the alignment of the values ​​of one or more of N, M, Δ, or q between the first device and the second device. Furthermore, the first device and the second device can determine w based on the same one or more of N, M, Δ, or q to support the alignment of the value of w between the first device and the second device.

[0039] Secondly, embodiments of this application provide a communication method, which can be executed by a second communication device, or in other words, the method can be applied to a second communication device. Unless otherwise specified, the "second communication device" in this application can refer to the second device itself, a component within the second device, or a logic module or software capable of implementing all or part of the second device. The second device can be a receiving device. Specifically, the second device can be a terminal or a network device such as a base station. The components in this application may include, for example, at least one of a chip, chip system, processor, transceiver, processing unit, transceiver unit, or other functional modules. Taking the second device as the executing entity as an example, the method includes:

[0040] The second device obtains the information to be decoded; the second device obtains a second bit sequence based on the information to be decoded; the second device performs dedistribution matching on the second bit sequence based on the quantization bit width w to obtain a first bit sequence, wherein w is related to the length N of the second bit sequence or the maximum length N of the second bit sequence. max Related. Among them, N and N max The integers are positive integers, and N ≤ N max w is a positive integer.

[0041] In one possible implementation, the second device can perform a second transformation on the second bit sequence to obtain a symbol sequence; the second device can perform dedistribution matching on the symbol sequence based on w to obtain the first bit sequence.

[0042] In one possible implementation, w is also related to M, which is the maximum number of distinct values ​​in the distributed matching symbol sequence.

[0043] In one possible implementation, w is positively correlated with M.

[0044] In one possible implementation, w corresponds to the number of a symbol in the symbol sequence.

[0045] In one possible implementation, the second device may also obtain a third bit sequence based on the information to be decoded; the second device may also obtain payload bits based on the first bit sequence and the third bit sequence.

[0046] In one possible implementation, w is positively correlated with N, or w is positively correlated with N. max They are positively correlated.

[0047] In one possible implementation, w, N, and M satisfy: Δ is a constant; or, w and N max And M satisfies: Δ is a constant. Here, log represents the logarithm to base 2. This indicates rounding up.

[0048] In one possible implementation, w is also related to the bit loss q of the first bit sequence.

[0049] In one possible implementation, q is negatively correlated with w.

[0050] In one possible implementation, q and w satisfy the following relationship:

[0051] or,

[0052] w = logM + log(1 / (2) q / N -1). Here, log represents the logarithmic operation with base 2.

[0053] In one possible implementation, the second device may also receive second information, which is used to indicate w; or, the second device may also send second information, which is used to indicate w.

[0054] In one possible implementation, the second device may also receive third information, which is used to indicate one or more of N, M, Δ, or q; or, the second device may also send third information, which is used to indicate one or more of N, M, Δ, or q.

[0055] The beneficial effects of the second aspect and its possible implementation methods can be found in the description of the beneficial effects of the first aspect and its corresponding implementation methods, and will not be repeated here.

[0056] Thirdly, a communication device is provided. The device can implement the method described in any possible implementation of any of the first or second aspects described above. The device possesses the functions of the first or second communication device described above. The device is, for example, a terminal device, a functional module within a terminal device, a network device, or a functional module within a network device, etc.

[0057] In one optional implementation, the device may include modules corresponding one-to-one with the methods / operations / steps / actions performed in any possible implementation of any of the first to second aspects. These modules may be hardware circuits, software, or a combination of hardware circuits and software. In another optional implementation, the device includes a processing unit (sometimes also called a processing module) and a communication unit (sometimes also called a transceiver module, communication module, etc.). The transceiver unit is capable of both sending and receiving functions. When the transceiver unit performs the sending function, it may be called a sending unit (sometimes also called a sending module); when the transceiver unit performs the receiving function, it may be called a receiving unit (sometimes also called a receiving module). The sending unit and the receiving unit may be the same functional module, which is called the transceiver unit and can perform both sending and receiving functions; or, the sending unit and the receiving unit may be different functional modules, with the transceiver unit being a collective term for these functional modules.

[0058] For example, when the apparatus is used to perform the method described in any one of the first to second aspects, the apparatus may include a communication unit and a processing unit.

[0059] Fourthly, embodiments of this application also provide a communication device, including a processor for executing a computer program (or computer-executable instructions) stored in a memory, such that when the computer program (or computer-executable instructions) is executed, the device performs the method as described in any possible implementation of any of the first to second aspects.

[0060] In one possible implementation, the processor and memory are integrated together;

[0061] In another possible implementation, the memory is located outside the communication device.

[0062] The communication device also includes a communication interface for communicating with other devices, such as sending or receiving data and / or signals. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0063] Fifthly, a computer-readable storage medium is provided for storing a computer program or instructions that, when executed, enable the implementation of the method described in any possible implementation of any of the first to second aspects, and the method shown in any possible implementation of the first aspect.

[0064] A sixth aspect provides a computer program product containing instructions that, when run on a computer, enables the method described in any possible implementation of any of the first to second aspects to be implemented.

[0065] In a seventh aspect, embodiments of this application also provide a communication device for performing the method described in any possible implementation of any of the first to second aspects described above.

[0066] Eighthly, a chip system is provided, comprising logic circuitry (or, as understood, a processor, which may include logic circuitry, etc.), and further comprising input / output interfaces. The input / output interfaces can be used to input messages or to output messages. The input / output interfaces can be the same interface, i.e., the same interface can implement both sending and receiving functions; or, the input / output interface includes an input interface and an output interface, the input interface being used to implement the receiving function, i.e., to receive messages; and the output interface being used to implement the sending function, i.e., to send messages. The logic circuitry can be used to perform operations other than the sending and receiving functions in any possible implementation of any of the first to second aspects described above; the logic circuitry can also be used to transmit messages to the input / output interfaces or to receive messages from other communication devices from the input / output interfaces. The chip system can be used to implement the methods described in any possible implementation of any of the first to second aspects described above. The chip system can be composed of chips or can include chips and other discrete devices.

[0067] Optionally, the chip system may also include a memory, which can be used to store instructions, and the logic circuits can call the instructions stored in the memory to implement the corresponding functions.

[0068] Ninth aspect, a communication method is provided, which may include the method implemented by a first communication device as shown in the first aspect and any possible implementation thereof, and the method implemented by a second communication device as shown in the second aspect and any possible implementation thereof.

[0069] A tenth aspect provides a communication system that may include a first communication device and a second communication device. The first communication device may be used to implement the method shown in the first aspect and any possible implementation thereof, and the second communication device may be used to implement the method shown in the second aspect and any possible implementation thereof.

[0070] The technical effects brought about by the third to tenth aspects above can be found in the descriptions of the beneficial effects of the corresponding solutions in the first and second aspects above, and will not be repeated here. Attached Figure Description

[0071] Figure 1 is a schematic diagram of the architecture of a wireless communication system provided in an embodiment of this application;

[0072] Figure 2(a) is a schematic diagram of a processing flow of information source and information sink provided in an embodiment of this application;

[0073] Figure 2(b) is a schematic diagram of a distribution matching and dedistribution matching process provided in an embodiment of this application;

[0074] Figure 2(c) is a schematic diagram of the constellation point distribution after shaping according to an embodiment of this application;

[0075] Figure 3 is a schematic diagram of a fence structure provided in an embodiment of this application;

[0076] Figure 4 is a schematic diagram of an interval of arithmetic coding based on calculation provided in an embodiment of this application;

[0077] Figure 5 is a flowchart illustrating a communication method provided in an embodiment of this application;

[0078] Figure 6 is a schematic diagram of a distributed matching process provided in an embodiment of this application;

[0079] Figure 7 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0080] Figure 8 is a schematic diagram of a solution distribution matching process provided in an embodiment of this application;

[0081] Figure 9 is a schematic diagram of another fence diagram structure provided in an embodiment of this application;

[0082] Figure 10 is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0083] Figure 11 is a schematic diagram of another communication device provided in an embodiment of this application. Detailed Implementation

[0084] In the embodiments of this application, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as an "example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the term "example" is intended to present concepts in a concrete manner. In the embodiments of this application, "of," "corresponding, relevant," and "corresponding" may sometimes be used interchangeably, and it should be noted that their intended meanings are consistent unless their distinction is emphasized.

[0085] The technical solutions of this application can be applied to various wireless communication systems, such as Universal Mobile Telecommunications System (UMTS), Wireless Local Area Network (WLAN), short-range wireless communication systems (such as sidelink, wireless fidelity, Wi-Fi, Bluetooth, etc.), wired networks, vehicle-to-everything (V2X) communication systems, device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, 4th generation (4G) mobile communication systems (such as Long Term Evolution (LTE) systems), LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Worldwide Interoperability for Microwave Access (WiMAX) communication systems, 5G mobile communication systems (such as New Radio (NR) systems), Future Communications systems, or other similar communication systems, without limitation. This application describes the communication system shown in Figure 1 as an example. When applying the technical solution of this application to other communication systems, the devices, components, modules, etc. in the embodiment can be replaced with corresponding devices, components, modules in other communication systems without limitation.

[0086] Figure 1 is a schematic diagram of the architecture of the communication system applied in the embodiments of this application. As shown in Figure 1, the communication system includes an access network 100. Optionally, the communication system may also include a core network 200 and an Internet 300. The access network 100 may include at least one network device, such as 110a and 110b in Figure 1, and may also include at least one terminal device, such as 120a-120j in Figure 1. Specifically, 110a is a base station, 110b is a micro-station, 120a, 120e, 120f, and 120j are mobile phones, 120b is a car, 120c is a fuel dispenser, 120d is a home access point (HAP) deployed indoors or outdoors, 120g is a laptop computer, 120h is a printer, and 120i is a drone. The same terminal device or network device can provide different functions in different application scenarios. For example, the mobile phones in Figure 1 are 120a, 120e, 120f and 120j. Mobile phone 120a can access base station 110a, connect to car 120b, communicate directly with mobile phone 120e and access HAP. Car 120b can access HAP and communicate directly with mobile phone 120a. Mobile phone 120f can access micro-station 110b, connect to laptop 120g and printer 120h. Mobile phone 120j can control drone 120i.

[0087] (1) Network equipment

[0088] A network device is a network-side device with wireless transceiver capabilities. A network device can be a device in a radio access network (RAN) that provides wireless communication capabilities to terminal devices; this is called RAN equipment. The RAN can be an access network within the 3rd Generation Partnership Project (3GPP), such as 4G, 5G, or future networks. The RAN can also be an open RAN (O-RAN or ORAN), a cloud radio access network (CRAN), or a communication network combining two or more of these.

[0089] RAN equipment can also be a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next-generation NodeB (gNB) in a 5G mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system, etc.

[0090] RAN equipment can also be modules or units that perform some of the functions of a base station. For example, it can be a central unit (CU), a distributed unit (DU), or a radio unit (RU). The CU performs the functions of the radio resource control (RRC) and PDCP protocols of the base station, and can also perform the functions of the service data adaptation protocol (SDAP). The CU can be further divided into a CU control plane (CP) (i.e., CU-CP) and a CU user plane (UP) (i.e., CU-UP). The DU performs the functions of the RLC and MA layers of the base station, and can also perform some or all of the physical layer functions. For specific descriptions of the above protocol layers, please refer to the relevant 3GPP technical specifications. CU and DU can be set up separately, or they can be included in the same network element, such as in a baseband unit (BBU). The RU can be included in radio frequency equipment or radio frequency units, such as in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH). In different systems, CU, DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, and RU can also be called O-RU. Any of the CU (or CU-CP, CU-UP), DU, and RU units in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules. The RA device can be a macro base station (as shown in Figure 1, 110a), a micro base station or an indoor station (as shown in Figure 1, 110b), or a relay node or donor node, etc. The embodiments of this application do not limit the specific technology or specific device form used in the network equipment.

[0091] In the embodiments of this application, the functions of the network device can be executed by modules (such as chips) within the network device, or by a control subsystem that includes the functions of the network device. This control subsystem, which includes the functions of the network device, can be a control center in the aforementioned application scenarios such as smart grids, industrial control, intelligent transportation, and smart cities.

[0092] (2) Terminal equipment

[0093] A terminal device is a user-side device with wireless transceiver capabilities. Terminal devices can also be called terminals, user equipment (UE), mobile stations, mobile terminals, etc. Terminal devices can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, intelligent transportation, and smart cities. Terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, drones, helicopters, airplanes, ships, robots, robotic arms, smart home devices, etc. In the embodiments of this application, the device used to implement the functions of the terminal device can be the terminal device itself, or it can be a device that supports the terminal device in implementing that function, such as a chip system or a combination of devices or components that can implement the functions of the terminal device. This device can be installed in the terminal device. The embodiments of this application do not limit the specific technology or specific device form used in the terminal device.

[0094] In this embodiment of the application, the functions of the terminal device can also be performed by modules (such as chips or modems) in the terminal device, or by a device containing the functions of the terminal device.

[0095] Network devices and terminal devices can be fixed in location or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and artificial satellites. The embodiments of this application do not limit the application scenarios of the network devices and terminal devices.

[0096] The roles of network devices and terminal devices can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile network device. For terminal devices 120j that access the wireless access network 100 via 120i, terminal device 120i is a network device; however, for network device 110a, 120i is a terminal device. That is, 110a and 120i communicate via a wireless air interface protocol. Of course, 110a and 120i can also communicate via a network device-to-network device interface protocol. In this case, relative to 110a, 120i is also a network device. Therefore, both network devices and terminal devices can be collectively referred to as communication devices. 110a and 110b in Figure 1 can be called communication devices with network device functions, and 120a-120j in Figure 1 can be called communication devices with terminal device functions.

[0097] Network devices and terminal devices, network devices and network devices, and terminal devices can communicate through licensed spectrum, unlicensed spectrum, or both simultaneously, without limitation.

[0098] The network architecture and business scenarios described in this application are intended to more clearly illustrate the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0099] The following is an explanation of the relevant terms used in the embodiments of this application. Unless otherwise specified, these explanations are provided to support the meaning of the relevant terms and to make the embodiments of this application easier to understand, and should not be regarded as a strict limitation of the relevant terms within the scope of protection claimed by this application.

[0100] (1) Channel coding and channel decoding

[0101] Figure 2(a) is a schematic diagram of a processing flow for the source and sink. As shown in Figure 2(a), the transmitting end (i.e., the source) obtains the bit sequence to be encoded (i.e., the information bit sequence) through source coding, and then performs channel coding on the information bit sequence to obtain the encoded bit sequence. Correspondingly, after the receiving end (i.e., the sink) obtains the symbol sequence to be decoded, it performs channel decoding on the symbol sequence to be decoded to obtain the information bit sequence, and then performs source recovery on the information bit sequence to obtain useful information.

[0102] Since source coding does not consider interference resistance, if the bit sequence output from source coding is directly transmitted through the channel, noise interference in the channel will cause bit errors, reducing communication reliability. Therefore, channel coding, which encodes the bit sequence output from source coding again, can improve communication reliability. Channel decoding is the inverse process of channel coding.

[0103] There are various channel coding methods, such as using polar codes or LDPC codes. Polar codes were chosen as the control channel coding method in the 5G standard. Polar codes are a coding scheme that can be rigorously proven to "achieve" the Shannon channel capacity, and have the advantages of good decoding performance and low complexity. LDPC codes were chosen as the data channel coding method in the 5G standard. LDPC codes are linear block codes with a sparse parity-check matrix, which not only have good performance approaching the Shannon limit, but also have low decoding complexity and flexible structure.

[0104] (2) Modulation and demodulation

[0105] Referring to Figure 2(a), the transmitting end can also map the encoded bit sequence to the modulation symbol sequence, and then send the modulation symbol sequence; correspondingly, the receiving end can receive the modulation symbol sequence and then demodulate it to obtain the symbol sequence to be decoded.

[0106] Modulation refers to the process by which the transmitting end maps the encoded bit sequence to a constellation based on a constellation diagram to obtain a modulated symbol sequence. Demodulation is the reverse process of modulation. Common modulation methods include quadrature amplitude modulation (QAM) and amplitude shift keying (ASK) modulation.

[0107] For example, the encoded bit sequence can be mapped to the modulation symbol sequence by referring to a lookup table or according to a preset rule. Here, only a lookup table is used as an illustration. As shown in Table 1, it is a bit mapping relationship of 8ASK. During the modulation process, the modulation symbol x is determined according to bits b0, b1 and b2, which is used as the modulation symbol to be transmitted.

[0108] Table 1: Mapping between bit values ​​and modulation symbols

[0109] When using 8ASK modulation, the encoded bit sequence can be mapped to a modulation symbol sequence according to the bit values, referring to Table 1. When using QAM (such as 16QAM, 64QAM, etc.) modulation, the QAM constellation diagram has real and imaginary parts, which can be mapped to the modulation symbol sequence according to Table 1 or other tables, respectively. This application does not elaborate on this further.

[0110] It should be noted that different bits have different functions when mapping the encoded bit sequence to the modulation symbol sequence. For example, in Table 1, bit b0 is used to determine the quadrant of the modulation symbol, so bit b0 is also called the symbol bit. Bits b1 and b2 are used to determine the amplitude of the modulation symbol, so bits b1 and b2 are also called amplitude bits. Furthermore, the transmission reliability of bits b0, b1, and b2 decreases in that order, that is, the transmission reliability satisfies the following relationship: transmission reliability of b0 > transmission reliability of b1 > transmission reliability of b2.

[0111] It should be noted that the values ​​of the modulation symbols in Table 1 (i.e., the magnitude of x) are only examples. In actual applications, x can be adjusted according to power consumption requirements, such as scaling up or down the multiple x values ​​shown in Table 1 by the same proportion.

[0112] (3) Distribution matching, or probability shaping.

[0113] Higher-order modulation maps multiple bits to the same modulation symbol, thereby further improving spectral efficiency. Common higher-order modulation schemes include 16QAM and 64QAM, without specific limitations. 16QAM maps 4 bits to one modulation symbol, while 64QAM maps 6 bits to one modulation symbol.

[0114] In higher-order modulation, different symbols may have different energies. As shown in Table 1 above, the energies of the modulation symbols from highest to lowest are: modulation symbol -7 (modulation symbol 7), modulation symbol -5 (modulation symbol 5), modulation symbol -3 (modulation symbol 3), and modulation symbol -1 (modulation symbol 1). Among them, modulation symbol -7 has the same energy as modulation symbol 7, modulation symbol -5 has the same energy as modulation symbol 5, modulation symbol -3 has the same energy as modulation symbol 3, and modulation symbol -1 has the same energy as modulation symbol 1.

[0115] By transmitting more low-energy symbols and fewer high-energy symbols, average energy can be saved. Theoretical analysis shows that for a Gaussian white noise channel, the information transmitted per unit energy is maximized when the transmitted symbol distribution follows a Gaussian distribution. Compared to a uniform distribution, the Gaussian distribution has the best performance, theoretically offering a performance gain of 1.53 dB.

[0116] Distribution matching, also known as probabilistic shaping, is a common shaping technique. A typical flowchart is shown in Figure 2(b). Figure 2(b) illustrates another processing flow for the source and sink. The difference between Figure 2(b) and Figure 2(a) is that in Figure 2(b), the transmitter needs to perform distribution matching, and the receiver needs to perform dedistribution matching (or deprobabilistic shaping). As shown in Figure 2(b), by cascading a precoder before channel coding, the information bits are mapped (or "shaped") to a bit sequence that follows a specific distribution. Therefore, the precoder is also called a distribution matcher (DM). Then, during channel coding, systematic coding is used, so that the sequence satisfying the specific distribution ultimately appears directly in the coded sequence, thus shaping the final modulation symbol. As an example, the constellation point distribution after "shaping" is shown in Figure 2(c). It can be seen that the probability of low-energy symbols appearing is higher than that of high-energy symbols.

[0117] In this application, distribution matching can also be simply referred to as shaping, which will be explained uniformly here and will not be elaborated on later.

[0118] For example, given 500 information bits, 100 information bits are not distributed and the remaining 400 information bits are distributed to obtain a bit sequence that follows a specific distribution, which consists of 512 bits. Then, channel coding is performed on the 100 information bits and the resulting 512 bits.

[0119] One method for implementing distribution matching is to obtain a symbol sequence based on arithmetic coding techniques, and then convert the symbol sequence into a bit sequence.

[0120] (4.1) One distribution matching scheme based on arithmetic coding is approximate enumerative sphere shaping (AESS).

[0121] Symbolic AESS can directly generate N max Long letter sequences, such as the alphabet A = {1 3 5 7}, where 1, 3, 5, and 7 can each be a letter. Letters can represent possible symbols (or values) in the distribution matching output sequence, that is, the maximum number of different values ​​in the symbol sequence output by the distribution matching. Taking the alphabet A = {1 3 5 7} as an example, the possible symbols in the symbol sequence output by the distribution matching are 1, 3, 5, and 7. Any output sequence of the distribution matching may contain some letters, for example, the output sequence is (31), meaning that each sequence is not required to contain all the letters.

[0122] Wherein, the normalized energy corresponding to the letter 'a' is E(a) = (a 2 -1) / 8. For example, the energies corresponding to {1 3 5 7} are {0 1 3 6}, which are stored with a length of N. max Energy less than or equal to E max A trellis graph, composed of approximately the number of letter sequences, can achieve a distribution matching effect. Using N... max =2,E max For example, if the value is 3, the number of rows and columns of the fence diagram are E. max +1 and N max +1, the element T(E,n) in the E-th row and n-th column represents a length of N. max The number of letter sequences with energy not exceeding E and an approximate value of -n, with all elements in the last column of the fence graph being 1. The elements in the nth column of the fence graph can be obtained by summing no more than |A| elements in the (n+1)th column, where |A| is the size of the alphabet. The size of the alphabet represents the number of possible letters in the output sequence; for example, if A = {1 3 5 7}, then |A| = 4.

[0123] Specifically, For example, if the sum is T(E,n) can be Therefore, T(E,n) can be represented by w bits (s0,…,s). w-1 The values ​​of w and the exponent t are determined. w is a positive integer, and t is an integer. i = 0, 1, 2, ...

[0124] w can be referred to as quantization bit width, precision, or number of quantization bits.

[0125] In this application, the arithmetic coding based on AESS can include infinite-precision algorithms and finite-precision algorithms. The infinite-precision algorithm uses an infinite-precision fence graph, and the finite-precision algorithm uses a finite-precision fence graph.

[0126] Figure 3 shows a fence diagram with infinite precision, as indicated by number (a) in Figure 3. In this diagram, the element in row E and column n... Infinite precision can also be understood as using the maximum precision. In addition, number (b) in Figure 3 shows a fence diagram with finite precision, i.e., w=1.

[0127] The input sequence for probabilistic shaping is a K-length bit sequence. For example, during the probability shaping process, one can... Arranged in lexicographical order, for example Serial number K is a positive integer. The output sequence is obtained based on the elements T(E,n) of the fence graph. Since the energy of the output sequence does not exceed E... max This achieves the effect of reducing the energy of the amplitude sequence and determining the output amplitude sequence. The process is as follows:

[0128] With K=2 and For example, The output amplitude sequence is

[0129] Since the encoded output sequence is related to the element T(E,n) of the fence graph, and w affects the value of T(E,n), w will affect the value of the encoded output sequence of the symbol-level AESS.

[0130] (4.2) A distribution matching scheme based on arithmetic coding is computation-based arithmetic coding.

[0131] In computation-based arithmetic coding, B candidate output letter sequences divide [0,1) into B disjoint intervals [b... j ,b j+1 ), 0=b0≤b1…≤b B =1, [b j ,b j+1 ) is the interval corresponding to the j-th sequence. K-length bit-coded input sequence Arranged in dictionary order. For example, If u i =v i ,i≤j,u j >v j , A real number between [0, 1] Where i is The lexicographical index. For example, the lexicographical order of 10 is 2, corresponding to the real value 2 / 4, which is the encoded input sequence. Corresponding encoded output sequence If and only if The corresponding real number is The corresponding interval [b j ,b j+1 (See Figure 4, which uses K=5 as an example.)

[0132] A constant-composition distribution matcher (CCDM) is a computationally-based arithmetic coding distribution matcher whose output sequence has fixed components. For example, in an ordered alphabet A = {a0 = 0, a1 = 1}, a... iThis represents the i-th symbol in the alphabet of the DM output sequence. As shown in Figure 4, the components of the 5-length sequence c = {1,0,0,0,0} are: the number of letters of type 0 (0) is m0 = 4, and the number of letters of type 1 (1) is m1 = 1. The number of each letter in the CCDM encoded output sequence is fixed and is called the target component. For example, other 5-length sequences with the same components as {1,0,0,0,0} include {0,1,0,0,0}, {0,0,1,0,0}, {0,0,0,1,0}, and {0,0,0,0,1}. The number of sequences with the same components is... CCDM's N-length output letter sequence Arranged in lexicographical order, each interval has the same length. B represents the number of sequences in the same group. For example, as shown in Figure 4, the lexicographical order of 00100 is 2, corresponding to the interval [2 / 5, 3 / 5].

[0133] The corresponding interval width can be calculated recursively. Representative sequence Corresponding interval width in For c s The number of corresponding letters in the components, for c s The corresponding number of letters. s represents the bit's number in the first bit sequence. It represents the empty set. It can be called the first ratio.

[0134] Computation-based arithmetic coding can include two types of algorithms: finite precision algorithms and infinite precision algorithms.

[0135] In finite-precision arithmetic coding Reserve the w bits, for example That is, retain 2 significant digits, therefore take w refers to the quantization bit width, precision, or number of quantization bits. In infinite-precision arithmetic coding, Keep the full length.

[0136] It is evident that w affects the interval width, which in turn affects the value of the CCDM's encoded output sequence.

[0137] In summary, the correspondence between the input and output sequences of the current distribution matching, as well as the correspondence between the input and output sequences of the dedistribution matching, are both affected by the quantization bit width w. If the transmitting and receiving devices use different w, the input bit sequence of the distribution matching will be inconsistent with the output bit sequence obtained by the dedistribution matching, and the receiving and transmitting devices will be unable to align the bit sequences, resulting in transmission failure.

[0138] Therefore, how to align the quantization bit widths of the transmitting and receiving devices has become an urgent technical problem to be solved.

[0139] This application provides a communication method and apparatus for implementing distribution matching and dedistribution matching based on quantization bit width, so that the transmitting device and the receiving device use the same quantization bit width to perform distribution matching and dedistribution matching respectively.

[0140] Figure 5 is a schematic flowchart of a communication method provided in an embodiment of this application. The method is executed by a first device. Unless otherwise specified, the "first device" in this application can refer to the first device itself (e.g., a terminal device or a network device), a component within the first device (e.g., a functional module, communication module, processor, circuit, chip, or chip system), or a logic module or software capable of implementing all or part of the functions of the first device. Furthermore, for a network device, components may also include CU, DU, or RU.

[0141] The first device can function as a transmitting device, used to perform actions related to transmitting signals, such as performing distribution matching. Specifically, the first device can be a terminal and / or a network device (such as a base station). For example, in uplink communication between a terminal and a base station, the first device can be a terminal. Similarly, in downlink communication between a terminal and a base station, the first device can be a network device. Furthermore, this application does not exclude applications in terminal-to-terminal communication scenarios, in which case both the signal transmitting device and the signal receiving device can be terminals.

[0142] Additionally, the second device can act as a receiving device to receive information from the first device. For example, this information can be sent by the first device using the method shown in Figure 5. The quantization bit width used by the first device for distribution matching is the same as the quantization bit width used by the second device for distribution matching.

[0143] Taking the first device as the executing entity as an example, the method includes the following steps:

[0144] S101: The first device obtains the first bit sequence.

[0145] The first bit sequence can be some or all of the bits in the payload bits. The payload bits can be the bit sequence that the first device carries over to transmit.

[0146] Optionally, in S101, the first device may use a portion of the bits in the payload bits as the first bit sequence.

[0147] S102: The first device performs distribution matching on the first bit sequence according to the quantization bit width w to obtain the second bit sequence. Wherein, w is related to the length N of the second bit sequence or the maximum length N of the second bit sequence. max related.

[0148] The length N of the second bit sequence can represent the number of bits in the second bit sequence. max This represents the maximum number of bits in the second bit sequence. N and N max The integers are positive integers, and N ≤ N max .

[0149] As an example, w is positively correlated with the length N of the second bit sequence, or w is positively correlated with the maximum length N of the second bit sequence. max They are positively correlated. That is, as N or N... max Increase, w increases.

[0150] For example, for AESS-based distribution matching, w and N max It can satisfy: Δ is a constant. We can set Δ = -1.

[0151] For example, for computationally finite-precision arithmetic codes, w and N can satisfy: Δ is a constant. We can let Δ = 2.

[0152] As shown in Figure 6, the payload bits to be transmitted by the first device can include a first bit sequence and a third bit sequence. In S102, the first device can perform distribution matching on the first bit sequence according to the quantization bit width w to obtain the second bit sequence.

[0153] Specifically, the first bit sequence can be processed by distribution matching to obtain a symbol sequence, which is the output sequence of the distribution matching. The first device can further perform a first transformation on the symbol sequence to obtain a second bit sequence. This first transformation can be, for example, a transformation from a symbol sequence to a bit sequence, such as an analog-to-digital converter.

[0154] As is understandable, Figure 6 uses a precoder performing distribution matching as an example. This precoder may also include a symbol bit converter for performing the first transformation.

[0155] In S102, w is related to the length N of the second bit sequence, which can also be replaced by: w being related to the length N of the symbol sequence. symb Related. Among them, N symb Associated with N, for example, Nsymb N is the length of the symbol sequence before the first transformation, and N is the length of the second bit sequence after the first transformation.

[0156] Or the maximum length N of the second bit sequence max Related, it can also be replaced by: w and the maximum length N of the symbol sequence symb-max Related. Among them, N symb-max With N max Related, for example, N symb-max To determine the maximum length of the symbol sequence before the first transformation, N max The maximum length of the second bit sequence after performing the first transformation.

[0157] In one possible implementation, w can also be related to M, which is the maximum number of distinct values ​​in the symbol sequence of the distribution matching. Here, M can be understood as the size of the alphabet for the distribution matching. Each letter represents a possible symbol value in the symbol sequence output by the distribution matching.

[0158] For example, w is positively correlated with M. That is, as M increases, w increases.

[0159] In one possible example, w is positively correlated with N and also positively correlated with M. For instance, in the case of a lossless first bit sequence of a distribution-matched input, w, N, and M satisfy: Δ is a constant. It can also be described as w versus N. symb Positively correlated and positively correlated with M. For example, w, N symb And M satisfies: Δ is a constant. This indicates rounding up.

[0160] Optionally, Δ can be related to the distribution matching method. For example, for AESS-based distribution matching, Δ can be set to -1. Or, for computation-based arithmetic coding, Δ can be set to 2.

[0161] In another possible example, w and N max Positively correlated and positively correlated with M. For example, in the case of a lossless first bit sequence of a distribution-matched input, w and N... max And M satisfies: Δ is a constant. It can also be described as w versus N. symb-max Positively correlated and positively correlated with M. For example, w, N symb-max And M satisfies: Δ is a constant. This indicates rounding up.

[0162] Optionally, Δ can be related to the distribution matching method. For example, for AESS-based distribution matching, Δ can be set to -1. Or, for computation-based arithmetic coding, Δ can be set to 2.

[0163] In another possible example, if the first bit sequence of the input allowed for distribution matching has a certain loss, then w can also be related to the bit loss q of the first bit sequence. The bit loss can define the number of bits in the first bit sequence that can be lost. In scenarios with power constraints, a certain bit loss can be allowed in the distribution matching process. For example, w is negatively correlated with q.

[0164] An example of w relating to the bit loss q could be: it could be based on a threshold q of the bit loss q. th Determine w. For example, w can be configured such that q satisfies q ≤ q th q th This represents the bit loss threshold. Here, q can be determined through simulation or calculated using a formula. For example, q≤f(N) max E max ,M,w), or q≤f(N,E) max ,M,w). f(x) represents a function related to x.

[0165] For example, taking the distributed matching scheme based on AESS as an example, we can define R = q / N max Let q be the code rate loss for the distribution-matched input bit sequence. Here, q is the maximum length K of the input bit sequence supported by the infinite-precision fence graph. max The difference between the maximum input bit sequence length supported by the finite-precision fence graph and the maximum input bit sequence length. For example, M = 2, N max =64,E max =16, the maximum input bit sequence length K' supported by an infinite-precision fence graph. max When ω = 49 and w = 5, the maximum length of the input bit sequence supported by the finite-precision fence graph is K. max =47, then q=K' max -K max =2, correspondingly,

[0166] In this example, we can let q ≤ f(N) max E max M,w)=-N max log(1-M*2 1-w That is, w can be derived from N. max M and q together determine w. According to the above formula, w can satisfy:

[0167] For example, taking computation-based arithmetic coding, the bit loss q can be taken as K corresponding to computation-based infinite-precision arithmetic coding. max K corresponding to computation-based finite-precision arithmetic coding max difference.

[0168] Among them, the computation-based infinite-precision arithmetic code corresponds to B represents the number of candidate output sequences for the arithmetic code. The finite-precision arithmetic code based on computation corresponds to... Output the letter sequence for arithmetic encoding. That is... It is one of the B candidate output sequences. This indicates rounding down to the nearest integer.

[0169] In this example, we can let q ≤ f(N, E) max ,M,w)=Nlog(1+M*2 -w That is, w can be determined by N, M, and q. According to the above formula, w can satisfy: w = logM + log(1 / (2 q / N -1)).

[0170] Alternatively, w can be considered to be related to the code rate loss R of the first bit sequence. w can be configured such that R satisfies R ≤ R th R th This represents the threshold for bit rate loss. Here, q can be determined through simulation or calculated using a formula. For example, R ≤ g(N) max E max ,M,w), or R≤g(N,E) max ,M,w). g(x) represents a function related to x.

[0171] For example, taking a distributed matching scheme based on AESS as an example, R = q / N max We can set R ≤ g(N) max E max ,M,w). For example, R≤g(N) max E max ,M,w)=-log(1-M*2 1-w That is, w can be derived from N. max It is jointly determined by M and R.

[0172] For example, taking computation-based arithmetic coding, R = q / N. We can let R ≤ g(N, E) max For example, R≤g(N,E). max ,M,w)=log(1+M*2 -w That is, w can be determined by N, M and R together.

[0173] In one possible embodiment, the quantization bit width w can be understood as a value applicable to all bits in the first bit sequence, that is, the first device can use the same quantization bit width to perform distribution matching on all bits in the first bit sequence to obtain the highest precision.

[0174] Furthermore, to reduce power consumption, the quantization bit width can also correspond to the symbol numbers in the symbol sequence. The symbol numbers represent the output order of the symbols in the symbol sequence. It can be assumed that bits in a distributed, matched input sequence or symbols in an output sequence can correspond to multiple different quantization bit widths. For example, as the symbols are output in the output sequence from beginning to end, the value of w can be considered to decrease.

[0175] As an example, the nth symbol in the sequence symb The quantization bit width corresponding to each symbol is denoted as w′=w-Δw, where Δw is related to n. symb The value of n is related. symb n is a positive integer. symb The symbols in the symbol sequence output by the distribution matching are numbered, with the symbol sequence length being N. symb For example, n symb =0, 1, 2...N symb -1. For example, n symb The larger the value, the larger Δw becomes. That is, the first device can determine the quantization bit width w′ based on the number of the distributed-matched output symbol sequence (or the number of the already output symbol sequence), and perform distribution matching on the bits in the first bit sequence based on the quantization bit width w′. For example, as n... symb Increment from 0 to N symb -1, Δw gradually increases from 0. That is, the quantization bit width corresponding to the symbol with index 0 in the distribution-matched output can be smaller than that of the symbol with index N. symb The quantization bit width corresponding to the sign of -1.

[0176] As another example, the nth symbol in the symbol sequence symb The quantization width corresponding to each bit is w, meaning that for each symbol in the symbol sequence, the first device can independently determine its quantization width. At this time, the quantization width w can be related to n. symb Furthermore, as described in this application, the quantization bit width w can also be related to N, N max It relates to one or more of M, Δ, or q.

[0177] With w and n symb N max For example, related to M, the value of w can be from the set The value selected, for example, with n symb Increment from 0 to N symb -1 allows you to select a decreasing value of w from this set. For example, when nsymb When = 0, take When n symb =N symb When -1, w = 1. Alternatively, it can be considered that p consecutive symbols correspond to the same quantization bit width; therefore, the quantization bit width w corresponding to p consecutive symbols in the symbol sequence can be related to the symbol number, N... max It relates to M and p, where p is a positive integer greater than 1.

[0178] S103: The first device performs channel coding and modulation based on the second bit sequence to obtain the first information.

[0179] As shown in Figure 6, the first device can encode and modulate the second and third bit sequences to obtain the modulated first information. For example, the first information can be a modulated symbol sequence obtained through encoding and modulation.

[0180] Figure 7 is a schematic flowchart of a communication method provided in an embodiment of this application. The method is executed by a second device. Unless otherwise specified, the "second device" in this application can refer to the second device itself (e.g., a terminal device or a network device), a component within the second device (e.g., a functional module, communication module, processor, circuit, chip, or chip system), or a logic module or software capable of implementing all or part of the functions of the second device. Furthermore, for network devices, components may also include CU, DU, or RU.

[0181] The second device can serve as a receiving device to perform reception-related actions, such as distributive matching. Specifically, the second device can be a terminal and / or a network device (such as a base station). For example, in uplink communication between a terminal and a base station, the second device can be a network device. Similarly, in downlink communication between a terminal and a base station, the second device can be a terminal. Furthermore, this application does not exclude applications in terminal-to-terminal communication scenarios, where both the signal transmitting device and the signal receiving device can be terminals.

[0182] Taking the second device as the executing entity as an example, the method includes the following steps:

[0183] S201: The second device obtains the information to be decoded.

[0184] The information to be decoded can be obtained by the second device receiving a signal sent by the first device through a receiver. For example, the first device can send a signal corresponding to the first information in S103 through a transmitter, and the second device can obtain the information to be decoded after receiving the signal through a receiver.

[0185] The information to be decoded is, for example, a sequence of modulated symbols to be decoded and demodulated.

[0186] S202: The second device obtains the second bit sequence based on the information to be decoded.

[0187] As an example, in S202, the second device can perform decoding and demodulation operations on the information to be decoded to obtain a bit sequence. This bit sequence includes a second bit sequence and a third bit sequence. The second device can also obtain the second bit sequence from the bit sequence after the decoding and demodulation operations.

[0188] The second device can determine the positions of the second bit vector and / or the third bit vector in the bit sequence according to the protocol definition or a predefined configuration. For example, the second device can use the last 200 bits of the bit sequence obtained from decoding and demodulation operations as the second bit vector, according to the protocol definition.

[0189] S203: The second device performs dedistribution matching on the second bit sequence according to the quantization bit width w to obtain the first bit sequence.

[0190] The quantization bit width can satisfy the description of the quantization bit width introduced in S102, and will not be repeated here.

[0191] The second device can perform a second transformation on the second bit vector to obtain a symbol sequence. This second transformation can be, for example, a conversion from a bit sequence to a symbol sequence, such as a digital-to-analog conversion.

[0192] The symbol sequence can be used as the input sequence for dedistribution matching, and correspondingly, the first bit vector can be used as the output sequence for dedistribution matching. In S203, the second device can perform dedistribution matching on the symbol sequence according to the quantization bit width w and output the first bit sequence.

[0193] Following S203, the second device can also obtain the payload bits based on the first bit sequence and the third bit sequence. These payload bits are the bit sequence sent by the first device, i.e., the payload data.

[0194] The relationship between the information to be decoded, the third bit sequence, the second bit sequence, and the first bit sequence in Figure 7 can be seen in Figure 8.

[0195] Based on the flowcharts in Figures 5 and 7, when the first device communicates with the second device, the quantization bit widths used for distribution matching and dedistribution matching can be aligned. That is, the quantization bit width used by the first device for distribution matching is the same as the quantization bit width used by the second device for dedistribution matching.

[0196] It is understandable that the first device and the second device can exchange the value of w, so that the first device and the second device use the same value of w. Specifically, the first device can perform distribution matching based on this value, and correspondingly, the second device can perform dedistribution matching based on this value of w.

[0197] As an example, prior to S102, the first device can determine the values ​​of N and N based on the given information. max The first device can determine w by selecting one or more of M, Δ, or q. After determining w, the first device can also send second information to the second device. This second information indicates the value of w, meaning the second device can determine w based on the received second information. Therefore, the second device can obtain w based on the second information before step S203. Optionally, the first device can be a network device, and correspondingly, the second device can be a terminal device.

[0198] Optionally, the second information may carry the value of w, the index or number of the value of w among multiple possible values, etc., without specific limitations.

[0199] As another example, it can be determined by a second device based on N, N max The second device determines w by one or more of M, Δ, or q. After determining w, the second device may also send second information to the first device to indicate the value of w. The first device can obtain w based on the second information before step S102. Optionally, the second device can be a network device, and correspondingly, the first device can be a terminal device.

[0200] Optionally, the second information may carry the value of w, the index or number of the value of w among multiple possible values, etc., without specific limitations.

[0201] Furthermore, before communication, the first device can determine the values ​​of N and N. max w can be determined by one or more of N, M, Δ, or q. Additionally, the second device can be determined based on N, N... max w is determined by one or more of M, Δ, or q. The first device can interact with the second device N, N... max The value of one or more of M, Δ, or q is selected to ensure that the first device and the second device use the same w value.

[0202] As an example, prior to S102, the first device can determine the values ​​of N and N based on the given information. max The first device can also send a third message to the second device, which can be used to indicate the value of w. That is, the second device can determine N, N', M', Δ, or q based on the received third message. max One or more of M, Δ, or q, can be further determined before S203 based on N, N max w is determined by one or more of M, Δ, or q. Optionally, the first device can be a network device, and correspondingly, the second device can be a terminal device.

[0203] Optionally, the third information may carry N, N maxThe value of one or more of M, Δ, or q, N, N max The index or number of one or more of the values ​​of M, Δ, or q among multiple possible values ​​is not specifically limited.

[0204] As another example, it can be determined by a second device based on N, N max The second device can also send third information to the first device, which can be used to indicate the value of w. That is, the first device can determine N, N', M', Δ, or q based on the received third information before S102. max One or more of M, Δ, or q, can be further determined based on N, N max w is determined by one or more of M, Δ, or q. Optionally, the second device can be used as a network device, and correspondingly, the first device can be used as a terminal device.

[0205] Alternatively, N and N can be defined through a protocol. max The value of N, M, Δ, or q is determined by the first device before S102, according to the definition of the protocol. max One or more of M, Δ, or q, can be further determined based on N, N max w is determined by one or more of M, Δ, or q. Additionally, the second device can also determine N, N', and N'' according to the protocol definition. max One or more of M, Δ, or q, can be further determined based on N, N max w is determined by one or more of M, Δ, or q.

[0206] In one possible implementation, distribution matching based on AESS can directly generate N. max Long output symbol sequence. A symbol sequence can also be called a letter sequence. For example, assuming the alphabet is A = {1 3 5 7}, the normalized energy corresponding to any letter 'a' in the alphabet is E(a) = (a... 2 -1) / 8. With N max =2,E max For example, if the value is 3, the number of rows and columns of the fence diagram are E. max +1 and N max +1, the element T(E,n) in the E-th row and n-th column represents a length of N. max -n, and an approximation of a symbol sequence whose energy does not exceed E, with the last column of the fence diagram being 0 or 1.

[0207] The elements in the nth column of the fence diagram can be obtained by the sum of no more than M = |A| elements in the (n+1)th column, where |A| is the size of the alphabet. The size of the alphabet represents the number of possible letters in the output sequence. For example, if A = {1 3 5 7}, then |A| = 4.

[0208] Specifically, For example, if the sum is T(E,n) can be Therefore, T(E,n) can be represented by w bits (s0,…,s). w-1 The fence diagram and the exponent t are determined. Flipping the fence diagram horizontally or vertically yields an equivalent fence diagram, without specific limitations.

[0209] The maximum length of the input sequence for distribution matching is...

[0210] For example, in step S102, where the first device performs distribution matching on the first bit sequence, the first bit sequence is the input sequence for distribution matching, and the symbol sequence described in S102 is the output sequence for distribution matching.

[0211] In Example 1, the quantization bit width w used for distribution matching can be based on N. max And M is determined. Wherein, as described in S102, w and N... max They are positively correlated, and also positively correlated with M. For example, Δ can be positively correlated with the maximum height of the fence diagram. For example, Δ = -1. For instance, when M = 2,

[0212] Optionally, the quantization bit width w in Embodiment 1 can also be related to the bit loss q of the first bit sequence. Referring to the description in S102, q can be the maximum input bit sequence length K supported by the infinite precision fence graph. max The difference between the maximum input bit sequence length supported by the finite-precision fence graph and the maximum input bit sequence length. For example, M = 2, N max =64,E max =16, the maximum input bit sequence length K' supported by an infinite-precision fence graph. max When ω = 49 and w = 5, the maximum length of the input bit sequence supported by the finite-precision fence graph is K. max =47, then q=K' max -K max =2, correspondingly, We can let q≤f(N) max E max M,w)=-n max log(1-M*2 1-w That is, w can be derived from N. max M and q together determine w. w can satisfy:

[0213] Alternatively, the quantization bit width w in Example 1 can be considered to be related to the code rate loss value R of the first bit sequence; that is, the quantization bit width w can be determined based on the code rate loss value R. Where R = q / N max We can set R ≤ g(N) max E max For example, R≤g(N,M,w). max E max ,M,w)=-log(1-M*2 1-w That is, w can be derived from N. max It is jointly determined by M and R.

[0214] In Example 1, the quantization bit widths corresponding to multiple symbols in the symbol sequence of the distributed matching output can be different. For example, to reduce power consumption, the quantization bit widths corresponding to multiple symbols in the symbol sequence of the distributed matching output can also correspond to the symbol numbers in the symbol sequence.

[0215] As explained in S102, as an example, the nth symbol in the symbol sequence... symb The quantization bit width corresponding to each symbol is denoted as w′=w-Δw, where Δw is related to n. symb The value of n is related. symb It is a positive integer. For example, n symb The larger the value, the larger Δw becomes. That is, the first device can determine the quantization bit width w′ based on the number of the distributed-matched output symbol sequence (or the number of the already output symbol sequence), and perform distribution matching on the bits in the first bit sequence based on the quantization bit width w′. For example, as n... symb Increment from 0 to N symb -1, Δw gradually increases from 0. That is, the quantization bit width corresponding to the symbol with index 0 in the distribution-matched output can be smaller than that of the symbol with index N. symb The quantization bit width corresponding to the sign of -1.

[0216] n symb It can also be considered related to the number of columns in the fence diagram. The number of columns in the fence diagram is N. symb +1. As shown in Figure 9, taking a fence diagram with 5 columns as an example, M = 2, N... symb =4, and E max =3, the fence diagram with infinite precision is shown in Figure 9(a), and the fence diagram with finite precision is shown in Figure 9(b).

[0217] In a finite-precision fence graph, the quantization bit width w′ and n symb It can satisfy: `max()` represents the maximum value. Therefore, the quantization bit width of columns 1 and 2 is w. ′=2, the quantization bit width of columns 3 to 5 is w′ = 1. That is, in the output symbol sequence, numbered n symb The quantization bit width corresponding to the sign of 0 and 1 is w′ = 2, and the number is n. symb The quantization bit width corresponding to the signs = 2 and 3 is w′ = 1.

[0218] Alternatively, Δw = 0, meaning that the quantization bit width for each column is w. In this case, the quantization bit width values ​​for multiple symbols in the symbol sequence output by distribution matching are the same.

[0219] As another example, the nth symbol in the symbol sequence symb The quantization width corresponding to each bit is w, meaning that for each symbol in the symbol sequence, the first device can independently determine its quantization width.

[0220] With w and n symb N max For example, related to M, the value of w can be from the set The value selected, for example, with n symb Increment from 0 to N symb -1 allows you to select a decreasing value of w from this set. For example, when n symb When = 0, take When n symb =N symb When -1, w = 1. Alternatively, it can be considered that p consecutive symbols correspond to the same quantization bit width; therefore, the quantization bit width w corresponding to p consecutive symbols in the symbol sequence can be related to the symbol number, N... max It relates to M and p, where p is a positive integer greater than 1.

[0221] In another possible implementation, computationally-based distribution matching can produce a sequence of N long output symbols. In this approach, an ordered alphabet A = {a0, a1, ..., a...} |A|-1}, M=|A|>2, encode and output the letter sequence The length is N, c i Let B be the number of candidate output letter sequences, where 0 ≤ i ≤ N-1. These B candidate output sequences divide the region [0, 1) into B disjoint intervals [b...]. j ,b j+1 ), 0 = b0 ≤ b1 … ≤ b B =1, [b j ,b j+1 ) is the interval corresponding to the j-th sequence. K-bit encoded input sequence Arranged in dictionary order. For example, If u i =v i ,i≤j,u j >vj , A real number between [0, 1] Where i is The lexicographical index. For example, the lexicographical order of 10 is 2, corresponding to the real value 2 / 4, which is the encoded input sequence. Corresponding encoded output sequence If and only if The corresponding real number is The corresponding interval [b j ,b j+1 )middle.

[0222] remember The corresponding interval is The lower endpoint of the interval This represents the interval width. It can be calculated recursively. Representative sequence The corresponding interval width. It can be seen that, [] w This means retaining w significant digits. For example, if w = 2,

[0223] In Example 2, the quantization bit width w used for distribution matching can be determined based on N and M. As described in S102, w is positively correlated with N and positively correlated with M. For example, Δ can be a preset transmission value. For example, Δ = 2 can reduce losses due to finite precision. For instance, when M = 2,

[0224] Optionally, the quantization bit width w in Embodiment 2 can also be related to the bit loss q of the first bit sequence. Referring to the description in S102, the bit loss q can be taken as K corresponding to infinite-precision arithmetic. max K corresponding to finite precision arithmetic coding max The difference. Among them, the infinite precision arithmetic corresponds to... B represents the number of candidate output sequences for the arithmetic code. Finite-precision arithmetic coding corresponds to... Output the letter sequence for arithmetic encoding. That is... It is one of the B candidate output sequences. This indicates rounding down. In this example, we can let q ≤ f(N, E). max ,M,w)=nlog(1+M*2 -w That is, w can be determined by N, M, and q together. For example, w can satisfy: w = logM + log(1 / (2 q / N -1)).

[0225] Alternatively, the quantization bit width w in Example 2 can be considered to be related to the code rate loss value R of the first bit sequence, that is, the quantization bit width w can be determined based on the code rate loss value R. Where R = q / N. We can let R ≤ g(N, E max For example, R≤g(N,E). max ,M,w)=log(1+M*2 -w That is, w can be determined by N, M and R together.

[0226] In embodiment 2, w can be determined by a first device, and the first device can send second information to a second device, which is used to indicate w. The first device can be a network device, and the second device can be a terminal.

[0227] Alternatively, w can be determined by a second device, which then sends second information to the first device to indicate w. The second device can be a network device, and the first device can be a terminal.

[0228] Furthermore, referring to the description in S102, the quantization bit width can also correspond to the symbol number in the symbol sequence. For example, to reduce power consumption, the quantization bit width corresponding to different symbols in the distributed matching output symbol sequence can also correspond to the symbol number in the symbol sequence. Specifically, as the symbol number increases, the quantization bit width corresponding to the symbol can gradually decrease. For example, max() means to retrieve the maximum value.

[0229] As explained in S102, as an example, the nth symbol in the symbol sequence... symb The quantization bit width corresponding to each symbol is denoted as w′=w-Δw, where Δw is related to n. symb The value of n is related. symb It is a positive integer. For example, n symb The larger the value of n, the larger the value of Δw. For example, as n increases... symb Increment from 0 to N symb -1, Δw gradually increases from 0. That is, the quantization bit width corresponding to the symbol with index 0 in the distribution-matched output can be smaller than that of the symbol with index N. symb The quantization bit width corresponding to the sign of -1.

[0230] Alternatively, Δw can be considered as 0, meaning that the quantization bit width for each column is w. In this case, the quantization bit width values ​​for multiple symbols in the symbol sequence output by the distribution matching are the same.

[0231] As another example, the nth symbol in the symbol sequence symbThe quantization width corresponding to each bit is w, meaning that for each symbol in the symbol sequence, the first device can independently determine its quantization width.

[0232] With w and n symb N max For example, related to M, the value of w can be from the set The value selected, for example, with n symb Increment from 0 to N symb -1 allows you to select a decreasing value of w from this set. For example, when n symb When = 0, take When n symb =N symb When -1, w = 1. Alternatively, it can be considered that p symbols correspond to the same quantization bit width; then the quantization bit width w corresponding to the p symbols in the symbol sequence can be related to the symbol number, N... max It relates to M and p, where p is a positive integer greater than 1.

[0233] It is understood that, in order to achieve the functions in the above embodiments, the communication device includes hardware structures and / or software modules corresponding to each function. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0234] Figures 10 and 11 are schematic diagrams of possible communication devices provided in embodiments of this application. These communication devices can be used to implement the functions of the first communication device and / or the second communication device in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments. The first communication device and / or the second communication device can be referred to the description in the above method embodiments, and will not be repeated here. For example, the communication device can be used to implement the function of the first device in the process shown in Figure 5, or to implement the function of the second device in the process shown in Figure 7.

[0235] The communication device 1000 shown in Figure 10 includes a processing unit 1010 and a transceiver unit (or communication unit) 1020. The communication device 1000 is used to implement the functions of the first communication device, the second communication device, the third communication device, or the fourth communication device in the above method embodiments. The transceiver unit may include a sending unit and a receiving unit, used for sending and receiving, respectively.

[0236] Taking the process shown in Figure 10 as an example, when the communication device 1000 is used to implement the function of the third communication device in the method embodiment shown in Figure 10, specifically, the transceiver unit 1020 can be used to receive first configuration information from the second communication device or the first communication device; the transceiver unit 1020 can also be used to receive the first sensing reference signal according to the receiving configuration information of the first sensing reference signal.

[0237] When the communication device 1000 is used to implement the function of the second communication device in the method embodiment shown in FIG10, specifically, the transceiver unit 1020 can be used to send NAS messages, which contain the reception configuration information of the first sensing reference signal.

[0238] When the communication device 1000 is used to implement the function of the first communication device in the method embodiment shown in FIG10, specifically, the transceiver unit 1020 can be used to send an RRC message, which contains the reception configuration information of the first sensing reference signal.

[0239] For a more detailed description of the above-mentioned processing unit 1010 and transceiver unit 1020, please refer directly to the description of the process steps and related features in the above method embodiments, which will not be repeated here.

[0240] The communication device 1100 shown in Figure 11 includes a processor 1110 and an interface circuit 1120. The processor 1110 and the interface circuit 1120 are coupled to each other. It is understood that the interface circuit 1120 can be a transceiver or an input / output interface. Optionally, the communication device 1100 may also include a memory 1130 for storing instructions executed by the processor 1110, or storing input data required by the processor 1110 to execute instructions, or storing data generated after the processor 1110 executes instructions.

[0241] When the communication device 1100 is used to implement the above method embodiment, the processor 1110 is used to implement the function of the processing unit 1010, and the interface circuit 1120 is used to implement the function of the transceiver unit 1020.

[0242] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), microprocessors without interlocked piped stages architecture (MIPS), advanced instruction set computers (RISC) machines (ARM), network processors (NPs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0243] The method steps in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disk, portable hard disk, compact disc read-only memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Furthermore, the ASIC can reside in a first communication device, a second communication device, a third communication device, or a fourth communication device. Alternatively, the processor and storage medium can exist as discrete components in the first, second, third, or fourth communication device.

[0244] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. A computer program is a set of instructions that directs each step of an action of an electronic computer or other device with message processing capabilities. It is typically written in a programming language and runs on a target architecture. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be volatile or non-volatile, or it can include both types of storage media.

[0245] Based on the same technical concept, embodiments of this application also provide a computer-readable storage medium, including a program or instructions, which, when run on a computer, cause the methods in the above method embodiments to be executed.

[0246] Based on the same technical concept, embodiments of this application also provide a computer program product, including instructions that, when run on a computer, cause the methods in the above method embodiments to be executed.

[0247] Based on the same technical concept, embodiments of this application also provide a communication system, including a first device and a second device, which are used to implement the communication methods shown in FIG5 and FIG7, respectively.

[0248] 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.

[0249] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0250] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates an "or" relationship between the preceding and following related objects; in the formulas of this application, the character " / " indicates a "division" relationship between the preceding and following related objects.

[0251] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

Claims

1. A communication method characterized by comprising: include: Obtain the first bit sequence; The first bit sequence is distributed and matched according to the quantization bit width w to obtain the second bit sequence, wherein w is matched with the length N of the second bit sequence or the maximum length N of the second bit sequence. max Related to, among which, N and N max The integer is a positive integer, and N ≤ N max w is a positive integer; Channel coding and modulation are performed based on the second bit sequence to obtain the first information.

2. The method as described in claim 1, characterized in that, The step of performing distribution matching on the first bit sequence according to the quantization bit width w to obtain the second bit sequence includes: A symbol sequence is obtained by performing distribution matching on the first bit sequence according to w; The second bit sequence is obtained by performing a first transformation on the symbol sequence.

3. The method of claim 2, wherein, The w is also related to M, which is the maximum number of distinct values ​​in the distributed matching symbol sequence.

4. The method of claim 3, wherein, The w is positively correlated with the M.

5. The method of any one of claims 2-4, wherein, The w corresponds to the number of the symbol in the symbol sequence.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Obtain the payload bits, which include the first bit sequence and the third bit sequence; The channel coding and modulation based on the second bit sequence includes: Channel coding and modulation are performed based on the second bit sequence and the third bit sequence.

7. The method of any one of claims 1-6, wherein, The w is positively correlated with the N, or the w is positively correlated with the N max The w is positively correlated with the N, or the w is positively correlated with the N 8. The method of any one of claims 1-7, wherein, The w, the N, and the M satisfy: Δ is a constant; or, said w, said N max and said M satisfy: Δ is a constant, wherein, log represents a logarithm operation with base 2, This indicates rounding up.

9. The method of any one of claims 1-7, wherein, The w is also related to the bit loss q of the first bit sequence, where q is an integer greater than or equal to 0.

10. The method as described in claim 9, characterized in that, The q is negatively correlated with the w.

11. The method as described in claim 10, characterized in that, The relationship between q and w is as follows: or, w = log M + log(l / (2 q / N -1)) where log denotes the logarithm with base 2.

12. The method according to any one of claims 1-11, characterized in that, The method further includes: Receive second information, the second information being used to instruct w; or, Send a second message, which is used to instruct w.

13. The method of any one of claims 1-12, wherein, The method further includes: Receive third information, which indicates one or more of N, M, Δ, or q; or, Send a third message, which indicates one or more of N, M, Δ, or q.

14. A communication method, comprising: include: Obtain the information to be decoded; The second bit sequence is obtained based on the information to be decoded; Based on the quantization bit width w, the second bit sequence is dedistributed and matched to obtain the first bit sequence, wherein w is related to the length N of the second bit sequence or the maximum length N of the second bit sequence. max Related to, among which, N and N max The integer is a positive integer, and N ≤ N max w is a positive integer.

15. The method of claim 14, wherein, The step of performing dedistribution matching on the second bit sequence according to the quantization bit width w to obtain the first bit sequence includes: A symbol sequence is obtained by performing a second transformation based on the second bit sequence; The first bit sequence is obtained by performing distributive matching on the symbol sequence according to w.

16. The method of claim 15, wherein, The w is also related to M, which is the maximum number of distinct values ​​in the distributed matching symbol sequence.

17. The method of claim 16, wherein, The w is positively correlated with the M.

18. The method of any one of claims 15-17, wherein, The w corresponds to the number of the symbol in the symbol sequence.

19. The method of any one of claims 14-18, wherein, The method further includes: The third bit sequence is obtained based on the information to be decoded; The payload bits are obtained based on the first bit sequence and the third bit sequence.

20. The method of any one of claims 14-19, wherein, The w is positively correlated with the N, or the w is positively correlated with the N max .

21. The method of any one of claims 14-20, wherein, The w, the N, and the M satisfy: Δ is a constant; or, said w, said N max and said M satisfy: Δ is a constant, wherein, log represents a logarithm operation with base 2, This indicates rounding up.

22. The method of any one of claims 14-20, wherein, The w is also related to the bit loss q of the first bit sequence, where q is an integer greater than or equal to 0.

23. The method of claim 22, wherein, The q is negatively correlated with the w.

24. The method of claim 23, wherein, The relationship between q and w is as follows: or, w = log M + log(l / (2 q / N -1)) where log denotes the logarithm with base 2.

25. The method of any one of claims 14-24, wherein, The method further includes: Receive second information, the second information being used to instruct w; or, Send a second message, which is used to instruct w.

26. The method of any one of claims 14-25, wherein, The method further includes: Receive third information, which indicates one or more of N, M, Δ, or q; or, Send a third message, which indicates one or more of N, M, Δ, or q.

27. A communications device, characterized by Includes a processor for executing computer programs or instructions to implement the method as described in any one of claims 1-13, or to implement the method as described in any one of claims 14-26.

28. A computer-readable storage medium, characterized in that, The storage medium stores a computer program or instructions, which, when executed by a communication device, implement the method as described in any one of claims 1-13, or the method as described in any one of claims 14-26.

29. A computer program product, characterised in that, When the computer program product is executed by a computer, the computer executes the method as described in any one of claims 1-13, or executes the method as described in any one of claims 14-26.

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