Communication method and system, storage medium, electronic device, and computer program product

Abstract

Embodiments of the present disclosure provide a communication method and system, a storage medium, an electronic device, and a computer program product. The method comprises: performing encoding processing on original bit data to obtain N channels of encoded data, wherein N is an integer greater than or equal to 2; performing N channels of modulation processing on the N channels of encoded data on the basis of N modulation and coding schemes (MCSs) to obtain N channels of modulated data, wherein each channel of modulated data corresponds to one MCS; mapping the N channels of modulated data to resource blocks on the basis of a preset physical resource mapping table; and performing waveform processing on the mapped data to generate a time domain signal, and sending the time domain signal over a wireless channel.

Description

Communication methods, systems, storage media, electronic devices and computer program products

[0001] Cross-reference of related applications

[0002] This disclosure is based on and claims priority to Chinese Patent Application No. 2025102126869, filed on February 25, 2025, entitled “Communication Method, System, Storage Medium, Electronic Device and Computer Program Product”, and incorporates the entire contents of that patent application by reference. Technical Field

[0003] This disclosure relates to the field of communications, and more specifically, to a communication method, system, storage medium, electronic device, and computer program product. Background Technology

[0004] In wireless mobile communication systems, the characteristics of the wireless channel significantly impact system performance. Transmitted signals typically experience substantial distortion after passing through the channel. Therefore, to ensure accurate signal recovery at the receiver, channel equalization techniques are generally employed to compensate for channel fading. Channel equalization requires prior knowledge of Channel State Information (CSI). Thus, wireless mobile communication systems typically perform channel estimation by transmitting pilot symbols to obtain an accurate CSI, and then use this CSI for channel equalization to eliminate signal waveform distortion caused by the channel. Performing channel estimation before equalization is a crucial step in building robust wireless communication systems. Currently, Least Squares (LS) and Minimum Mean Square Error (MMSE) algorithms are commonly used for channel estimation. Channel equalization algorithms commonly include Zero-Forcing (ZF) equalization and MMSE equalization. All of these non-blind channel estimation algorithms require pilot signal transmission, resulting in pilot overhead and reduced communication efficiency. Therefore, researching pilot-free communication systems can avoid the impact of pilot overhead and further improve data transmission efficiency.

[0005] There is no good solution to the above problems in the relevant technologies. Summary of the Invention

[0006] This disclosure provides a communication method, system, storage medium, electronic device, and computer program product.

[0007] According to one embodiment of this disclosure, a communication method is provided, comprising: encoding raw bit data to obtain N coded data, wherein N is an integer greater than or equal to 2; performing N modulation processing on the N coded data according to N modulation and coding schemes (MCS) to obtain N modulated data, wherein each modulated data corresponds to one MCS; mapping the N modulated data to resource blocks according to a preset physical resource mapping table; performing waveform processing on the mapped data to generate a time-domain signal, and transmitting the time-domain signal through a wireless channel.

[0008] According to another embodiment of this disclosure, a communication method is also provided, comprising: receiving a time-domain signal through a wireless channel and performing waveform de-coding on the time-domain signal; performing demapping on the waveform-decoded data according to a preset physical resource mapping table corresponding to N modulation and coding schemes (MCS) to obtain N channels of frequency-domain received data, wherein N is an integer greater than or equal to 2; performing layered equalization demodulation and decoding on the N channels of frequency-domain received data according to the N MCS to obtain N channels of decoded data, wherein each channel of decoded data corresponds to one MCS; and merging the N channels of decoded data to obtain parsed bit data.

[0009] According to another embodiment of this disclosure, a communication system is provided, comprising: a transmitting end, configured to encode raw bit data to obtain N coded data, wherein N is an integer greater than or equal to 2; to perform N modulation processing on the N coded data according to N modulation and coding strategies (MCS) to obtain N modulated data, wherein each modulated data corresponds to one MCS; to map the N modulated data to resource blocks according to a preset physical resource mapping table; to perform waveform processing on the mapped data to generate a time-domain signal, and to transmit the time-domain signal through a wireless channel; and a receiving end, configured to receive the time-domain signal through a wireless channel and perform waveform de-processing on the time-domain signal; to perform de-mapping processing on the de-waveformed data according to the physical resource mapping table to obtain N frequency-domain received data; to perform layered equalization demodulation processing and decoding processing on the N frequency-domain received data according to N MCS to obtain N decoded data, wherein each decoded data corresponds to one MCS; and to merge the N decoded data to obtain parsed bit data.

[0010] According to yet another embodiment of this disclosure, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0011] According to yet another embodiment of this disclosure, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in any of the above method embodiments.

[0012] According to yet another embodiment of this disclosure, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in any of the above method embodiments. Attached Figure Description

[0013] Figure 1 is a hardware structure block diagram of the base station operated in the embodiment of the method of this disclosure;

[0014] Figure 2 is a flowchart of a communication method of a transmitting end according to an embodiment of the present disclosure;

[0015] Figure 3 is a flowchart of a communication method of a receiving end according to an embodiment of the present disclosure;

[0016] Figure 4 is a structural block diagram of a communication system according to an embodiment of the present disclosure;

[0017] Figure 5 is a schematic diagram of the architecture of a communication system in one embodiment of this disclosure (I);

[0018] Figure 6 is a schematic diagram of the architecture of a communication system according to one embodiment of the present disclosure (II);

[0019] Figure 7 is a schematic diagram (a) of a resource mapping pattern of two MCS hybrid modulation transmissions according to an embodiment of the present disclosure;

[0020] Figure 8 is a schematic diagram (II) of a resource mapping pattern for two MCS hybrid modulation transmissions according to an embodiment of the present disclosure;

[0021] Figure 9 is a schematic diagram (III) of a resource mapping pattern for two MCS hybrid modulation transmissions according to an embodiment of the present disclosure;

[0022] Figure 10 is a schematic diagram (a) of a resource mapping pattern with two layers mapping the same RE position according to an embodiment of the present disclosure;

[0023] Figure 11 is a schematic diagram (II) of a resource mapping pattern with two layers mapping the same RE position according to an embodiment of the present disclosure;

[0024] Figure 12 is a schematic diagram (III) of a resource mapping pattern with two layers mapping the same RE position according to an embodiment of the present disclosure;

[0025] Figure 13 is a schematic diagram (a) of a resource mapping pattern with two layers mapping different RE locations according to an embodiment of the present disclosure;

[0026] Figure 14 is a schematic diagram (II) of a resource mapping pattern with two-layer mapping of different RE locations according to an embodiment of the present disclosure;

[0027] Figure 15 is a schematic diagram (III) of a resource mapping pattern with two-layer mapping of different RE locations according to an embodiment of the present disclosure;

[0028] Figure 16 is a schematic diagram (a) of a resource mapping pattern with the same RE location mapped in multiple layers according to an embodiment of the present disclosure;

[0029] Figure 17 is a schematic diagram (II) of a resource mapping pattern with the same RE location mapped in multiple layers according to an embodiment of the present disclosure;

[0030] Figure 18 is a schematic diagram (III) of a resource mapping pattern with the same RE location mapped in multiple layers according to an embodiment of the present disclosure;

[0031] Figure 19 is a schematic diagram (a) of a resource mapping pattern for different RE locations in a multi-layer mapping according to an embodiment of the present disclosure;

[0032] Figure 20 is a schematic diagram (II) of a resource mapping pattern for different RE locations in a multi-layer mapping according to an embodiment of the present disclosure;

[0033] Figure 21 is a schematic diagram (III) of a resource mapping pattern for different RE locations in a multi-layer mapping according to an embodiment of the present disclosure;

[0034] Figure 22 is a schematic diagram (IV) of a resource mapping pattern for different RE locations in a multi-layer mapping according to an embodiment of the present disclosure. Detailed Implementation

[0035] The embodiments of this disclosure will be described in detail below with reference to the accompanying drawings and examples.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0037] The method embodiments provided in this disclosure can be applied to communication nodes in a wireless communication network. Communication nodes include, but are not limited to, base stations (BS), relay nodes, and user equipment (UE). Taking operation on a base station as an example, Figure 1 is a hardware structure block diagram of a base station operating according to the method embodiments of this disclosure. As shown in Figure 1, a base station 100 may include one or more (only one is shown in Figure 1) processors 102 (processors 102 may include, but are not limited to, processing devices such as microprocessors (MCUs) or programmable logic devices (FPGAs)) and a memory 104 for storing data. The base station may also include transmission devices and input / output devices for communication functions. Those skilled in the art will understand that the structure shown in Figure 1 is merely illustrative and does not limit the structure of the base station. For example, a base station may include more or fewer components than shown in Figure 1, or have a different configuration than shown in Figure 1.

[0038] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the communication method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a base station via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the communication provider of the mobile terminal. In one instance, the transmission device includes a Network Interface Controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one instance, the transmission device may be a radio frequency (RF) module used to communicate with the Internet wirelessly.

[0039] In one embodiment of this disclosure, a communication method is provided, applied to a sending end. Figure 2 is a flowchart of the communication method of the sending end according to an embodiment of this disclosure. As shown in Figure 2, the process includes the following steps:

[0040] Step S202: Encode the original bit data to obtain N-channel encoded data;

[0041] Step S204: Perform N-channel modulation processing on N-channel coded data according to N modulation and coding schemes (MCS) to obtain N-channel modulated data, wherein each channel of modulated data corresponds to one MCS;

[0042] Step S206: Map N channels of modulation data to resource blocks according to a preset physical resource mapping table;

[0043] Step S208: Perform waveform processing on the mapped data to generate a time-domain signal, and transmit the time-domain signal through a wireless channel.

[0044] In this embodiment, N is the number of MCSs used in the multi-level hybrid modulation / demodulation of this disclosure, and N is an integer greater than or equal to 2.

[0045] In this embodiment, the physical resource mapping table is used to indicate the resources occupied by the modulation data of each of the N MCSs in a resource block (RB). A resource block is the basic unit of physical resources allocated to a user in both the frequency and time domains, and one resource block contains multiple resource elements (REs). Taking the LTE system as an example, an RB in the time domain consists of 12 subcarriers within a time slot (containing 7 or 14 Orthogonal Frequency Division Multiplexing (OFDM) symbols, depending on the subframe configuration), and an RE consists of one subcarrier and one OFDM symbol.

[0046] Existing pilotless communication systems employ a single-modulation transmission method. Because the system itself lacks pilot signal transmission, improving the performance of pilotless communication systems in high-order modulation and multi-stream transmission is challenging. Through steps S202 to S208, by employing N different MCSs, multi-order hybrid modulation of the data is achieved. This enables high-order modulation and multi-stream transmission without using pilot signals, thus solving the problem of performance improvement in high-order modulation and multi-stream transmission in pilotless communication systems in related technologies. This results in improved data transmission efficiency and quality.

[0047] The entities that perform the above steps can be base stations, user equipment, etc., but are not limited to these.

[0048] In some embodiments, the N MCSs are different types and / or different orders of modulation schemes. The MCSs may include: Quadrature Phase Shift Keying (QPSK), Quadrature Amplitude Modulation (QAM), such as 16-QAM, 64-QAM, 256-QAM, etc., but this disclosure is not limited thereto.

[0049] In some embodiments, all N types of MCS employ irregular modulation constellation diagrams. For example, irregular modulation constellation diagrams can be learned and generated using machine learning models. In this embodiment, employing irregular modulation constellation diagrams can further improve the system's anti-interference capability and spectral efficiency, making it suitable for scenarios requiring high transmission rates under complex channel conditions.

[0050] In some embodiments, the first MCS among the N MCSs is the lowest-order MCS among the N MCSs; the last MCS among the N MCSs is the highest-order MCS among the N MCSs.

[0051] In some embodiments, prior to step S202, the method further includes at least one of the following:

[0052] 1) Determine the value of N;

[0053] 2) Determine the configuration of the N types of MCS;

[0054] 3) Determine the number of layers in the transmission mode;

[0055] 4) Determine the physical resource allocation parameters for the N types of MCS;

[0056] 5) Determine the physical resource mapping table.

[0057] In one exemplary embodiment, the configuration of N MCSs may include the modulation type and modulation order of each MCS. The values ​​of the modulation type and modulation order N of each MCS and the configuration of the N MCSs can be set according to data transmission requirements, and this disclosure does not impose any restrictions on them.

[0058] In another exemplary embodiment, the configuration of N MCSs may include N different irregular modulation constellation diagrams.

[0059] In this embodiment, the number of transmission mode layers is the number of data streams transmitted simultaneously in a Multiple-Input Multiple-Output (MIMO) system. MIMO technology utilizes multiple antennas at the transmitting and receiving ends to achieve spatial diversity and spatial multiplexing, thereby improving data transmission rate and reliability. The number of transmission mode layers can be determined based on the number of antennas at the transmitting and receiving ends; for example, the minimum number of antennas at both ends can be determined as the number of transmission mode layers. If applied to a Single-Input Single-Output (SISO) system, it can be processed as having one layer.

[0060] In this embodiment, the physical resource allocation parameters of the N types of MCS are used to represent the physical resource allocation requirements of each MCS, and can be used as the constraint conditions or generation conditions of the physical resource mapping table.

[0061] In some embodiments, step S202 may include: splitting the original bit data into N paths of bit data according to the configuration of N types of MCS and the physical resource allocation parameters of the N types of MCS; and encoding the N paths of bit data separately to obtain N paths of encoded data. In this embodiment, the N paths of data are encoded independently, which can better adapt to the MIMO system and improve the system's anti-interference capability in complex environments.

[0062] In other embodiments, step S202 may include: determining the total bit data corresponding to the N MCSs from the original bit data based on the configuration of the N MCSs and the physical resource allocation parameters of the N MCSs; encoding the total bit data to obtain total encoded data; and splitting the total encoded data into N paths of encoded data based on the configuration of the N MCSs and the physical resource allocation parameters of the N MCSs. In this embodiment, the data is uniformly encoded before being split into multiple paths, which can reduce encoding complexity and improve data processing efficiency.

[0063] In some embodiments, the physical resource mapping table includes resource mapping patterns for N types of MCSs, and the resource mapping patterns are used to indicate the time-domain and frequency-domain positions of the resource units corresponding to each MCS in the resource block.

[0064] In some embodiments, determining the physical resource mapping table may include: in response to N equaling 2, allocating a portion of the resource units in the resource block to a first type of MCS according to the resource allocation generation criteria, and allocating the remaining resource units in the resource block to a second type of MCS, thereby determining the physical resource mapping table.

[0065] In other embodiments, determining the physical resource mapping table may include: in response to N being greater than 2, sequentially allocating the i-th part of the resource units in the resource block to the i-th type of MCS according to the resource allocation generation criteria, i = 1, ..., N-1, and all remaining resource units in the resource block to the N-th type of MCS, so as to determine the physical resource mapping table.

[0066] In this embodiment, when N equals 2, the first MCS is a low-order modulation scheme among the N MCSs, and the second MCS is a high-order modulation scheme among the N MCSs. When N is greater than 2, the first MCS is the lowest-order MCS among the N MCSs, and the Nth MCS is the highest-order MCS among the N MCSs. The low-order MCS has better robustness, helping the receiver to more accurately estimate channel state information (CSI), while the high-order MCS can carry more bits of information, improving data transmission efficiency and quality. For example, most of the resource units in a resource block can be allocated to the highest-order MCS to improve data transmission efficiency.

[0067] In some embodiments, resource allocation generation criteria include at least one of the following:

[0068] 1) The physical resource allocation parameters of the N types of MCS meet the preset requirements;

[0069] 2) Multiple transport layers corresponding to the first type of MCS or the i-th type of MCS are mapped to the same or different resource units;

[0070] 3) When multiple transport layers corresponding to the first type of MCS or the i-th type of MCS are mapped to different resource units, the resource units of the multiple transport layers corresponding to the first type of MCS or the i-th type of MCS are evenly distributed.

[0071] 4) In response to N equaling 2, the multiple transport layers corresponding to the second type of MCS are mapped to the same resource unit;

[0072] 5) In response to N being greater than 2, the multiple transport layers corresponding to the Nth type of MCS are mapped to the same resource unit.

[0073] Where i = 1, ..., N-1, the i-th type of MCS is used to refer to other MCSs except the highest-order MCS, so they can all be called low-order MCSs.

[0074] In this embodiment, the preset requirements for physical resource allocation parameters may include the set values, optional values, or optional ranges of each physical resource allocation parameter.

[0075] In this embodiment, the multiple transport layers of the highest-order MCS can only be mapped to the same resource unit, while the multiple transport layers of the lower-order MCS can be mapped to the same resource unit or to different resource units. Mapping the multiple transport layers of the lower-order MCS to different resource units actually improves demodulation performance by sacrificing some of the capacity gain of multi-layer transmission.

[0076] In some embodiments, the physical resource allocation parameters of the N types of MCS include at least one of the following:

[0077] 1) The number of single-layer symbols of the resource unit corresponding to the first type of MCS or the i-th type of MCS;

[0078] 2) The single-layer symbol spacing of the resource unit corresponding to the first type of MCS or the i-th type of MCS;

[0079] 3) The frequency domain starting position of the resource unit corresponding to the first type of MCS or the i-th type of MCS;

[0080] 4) Frequency domain spacing of resource units corresponding to the first type of MCS or the i-th type of MCS;

[0081] 5) The resource proportion of the resource unit corresponding to the first type of MCS or the i-th type of MCS;

[0082] 6) The resource percentage of the resource unit corresponding to the Nth type of MCS;

[0083] 7) The start symbol of the resource units of multiple transport layers corresponding to the first type of MCS or the i-th type of MCS;

[0084] 8) The symbol spacing between resource units of multiple transport layers corresponding to the first type of MCS or the i-th type of MCS.

[0085] In an exemplary embodiment, the preset requirements for the physical resource allocation parameters of each MCS can be configured independently or uniformly. Taking the lowest-order MCS as an example, the preset requirements for the physical resource allocation parameters of the lowest-order MCS can be configured as at least one of the following:

[0086] The number of symbols per layer for the RE in the lowest-order MCS is l num =2 / 3 / 4.

[0087] The frequency domain spacing of REs in the lowest-order MCS is Δk = 2 / 4 / 6 / 8 / 12.

[0088] The symbol spacing of the lowest-order MCS is 2 / 4 / 6 / 7 / 12 / 13 for a single layer of RE.

[0089] The resource allocation of the lowest-level MCS is a1;

[0090] The starting symbols for REs in each transport layer of the lowest-order MCS are 0 to 6;

[0091] In the lowest-order MCS, the REs of each transport layer are staggered, and the symbol interval between the REs of each transport layer is 0 to 6.

[0092] The lowest-order MCS has a single-layer frequency domain starting position k0, for example, k0 = mod(Cellid, 12), where Cellid is the cell identifier. The frequency domain starting position between multiple layers, configured for the l-th layer, is k... 0,l =k0+k Δ ·l,k 0,l Let k be the starting position of the l-th layer. Δ Configure parameters for the frequency domain start position to be staggered, which are 0 / 1 / 2 / 3.

[0093] In this embodiment, the values ​​of the physical resource allocation parameters for each MCS can be determined from the preset value range or optional values. The physical resource mapping table can be flexibly configured based on meeting the preset requirements, thereby adapting to complex and ever-changing communication scenarios and environments.

[0094] In some embodiments, when the total number N of MCSs in the system is 2, the RE positions of the lowest-order MCS in the RB are deducted, and the remaining RE positions are allocated to higher-order MCSs. When the total number N of MCSs in the system is greater than 2, the resource mapping pattern of MCS1 is generated first, followed by the generation of the resource mapping pattern of MCS2. The generation method of the MCS2 pattern must meet the generation criteria of MCS2, and the resource mapping patterns of other MCSs are generated sequentially. Finally, the resource mapping pattern of the MCSN is generated based on the positions of the remaining REs after deducting the RE positions of other MCSs in the RB.

[0095] In this embodiment, different MCS resource mapping patterns can be designed for different transmission modes, thereby ensuring that more accurate channel state information can be obtained through low-order modulation RE when transmitting without pilots, thus improving the system performance of MIMO multi-stream transmission and high-order modulation.

[0096] In some embodiments, step S206 may include: performing layer mapping processing on the N modulated data streams according to the number of layers in the transmission mode, and mapping the layer-mapped data to corresponding resource units according to the physical resource mapping table, wherein the resource block includes multiple resource units, and each resource unit corresponds to an MCS and a transmission layer. In this embodiment, if the number of layers in the transmission mode is 1, the layer mapping processing step can be omitted, thereby improving data processing efficiency.

[0097] In some other embodiments, step S206 may include: mapping the N modulation data to corresponding resource units according to the physical resource mapping table, wherein the resource block includes multiple resource units, and each resource unit corresponds to an MCS.

[0098] In this embodiment of the disclosure, multi-order hybrid modulation of data is achieved based on N different MCSs without using pilot signals. This can utilize the high robustness of low-order MCSs and the high transmission efficiency of high-order MCSs, thereby solving the problem that it is difficult to improve the performance of pilotless communication systems in high-order modulation and multi-stream in related technologies. This achieves the technical effect of improving data transmission efficiency and transmission quality, and not only improves spectral efficiency and transmission quality, but also enhances the robustness and adaptability of the system.

[0099] In one embodiment of this disclosure, a communication method is also provided, applied to a receiving end. Figure 3 is a flowchart of the communication method of the receiving end according to an embodiment of this disclosure. As shown in Figure 3, the process includes the following steps:

[0100] Step S302: Receive time-domain signals through a wireless channel and perform waveform decoding on the time-domain signals;

[0101] Step S304: Demap the waveform-decoded data according to the preset physical resource mapping table corresponding to the N modulation and coding strategies (MCS) to obtain N channels of frequency domain received data.

[0102] Step S306: Perform layered equalization demodulation and decoding processing on N channels of frequency domain received data according to N types of MCS to obtain N channels of decoded data, wherein each channel of decoded data corresponds to one type of MCS;

[0103] Step S308: Merge the N decoded data streams to obtain the parsed bit data.

[0104] In this embodiment, N is the number of MCSs used in multi-stage hybrid demodulation, and N is an integer greater than or equal to 2.

[0105] In this embodiment, hierarchical equalization and demodulation processing refers to performing equalization and demodulation processing on data from N different MCSs. The equalization process is used to eliminate interference introduced by the wireless channel, such as multipath effects and spatial correlation. Equalization techniques include, but are not limited to, zero-forcible (ZF) and minimum mean square error (MMSE). The time-domain signal in this disclosure is generated at the transmitting end through multi-order hybrid modulation and then transmitted to the receiving end via the wireless channel. The receiving end needs to use a corresponding multi-order hybrid demodulation method for channel estimation and data recovery. Those skilled in the art will understand that the N MCSs and physical resource mapping tables used by the receiving and transmitting ends during modulation and demodulation are the same.

[0106] In this embodiment, the physical resource mapping table is used to indicate the resources occupied by the modulation data of each of the N MCSs in a resource block (RB). A resource block is the basic unit of physical resources allocated to a user in both the frequency and time domains, and one resource block contains multiple resource elements (REs). Taking the LTE system as an example, an RB in the time domain consists of 12 subcarriers within a time slot (containing 7 or 14 OFDM symbols, depending on the subframe configuration), and an RE consists of one subcarrier and one OFDM symbol.

[0107] Through the above steps S302 to S308, by using N different MCSs, multi-order hybrid demodulation of data is achieved, enabling high-order modulation and multi-stream transmission without the use of pilot signals. This solves the problem that it is difficult to improve the performance of pilotless communication systems in high-order modulation and multi-stream transmission, and achieves the technical effect of improving data transmission efficiency and transmission quality.

[0108] The entities that perform the above steps can be base stations, user equipment, etc., but are not limited to these.

[0109] In some embodiments, the N MCSs are different types and / or different orders of modulation schemes. The MCSs may include: Quadrature Phase Shift Keying (QPSK), Quadrature Amplitude Modulation (QAM), such as 16-QAM, 64-QAM, 256-QAM, etc., but this disclosure is not limited thereto.

[0110] In some embodiments, all N types of MCS employ irregular modulation constellation diagrams. For example, irregular modulation constellation diagrams can be learned and generated using machine learning models. In this embodiment, employing irregular modulation constellation diagrams can further improve the system's anti-interference capability and spectral efficiency, making it suitable for scenarios requiring high transmission rates under complex channel conditions.

[0111] In some embodiments, the first MCS among the N MCSs is the lowest-order MCS among the N MCSs; the last MCS among the N MCSs is the highest-order MCS among the N MCSs.

[0112] In some embodiments, prior to step S302 or step S304, the method further includes at least one of the following:

[0113] 1) Determine the value of N;

[0114] 2) Determine the configuration of the N types of MCS;

[0115] 3) Determine the number of layers in the transmission mode;

[0116] 4) Determine the physical resource allocation parameters for the N types of MCS;

[0117] 5) Determine the physical resource mapping table.

[0118] In one exemplary embodiment, the configuration of N MCSs may include the modulation type and modulation order of each MCS. The values ​​of the modulation type and modulation order N of each MCS and the configuration of the N MCSs can be set according to data transmission requirements, and this disclosure does not impose any restrictions on them.

[0119] In another exemplary embodiment, the configuration of N MCSs may include N different irregular modulation constellation diagrams.

[0120] In this embodiment, the number of transmission mode layers is the number of data streams transmitted simultaneously in a Multiple-Input Multiple-Output (MIMO) system. MIMO technology can utilize multiple antennas at the transmitting and receiving ends to achieve spatial diversity and spatial multiplexing, thereby improving data transmission rate and reliability. The number of transmission mode layers can be determined based on the number of antennas at the transmitting and receiving ends; for example, the minimum number of antennas at both ends can be determined as the number of transmission mode layers.

[0121] In this embodiment, the physical resource allocation parameters of the N types of MCS are used to represent the physical resource allocation requirements of each MCS, and can be used as the constraint conditions or generation conditions of the physical resource mapping table.

[0122] In some embodiments, the physical resource mapping table includes resource mapping patterns for N types of MCSs, and the resource mapping patterns are used to indicate the time-domain and frequency-domain positions of the resource units corresponding to each MCS in the resource block.

[0123] In some embodiments, step S306 may include the following steps:

[0124] Step S3062: Perform layered equalization demodulation and decoding processing on the first frequency domain received data in the N frequency domain received data according to the first MCS among the N MCSs to obtain the first decoded data, wherein the first MCS is the lowest order MCS among the N MCSs.

[0125] Step S3064: Perform channel estimation processing based on the first frequency domain received data to obtain the original channel estimation information;

[0126] Step S3066: Generate channel estimation information for the j-th MCS among N types of MCS based on the original channel estimation information and physical resource mapping table, and perform hierarchical equalization demodulation and decoding processing based on the channel estimation information of the j-th MCS and the j-th frequency domain received data to obtain the j-th decoded data, where j = 2, ..., N.

[0127] In this embodiment, the data of the low-order MCS can be demodulated and decoded first, and the high robustness and low parsing complexity of the low-order MCS can be used for channel estimation and data recovery. Then, the channel estimation information of the low-order MCS can be used to parse the data of other MCSs. This realizes high-order modulation and multi-stream transmission in a pilotless communication system, and can improve the demodulation accuracy and robustness of the high-order MCS.

[0128] In some embodiments, step S3062 may include: performing blind detection equalization parsing processing on the first channel frequency domain received data according to a first MCS to obtain a first channel equalization parsing result; performing de-layer mapping processing on the first channel equalization parsing result according to the layer number of the transmission mode to obtain a first channel de-layer mapping data; performing demodulation processing on the first channel de-layer mapping data according to the first MCS to obtain a first channel demodulated data; and performing decoding processing on the first channel demodulated data to obtain a first channel decoded data.

[0129] In this embodiment, blind detection equalization parsing refers to channel estimation and equalization without relying on any pre-transmitted pilot signals. Blind detection equalization parsing can include: blind channel estimation and blind equalization.

[0130] In some embodiments, step S3064 may include the following steps:

[0131] Step S3064-2: Perform hard decision processing based on the first equalization parsing result to reconstruct the transmitting end data; or, re-encode, modulate, and layer map processing based on the first decoded data to reconstruct the transmitting end data.

[0132] Step S3064-4: Perform channel estimation processing based on the first frequency domain received data and the reconstructed transmitter data to obtain the original channel estimation information.

[0133] In this embodiment, hard decision processing refers to the demodulator calculating the distance between the blind equalization symbol and the ideal symbol at the transmitting end, and selecting the corresponding ideal modulation symbol at the transmitting end as the hard decision symbol after demodulation based on the principle of closest distance.

[0134] In some embodiments, the step S3066 of generating the channel estimation information of the j-th MCS among N types of MCSs based on the original channel estimation information and the physical resource mapping table may include: performing noise reduction processing on the original channel estimation information; and performing channel estimation interpolation processing on the resource location of the j-th MCS based on the physical resource mapping table and the noise-reduced original channel estimation information to obtain the channel estimation information of the j-th MCS.

[0135] In some embodiments, step S3066, which involves performing layered equalization demodulation and decoding processing based on the channel estimation information of the j-th MCS and the j-th frequency domain received data to obtain the j-th decoded data, may include: performing multi-input multi-output (MIMO) equalization parsing processing based on the channel estimation information of the j-th MCS and the j-th frequency domain received data to obtain the j-th equalization parsing result; performing de-layer mapping processing on the j-th equalization parsing result according to the layer number of the transmission mode to obtain the j-th de-layer mapped data; performing demodulation processing on the j-th de-layer mapped data based on the j-th MCS to obtain the j-th demodulated data; and performing decoding processing on the j-th demodulated data to obtain the j-th decoded data.

[0136] According to the various embodiments of this disclosure, efficient and reliable data transmission can be achieved through hybrid modulation and demodulation of multi-order MCS without using pilot signals. This not only improves spectral efficiency and transmission quality but also enhances the robustness and adaptability of the system. Starting from low-order MCS, the data of each MCS is analyzed using the channel estimation results of the low-order MCS. High-order modulation and multi-stream transmission of the pilotless communication system are realized while ensuring data transmission quality. This solves the problem of difficulty in improving the performance of high-order modulation and multi-stream in pilotless communication systems in related technologies, achieving the technical effect of improving data transmission efficiency and transmission quality. Furthermore, it not only improves spectral efficiency and transmission quality but also enhances the robustness and adaptability of the communication system.

[0137] A communication system is provided in one embodiment of this disclosure. Figure 4 is a structural block diagram of the communication system according to an embodiment of this disclosure. As shown in Figure 4, the system includes the following structure:

[0138] Transmitter 42 is used to encode the original bit data to obtain N coded data, where N is an integer greater than or equal to 2; to perform N modulation processing on the N coded data according to N modulation and coding strategies (MCS) to obtain N modulated data, where each modulated data corresponds to one MCS; to map the N modulated data to resource blocks according to a preset physical resource mapping table; to perform waveform processing on the mapped data to generate a time-domain signal, and to transmit the time-domain signal through a wireless channel;

[0139] The receiver 44 is configured to receive the time-domain signal through the wireless channel and perform waveform de-processing on the time-domain signal; perform de-mapping processing on the de-waveformed data according to the physical resource mapping table to obtain N channels of frequency-domain received data; perform hierarchical equalization demodulation and decoding processing on the N channels of frequency-domain received data according to the N types of MCS to obtain N channels of decoded data, wherein each channel of decoded data corresponds to one type of MCS; and merge the N channels of decoded data to obtain parsed bit data.

[0140] In this embodiment, the transmitting end 42 and the receiving end 44 can be any communication node in the wireless communication network, including but not limited to base stations, user equipment, relay nodes, service nodes, etc.

[0141] In this embodiment of the disclosure, the transmitting end 42 is further configured to perform communication according to the steps in any of the above-described transmitting end-side method embodiments. The receiving end 44 is further configured to perform communication according to the steps in any of the above-described receiving end-side method embodiments.

[0142] The communication system in this embodiment enables pilot-free communication, avoiding pilot overhead and dedicating all symbols to data transmission, thereby further improving data transmission efficiency. The data RE employs multi-level hybrid modulation, enabling the prediction of channel information for the complete transmission RE based on the REs of lower-order MCSs. This, combined with the predicted channel estimation results, enhances data parsing of REs for other higher-order MCSs, thus improving the high-order transmission performance of the pilot-free communication system and significantly increasing its spectral efficiency. The communication system in this disclosure is universally applicable across various channel environments.

[0143] Figure 5 is a schematic diagram of the architecture of a communication system according to one embodiment of this disclosure (I). As shown in Figure 5, the system includes: a transmitting end and a receiving end, wherein...

[0144] The transmitting end performs a series of processes on the original bit data, including N-way encoding, N-way modulation, layer mapping, N-way physical resource mapping, and waveform processing, and then transmits the processed data to the receiving end through a wireless channel.

[0145] The receiving end performs a series of processes on the received data, including waveform de-processing, N-channel physical resource mapping de-processing, layered parsing equalization processing, N-channel demodulation processing, and N-channel decoding processing, to obtain the final parsed bit data.

[0146] In this embodiment, each data stream is encoded separately, and different encoding methods can be adopted according to the actual communication environment and scenario requirements, making it more adaptable to different scenarios.

[0147] In this embodiment, the hierarchical parsing equalization process is performed layer by layer for N types of MCS. First, blind equalization and channel estimation are performed for MCS1 (i.e., the first type of MCS or the lowest order MCS). Then, equalization processing is performed for other MCS2, MCSN, etc., based on the channel estimation results of MCS1.

[0148] In some embodiments, the equalization processing of other MCSs can be performed either based solely on the channel estimation results of MCS1, or based on the demodulation and decoding results of MCS1.

[0149] Figure 6 is a schematic diagram of the architecture of a communication system according to one embodiment of this disclosure (II). As shown in Figure 6, the system includes: a transmitting end and a receiving end, wherein...

[0150] The transmitting end performs a series of processes on the original bit data, including encoding, splitting into N data streams, modulation, layer mapping, physical resource mapping, and waveform processing, and then transmits the processed data to the receiving end through a wireless channel.

[0151] The receiving end performs a series of processes on the received data, including waveform de-processing, N-channel physical resource mapping de-processing, layered parsing equalization processing, N-channel demodulation processing, N-channel data merging processing, and decoding processing, to obtain the final parsed bit data.

[0152] In this embodiment, the data is first encoded, and then the encoded data is split into multiple channels for multi-level hybrid modulation, which can improve the efficiency of data encoding and processing.

[0153] In one embodiment of this disclosure, the following information needs to be determined before data transmission:

[0154] (1) Determine the value of N, wherein the value of N can be determined by the high-level scheduling, and this disclosure does not restrict the specific determination method.

[0155] (2) Determine the resource proportions a1 to aN of all REs in this transmission for all MCS1 to MCSN (i.e., the ratio of the number of REs in each MCS to the total number of REs contained in a unit RB). The specific values ​​of the resource proportions can be obtained through simulation or set according to actual transmission requirements. The receiving end and the transmitting end can obtain the values ​​of the resource proportions in a predefined known manner. This disclosure does not restrict the specific method of generating the resource proportions.

[0156] In this embodiment, the resource ratio of MCS1 to MCSN needs to meet the following requirements.

[0157] (3) Determine the resource mapping patterns for all MCS1 to MCSN. The receiving end and the transmitting end can obtain the resource mapping patterns according to a predefined known method, or they can automatically generate the resource mapping patterns for each MCS based on predefined resource allocation generation criteria and different transmission modes (single-layer / multi-layer) configurations. This disclosure does not limit the specific content of the resource mapping patterns for each MCS.

[0158] In one exemplary embodiment, the resource allocation generation criteria include the following information:

[0159] 1) The number of symbols per layer of the RE in the lowest-order MCS is l num =2 / 3 / 4 configuration.

[0160] 2) The frequency domain spacing of the REs in the lowest-order MCS is configured as Δk = 2 / 4 / 6 / 8 / 12.

[0161] 3) The REs of the lowest order MCS are configured with an inter-symbol spacing of 2 / 4 / 6 / 7 / 12 / 13 in a single transport layer.

[0162] 4) The RE resources of different transport layers of the lowest-order MCS are staggered and equally distributed.

[0163] 5) The total number of REs occupied by the lowest-order MCS in the RB meets the resource allocation requirements:

[0164] Where 12 represents the number of subcarriers in the RB, l slot This refers to the number of symbols in a time slot within an RB, where each RB contains 12.1 slot RE, l num L0 is the number of symbols in a single layer, and L0 is the number of transmission layers.

[0165] 6) If data from different transmission layers of the lowest-order MCS are mapped to the same RE, then set L0=1; if data from different transmission layers are mapped to different REs, then L0=L, where L is the layer configuration and can be determined based on the number of antennas.

[0166] 7) The starting symbol configuration for different transport layers of the lowest-order MCS is 0 to 6;

[0167] 8) If different transport layers of the lowest-order MCS need to be staggered, the stagger interval between symbols of different transport layers is configured as 0 to 6.

[0168] 9) The frequency domain starting position k0 of the lowest-order MCS can be obtained according to the cell identifier modulo 12, k0 = mod(Cellid, 12). The frequency domain starting position between multiple layers, configured for layer l, k 0,l =k0+k Δ ·l,k 0,lLet k be the starting position of the l-th layer. Δ Configure parameters for the frequency domain start position to be staggered, which are 0 / 1 / 2 / 3.

[0169] 10) In a scenario where the total number of modulations N is 2, after deducting the RE positions already occupied by the lowest-order MCS, all remaining RE positions are allocated to the higher-order MCS, and the higher-order MCS needs to map multiple transport layers to the same RE resource in the multi-layer transmission mode.

[0170] 11) In scenarios where the total number of modulations N is greater than 2, the resource mapping pattern of MCS1 is generated first, followed by the generation of the resource mapping pattern of MCS2. The generation method of MCS2 must meet the generation criteria of MCS1. If there are other MCSs besides MCSN, the resource mapping patterns of the other MCSs also need to be generated sequentially. Finally, the resource mapping pattern of MCSN can be generated by allocating all remaining REs after deducting the RE positions of other MCSs to MCSN.

[0171] In one embodiment of this disclosure, based on the communication system in FIG5, the processing flow of the sending end may include the following steps:

[0172] Step S1: Based on the configuration of the N-way MCS and their respective physical resource allocation parameters (such as resource proportion), the original bit data is split into N-way bit data. MCSi , where i = 1, ..., N.

[0173] Step S2, for N-way Bit MCSi Perform encoding processing separately to obtain N-channel encoded data X. di .

[0174] Step S3, according to MCS1(Q1) to MCSN(Q) respectively N The modulation scheme is used to perform N-channel modulation processing to obtain the modulated data Y. di Y di =Modulate(X) d1 Q i ), i = 1, 2, ... N.

[0175] The modulation method used here employs an irregular modulation constellation diagram, which can be learned and generated using machine learning (such as a neural network model). Irregular constellation diagrams differ significantly from traditional constellation diagrams; their mapping points are not symmetrical, and the rotation direction of the constellation diagram is unique. Therefore, the receiver can utilize the uniqueness of the constellation diagram's rotation direction to perform blind equalization for parsing. This disclosure does not limit the specific form of the irregular modulation constellation diagram.

[0176] Step S4: The N modulated data are subjected to layer mapping processing to obtain Y. di,L .

[0177] Step S5: According to the predefined physical resource mapping table, respectively, Y... di,L Mapped to the corresponding physical resource (RE).

[0178] Step S6: After waveform processing, the data from the transmitting end is converted into a time-domain transmission signal (i.e., time-domain data) for transmission.

[0179] In one embodiment of this disclosure, based on the communication system in FIG5, the processing flow of the receiving end may include the following steps:

[0180] Step S7: Perform waveform decoding on the received signal to obtain the corresponding frequency domain received data.

[0181] Step S8: Extract the received data R from each channel according to the predefined MCSi physical resource mapping table. di .

[0182] Step S9: Send the N received signals to a receiver with layered equalization and demodulation function for equalization and decoding processing.

[0183] 1) First, perform low-order modulation MCS1 data parsing processing, based on the received data R. d1 (Frequency domain data) The receiver can obtain the equalization analysis results under low-order modulation MCS1 through blind equalization.

[0184] 2) Analysis results of equilibrium Perform de-mapping, demodulation, and decoding processes to obtain the parsing results of the MCS1 modulation data;

[0185] De-mapping processing: in, This refers to the de-layer mapping data corresponding to MCS1;

[0186] Demodulation processing: in, This is the demodulated data corresponding to MCS1;

[0187] Decoding process: Among them, Bit MCS 1 This is the final decoding result corresponding to MCS1.

[0188] 3) Channel estimation is performed using the MCS1 parsing results. Data reconstruction at the transmitter can be achieved in two ways, thereby enabling channel estimation:

[0189] Data reconstruction method 1 involves hard-decision processing based on the blind equalization result of MCS1 to obtain the demodulated symbol modulation information as the reconstructed transmitter data. (Frequency domain data). Hard decision processing includes: for the lowest-order MCS1 data, processing the blind equalization results... The nearest point to the MCS1 constellation map mapping point is used as the hard-determination result to obtain the reconstructed transmitter data.

[0190] Hard ruling: Q1 is the modulation scheme of MCS1 (using an irregular constellation pattern).

[0191] Data reconstruction method 2, based on the decoding result Bit of MCS1 MCS 1 The data undergoes re-encoding, modulation, and layer mapping processes to obtain the reconstructed data for the transmitting end.

[0192] Re-encode: CodeBit MCS 1 =Coder(Bit) MCS 1 );

[0193] Re-modulation: Y d1 =Modulate(CodeBit) MCS 1 );

[0194] Re-process the layer mapping:

[0195] 4) Based on the received frequency domain data R of MCS1 d1 With reconstructed transmitter frequency domain data Channel estimation processing is performed to obtain raw channel estimation information. For example, the least squares (LS) algorithm can be used for channel estimation, but this disclosure is not limited to this.

[0196] Channel estimation processing:

[0197] 5) Perform noise reduction processing (such as filtering) on ​​the original channel estimation information, and perform channel estimation interpolation processing on all MCS2 to MCSN resource locations to obtain the channel estimation results corresponding to the MCS2 to MCSN resource locations.

[0198] Channel estimation for other MCS: H MCS,i,L =Inter(filter(H) LS,L ) Time,Freq ), i = 2, ..., N.

[0199] 6) Based on the received frequency domain data and channel estimation results from MCS2 to MCSN, perform MIMO equalization processing to obtain analytical information, and then perform de-mapping processing to obtain the de-mapping data.

[0200] MIMO equalization processing:

[0201] De-mapping:

[0202] 7) Demodulate the other N-1 channels of data separately to obtain...

[0203] demodulation:

[0204] 8) Decode the other N-1 channels of data to obtain the parsed data BitMCSi for the other MCSs;

[0205] Decoding:

[0206] 9) Concatenate the N-way parsed data and send the combined Cyclic Redundancy Check (CRC) result to the higher layer.

[0207] Through the steps described above in the embodiments of this disclosure, multi-order hybrid modulation and demodulation of data can be realized in a pilotless communication system, achieving high-order modulation and multi-stream transmission. This solves the problem that it is difficult to improve the performance of pilotless communication systems in high-order modulation and multi-stream transmission in related technologies, and achieves the technical effect of improving data transmission efficiency and transmission quality.

[0208] In one embodiment of this disclosure, based on the communication system in FIG6, the processing flow of the sending end may include the following steps:

[0209] Step S1': Based on the N-way MCS configuration and their respective physical resource allocation parameters (such as resource proportion), determine the total bit data BitMCS corresponding to the N types of MCS from the original bit data; and encode the BitMCS to obtain the encoded data X. d ;

[0210] Step S2': Based on the N-way MCS configuration and their respective physical resource allocation parameters, adjust X... d Perform splitting processing to obtain N-way encoded data X di .

[0211] Step S3, according to MCS1(Q1) to MCSN(Q) respectively N The modulation scheme is used to perform N-channel modulation processing to obtain the modulated data Y.di Y di =Modulate(X) d1 Q i ), i = 1, 2, ... N.

[0212] Step S4: The N modulated data are subjected to layer mapping processing to obtain Y. di,L .

[0213] Step S5: According to the predefined physical resource mapping table, respectively, Y... di,L Mapped to the corresponding physical resource (RE).

[0214] Step S6: After waveform processing, the data from the transmitting end is converted into a time-domain transmission signal (i.e., time-domain data) for transmission.

[0215] The difference between this embodiment and the previous embodiment is that this example first performs encoding processing, splitting the encoded data into N-channel encoded data, which can reduce the complexity of the encoding processing and improve the encoding efficiency. Other processing steps, such as modulation processing, layer mapping processing, physical resource mapping processing, waveform processing, etc., are the same as those described in the previous embodiment, and will not be repeated here.

[0216] Furthermore, the processing flow of the receiving end in this embodiment is basically the same as that in the previous embodiment. The difference is that the demodulated data in this embodiment is no longer decoded separately. Instead, after generating N demodulated data, the N demodulated data are merged first, and then the merged data is decoded.

[0217] To better illustrate the communication method in this disclosure, it will be further described below in conjunction with specific parameter configurations and scenarios.

[0218] Example 1: Assuming a single-input single-output (SISO) OFDM communication system, the data is a single stream, the base station and user equipment are configured with a single antenna, and the number of scheduled RBs is 1, the initial parameter determination process of the transmitter in this disclosure is as follows:

[0219] 1) Determine the value of N in this transmission block; N is 2.

[0220] 2) The MCS level and modulation scheme are determined by the higher-level scheduling; MCS1 corresponds to QPSK modulation, and MCS2 corresponds to 64QAM modulation; the method by which the higher-level scheduling determines the MCS level is not limited. For example, it can be represented by MCS1 (Q1=2) and MCS2 (Q2=6).

[0221] 3) Determine the RE resource ratio for MCS1 transmission a1 = 12 / 168; and the RE resource ratio for MCS2 transmission a2 = 156 / 168;

[0222] 4) Determine the resource mapping patterns of MCS1 and MCS2, and construct them according to the resource mapping generation criteria (i.e., resource allocation generation criteria). The receiving end and the sending end determine the patterns according to the predefined method.

[0223] The predefined resource mapping generation criteria in this embodiment are as follows:

[0224] The lowest-order MCS method, MCS1, has a total number of mapping symbols of l. num =2 / 4;

[0225] The lowest-order MCS mode, MCS1, has a frequency domain RE spacing of Δk = 2 / 4;

[0226] The lowest-order MCS method, MCS1, satisfies the configured resource ratio of total REs, 12 / Δk·l. num =12;

[0227] The starting index position in the frequency domain is k0 = mod(CellID, 12), and here it is shown as k0 = 1.

[0228] The lowest-order MCS mode, MCS1, has its time-domain start symbol configured as 0.

[0229] The lowest-order MCS has a RE single-layer symbol spacing configuration of 4 / 7 / 13.

[0230] In this embodiment, based on the aforementioned parameter configuration and resource mapping generation criteria, the resource mapping pattern can be determined as shown in Figures 7, 8, and 9. Each RB includes 12*14 REs, where 12 represents the number of frequency domain resource partitions (e.g., subcarriers) and 14 represents the number of time domain resource partitions (e.g., OFDM symbols). In a single-stream, two-MCS hybrid modulation transmission scenario, the gray squares in Figures 7, 8, and 9 indicate the RE positions corresponding to MCS1 within the RB, and the remaining squares represent the RE positions corresponding to MCS2.

[0231] Figure 7 is a schematic diagram (I) of the resource mapping pattern of two MCS hybrid modulation transmissions according to an embodiment of the present disclosure. As shown in Figure 7, the total number of mapped symbols for MCS1 is 2, and the interval between symbols in a single layer is 7, that is, MCS1 occupies time domain symbols 0 and 7. The frequency domain RE interval is 2, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to MCS2.

[0232] Figure 8 is a schematic diagram (II) of the resource mapping pattern of two MCS hybrid modulation transmissions according to an embodiment of this disclosure. As shown in Figure 8, the total number of mapped symbols for MCS1 is 2, and the interval between symbols in a single layer is 13. That is, MCS1 occupies time domain symbols 0 and 13, the frequency domain RE interval is 2, the frequency domain start index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to MCS2.

[0233] Figure 9 is a schematic diagram (III) of the resource mapping pattern for hybrid modulation transmission of two MCSs according to an embodiment of this disclosure. As shown in Figure 9, the total number of mapped symbols for MCS1 is 4, and the interval between symbols in a single layer is 4. That is, MCS1 occupies time-domain symbols 0, 4, 8, and 12, and the frequency-domain RE interval is 4. The frequency-domain starting index position is 1, and the corresponding frequency-domain positions are 1, 5, and 9. The remaining positions are all RE positions corresponding to MCS2.

[0234] In this embodiment, the sending end processing flow is as follows:

[0235] 1) The original bit data is split into two data streams (Bit) according to the 2-channel MCS configuration and their respective physical resource allocation parameters. MCS1 And Bit MCS2 ;

[0236] 2) For two-way Bit MCS1 And Bit MCS2 The data is encoded separately to obtain two encoded data streams X. d1 and X d2 ;

[0237] 3) Perform two-channel modulation processing according to the modulation schemes of MCS1 (Q1=2) and MCS2 (Q2=6) respectively to obtain the modulated data Y. d1 Y d2 Y d1 =Modulate(X) d1 Q1) = Modulate(X d1 ,2); Y d2 =Modulate(X) d2 Q2) = Modulate(X d2 ,6).

[0238] 4) Based on the predefined physical resource mapping table, assign Y to each of the following: d1 Y d2 The data is mapped to the corresponding physical resource (RE) to obtain the frequency domain data of the transmitting end.

[0239] 5) The data (frequency domain data) at the transmitting end is processed into waveforms and then converted into a time domain transmission signal for data transmission.

[0240] In one exemplary embodiment, the receiving end processing flow is as follows:

[0241] 1) The received signal undergoes waveform demodulation to obtain the corresponding scheduled frequency domain received data;

[0242] 2) Based on the predefined physical resource mapping tables of MCS1 and MCS2, extract the received signal R respectively. d1 R d2 .

[0243] 3) Send the two received signals to a receiver with layered equalization and demodulation capabilities for equalization and decoding processing. The steps are as follows:

[0244] (1) First, perform low-order modulation MCS1 data parsing processing, based on the received R... d1 The receiver can obtain the equalization analysis results under low-order modulation through blind detection equalization.

[0245] (2) According to The equalization analysis results are de-layered, demodulated and decoded to obtain the MCS1 modulation data analysis results.

[0246] De-mapping: In this embodiment, single-layer transmission is used, and L = 1;

[0247] demodulation:

[0248] Decoding:

[0249] (3) Channel estimation is performed using the parsing results of MCS1. Here, the method based on... The transmitted data is reconstructed using hard-decision processing of the equalization analysis results. In this case, the data RE uses QPSK modulation. We calculate the equalization results separately. The nearest point to the QPSK constellation map is used as the hard decision result to obtain the modulation symbol information at the transmitting end.

[0250] Hard ruling:

[0251] (4) Based on the received frequency domain data and the transmitter frequency domain data reconstructed by hard decision, perform LS channel estimation processing to obtain the original channel estimation information H. LS,1 .

[0252] Channel estimation:

[0253] (5) After denoising the original channel estimation information and interpolating the MCS2 resource locations, the channel estimation information H corresponding to the MCS2 resource locations is obtained. MCS 2，1 .

[0254] Filtering and interpolation processing: H MCS 2，1 =Inter(filter(H) LS，1 ) Time,Freq ).

[0255] (6) Based on the received frequency domain data and channel estimation results of MCS2, perform equalization processing to obtain the parsing information, namely the equalization processing result of MCS2.

[0256] Balanced processing:

[0257] (7) Based on the equalization processing result of MCS2, perform de-mapping, demodulation and decoding processing in sequence to obtain the parsing result of MCS2.

[0258] De-mapping:

[0259] demodulation:

[0260] Decoding:

[0261] 4) Concatenate the parsing results of MCS1 and MCS2 and send them together with the CRC check result to the higher layer.

[0262] In another exemplary embodiment, the receiving end processing flow is as follows:

[0263] 1) The received signal undergoes waveform demodulation to obtain the corresponding scheduled frequency domain received data;

[0264] 2) Based on the predefined physical resource mapping tables of MCS1 and MCS2, extract the received signal R respectively. d1 R d2 .

[0265] 3) Send the two received signals to a receiver with layered equalization and demodulation capabilities for equalization and decoding processing. The steps are as follows:

[0266] (1) First, perform low-order modulation MCS1 data parsing processing, based on the received R... d1 The receiver can obtain the equalization analysis results under low-order modulation through blind detection equalization.

[0267] (2) According to The equalization analysis results are subjected to de-layer mapping, demodulation and decoding to obtain the MCS1 modulation data analysis results;

[0268] De-mapping: In this embodiment, single-layer transmission is used, and L = 1;

[0269] demodulation:

[0270] Decoding:

[0271] (3) Channel estimation is performed using the parsing results of MCS1. Instead of hard decision processing, the data is re-encoded, modulated, and layer-mapped based on the decoded results. The layer-mapped data is then used as the data for the transmitting end.

[0272] Re-encoded: CodeBit MCS 1 =Coder(Bit) MCS 1 );

[0273] Readjust: Y d1 =Modulate(CodeBit) MCS 1 );

[0274] Re-mapping:

[0275] (4) Based on the received frequency domain data and the reconstructed transmitter frequency domain data, perform LS channel estimation processing to obtain the original channel estimation information H. LS,1 .

[0276] Channel estimation:

[0277] (5) After denoising the original channel estimation information and interpolating the MCS2 resource locations, the channel estimation information H corresponding to the MCS2 resource locations is obtained. MCS 2，1 .

[0278] Filtering and interpolation processing: H MCS 2，1 =Inter(filter(H) LS，1 ) Time,Freq ).

[0279] (6) Based on the received frequency domain data and channel estimation results of MCS2, perform equalization processing to obtain the parsing information, namely the equalization processing result of MCS2.

[0280] Balanced processing:

[0281] (7) Based on the equalization processing result of MCS2, perform de-mapping, demodulation and decoding processing in sequence to obtain the parsing result of MCS2.

[0282] De-mapping:

[0283] demodulation:

[0284] Decoding:

[0285] 4) Concatenate the parsing results of MCS1 and MCS2 and send them together with the CRC check result to the higher layer.

[0286] Example 2: Assuming a two-layer data transmission system in an OFDM MIMO communication system, with dual antennas configured for both the base station and the user, and a scheduled RB count of 1, the process for determining the initial parameters of the transmitter in this disclosure is as follows.

[0287] 1) Determine the value of N in this transmission block; N is 2.

[0288] 2) The MCS level and modulation scheme are determined by the higher-level scheduling; MCS1 corresponds to QPSK modulation, and MCS2 corresponds to 64QAM modulation; the method by which the higher-level scheduling determines the MCS level is not limited. For example, it can be represented by MCS1 (Q1=2) and MCS2 (Q2=6).

[0289] 3) Determine the RE resource ratio for MCS1 transmission a1 = 12 / 168; and the RE resource ratio for MCS2 transmission a2 = 156 / 168;

[0290] 4) Determine the resource mapping patterns of MCS1 and MCS2, and construct them according to the predefined resource mapping generation criteria (i.e., resource allocation generation criteria). The receiving end and the sending end determine the patterns according to the predefined method.

[0291] In one exemplary embodiment, Example 1 of the predefined resource mapping generation criteria is as follows:

[0292] The lowest-order multi-layer resource mappings have the same RE location;

[0293] The lowest-order MCS method, MCS1, has a total number of mapping symbols of l. num =2 / 4;

[0294] The lowest-order MCS mode, MCS1, has a frequency domain RE spacing of Δk = 2 / 4;

[0295] The lowest-order MCS method, MCS1, has a total RE count that satisfies the resource allocation ratio of 12 / Δk·l. num ·1=12;

[0296] The starting index position in the frequency domain is k0 = mod(CellID, 12), and here it is shown as k0 = 1.

[0297] The lowest-order MCS mode, MCS1, has its time-domain start symbol position configured as symbol 0.

[0298] The lowest-order MCS has a RE single-layer symbol spacing configuration of 4 / 7 / 13.

[0299] In this embodiment, based on the parameter configuration and resource mapping generation criterion example 1 described above, the resource mapping pattern can be determined as shown in Figures 10, 11, and 12. Each RB includes 12*14 REs, where 12 represents the number of frequency domain resource partitions (e.g., subcarriers) and 14 represents the number of time domain resource partitions (e.g., OFDM symbols). In the scenario of dual-stream, dual-layer mapping with the same RE position and hybrid modulation transmission of two MCSs, the gray squares in Figures 10, 11, and 12 indicate the corresponding RE positions of MCS1's layer 1 and layer 2 in the RB, and the remaining squares represent the corresponding RE positions of MCS2's layer 1 and layer 2.

[0300] Figure 10 is a schematic diagram (I) of a resource mapping pattern with the same RE position in two layers according to an embodiment of the present disclosure. As shown in Figure 10, the total number of mapping symbols corresponding to layers 1 and 2 of MCS1 is 2, and the interval between single-layer symbols is 7, that is, layers 1 and 2 of MCS1 occupy time domain symbols 0 and 7, respectively. The frequency domain RE interval is 2, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to MCS2.

[0301] Figure 11 is a schematic diagram (II) of a resource mapping pattern with the same RE position in two layers according to an embodiment of this disclosure. As shown in Figure 11, the total number of mapping symbols in layers 1 and 2 of MCS1 is 2, and the interval between symbols in a single layer is 13. That is, MCS1 occupies time domain symbols 0 and 13, the frequency domain RE interval is 2, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to layers 1 and 2 of MCS2.

[0302] Figure 12 is a schematic diagram (III) of a resource mapping pattern with the same RE position in two layers according to an embodiment of this disclosure. As shown in Figure 12, the total number of mapping symbols in MCS1 layer 1 and layer 2 is 4, and the interval between symbols in a single layer is 4. That is, MCS1 occupies time domain symbols 0, 4, 8, 12, the frequency domain RE interval is 4, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 5, 9. The remaining positions are all RE positions corresponding to MCS2 layer 1 and layer 2.

[0303] In another exemplary embodiment, Example 2 of the predefined resource mapping generation criteria is as follows:

[0304] The lowest-order multi-layer resource mapping is used to locate different RE positions;

[0305] The lowest-tier MCS allocates RE resources equally across different tiers.

[0306] The lowest-order MCS method, MCS1, has a total number of mapping symbols of l. num =2;

[0307] The lowest-order MCS mode has a frequency domain RE spacing of Δk = 4;

[0308] The lowest-order MCS method, MCS1, has a total RE count that satisfies the resource allocation ratio of 12 / Δk·l. num L = 12;

[0309] The lowest-order MCSRE single-layer symbol spacing is configured as 7 / 12 / 13;

[0310] The starting index position of the frequency domain of layer 1 is set according to k0 = mod(CellID, 12), which is shown here as k0 = 1. The starting position of the frequency domain of layer 2 is configured to be 2 units apart from that of layer 1.

[0311] The time-domain start symbol position of layer 1 is symbol 0, and the inter-layer symbol interval is configured as 0 / 1.

[0312] In this embodiment, based on the parameter configuration and resource mapping generation criterion example 2 described above, the resource mapping pattern can be determined as shown in Figures 13, 14, and 15. Each RB includes 12*14 REs, where 12 represents the number of frequency domain resource partitions (e.g., subcarriers) and 14 represents the number of time domain resource partitions (e.g., OFDM symbols). In the scenario of dual-stream, multi-layer mapping with different RE positions and mixed modulation transmission of two MCSs, the black and gray squares in Figures 13, 14, and 15 respectively indicate the RE positions corresponding to layers 1 and 2 of MCS1 in the RB, and the remaining positions are all the RE positions corresponding to layers 1 and 2 of MCS2.

[0313] Figure 13 is a schematic diagram (I) of a resource mapping pattern for different RE positions in a two-layer mapping according to an embodiment of the present disclosure. As shown in Figure 13, the total number of mapping symbols corresponding to layers 1 and 2 of MCS1 is 2, the interval between single-layer symbols is 7, the time domain start symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 0, that is, layers 1 and 2 of MCS1 occupy time domain symbols 0 and 7 respectively. The frequency domain RE interval of the same transmission layer is 4, the frequency domain start index position of layer 1 is 1, and the RE resources of different layers are evenly distributed. Therefore, the frequency domain positions corresponding to layer 1 of MCS1 are 1, 5, and 9, and the frequency domain positions corresponding to layer 2 of MCS1 are 3, 7, and 11. The remaining positions are all RE positions corresponding to layers 1 and 2 of MCS2.

[0314] Figure 14 is a schematic diagram (II) of a resource mapping pattern for different RE positions in a two-layer mapping according to an embodiment of this disclosure. As shown in Figure 14, the total number of mapping symbols for layers 1 and 2 of MCS1 is 2, the interval between symbols in a single layer is 13, the starting symbol position in the time domain of layer 1 is 0, and the interval between symbols in the layers is configured as 0. That is, layers 1 and 2 of MCS1 occupy time domain symbols 0 and 13 respectively. The frequency domain RE interval is 4, the starting index position in the frequency domain is 1, and the RE resources of different layers are evenly distributed. Therefore, the frequency domain positions corresponding to layer 1 of MCS1 are 1, 5, and 9, and the frequency domain positions corresponding to layer 2 of MCS1 are 3, 7, and 11. The remaining positions are all RE positions corresponding to layers 1 and 2 of MCS2.

[0315] Figure 15 is a schematic diagram (III) of a resource mapping pattern for different RE positions in a two-layer mapping according to an embodiment of this disclosure. As shown in Figure 15, the total number of mapping symbols for MCS1 layer 1 and layer 2 is 2, the interval between symbols in a single layer is 12, the time domain starting symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 1. That is, layer 1 of MCS1 occupies time domain symbols 0 and 12, and layer 2 of MCS1 occupies time domain symbols 1 and 13. The frequency domain RE interval is 4, the frequency domain starting index position is 1, and the RE resources of different layers are evenly distributed. Therefore, the frequency domain positions corresponding to layer 1 of MCS1 are 1, 5, and 9, and the frequency domain positions corresponding to layer 2 of MCS1 are 3, 7, and 11. The remaining positions are all RE positions corresponding to layers 1 and 2 of MCS2.

[0316] In this embodiment, the sending end processing flow is as follows:

[0317] 1) The raw bits are used to calculate the encoding rate based on the 2-way MCS configuration and their respective physical resource allocation parameters, and the total bit data is used to calculate the encoding rate. all The data encoding process is completed, and the encoded data X is obtained. d ;

[0318] Encoding processing: X d =Coder(Bit) all );

[0319] 2) For X d The data is split and processed to obtain two coded data X channels under different modulation schemes. d1 and X d2 ;

[0320] 3) Perform two-channel modulation processing according to the modulation schemes of MCS1 (Q1=2) and MCS2 (Q2=6) respectively to obtain the modulated data Y. d1 Y d2 Y d1 =Modulate(X) d1 Q1) = Modulate(X d1 ,2); Yd2 =Modulate(X) d2 Q2) = Modulate(X d2 ,6);

[0321] 4) Regarding Y d1 Y d2 Layered processing is performed to obtain two channels of two-layer transmission data Y. d1，L1 / L2 Y d2，L1 / L2 ;

[0322] 5) Based on the predefined physical resource mapping table, assign Y to each of the following: d1，L1 / L2 Y d2，L1 / L2 The data is mapped to the corresponding physical resource (RE) to obtain the frequency domain data of the transmitting end.

[0323] 6) After waveform processing of the frequency domain data at the transmitting end, it is converted into a time domain transmission signal for data transmission.

[0324] Example 3: Assuming an OFDM MIMO communication system with four data layers, both the base station and user equipment are configured with four antennas, and the number of scheduled RBs is 1, the initial parameter determination process of the transmitter in this disclosure is as follows:

[0325] 1) Determine the value of N in this transport block; N is 2.

[0326] 2) The MCS level and modulation scheme are determined by the higher-level scheduling; MCS1 corresponds to QPSK modulation, and MCS2 corresponds to 64QAM modulation; the method by which the higher-level scheduling determines the MCS level is not limited. For example, it can be represented by MCS1 (Q1=2) and MCS2 (Q2=6).

[0327] 3) Determine one configuration where the RE resource ratio for MCS1 transmission is a1 = 12 / 168 and the RE resource ratio for MCS2 transmission is a2 = 156 / 168; and another configuration where the RE resource ratio for MCS1 transmission is a1 = 16 / 168 and the RE resource ratio for MCS2 transmission is a2 = 152 / 168.

[0328] 4) Determine the schematic diagrams of resource mapping for MCS1 and MCS2, and construct them according to the predefined resource mapping generation criteria (i.e., resource allocation generation criteria). The receiving end and the sending end determine the diagrams according to the predefined method.

[0329] In one exemplary embodiment, Example 3 of the predefined resource mapping generation criteria is as follows:

[0330] The lowest-order multi-level resource mappings have the same RE location;

[0331] The lowest-order MCS method, MCS1, has a total number of mapping symbols of l. num =2 / 4;

[0332] The lowest-order MCS mode, MCS1, has a frequency domain RE spacing of Δk = 2 / 4;

[0333] The lowest-order MCS method, MCS1, has a total RE count that satisfies the resource allocation ratio of 12 / Δk·l. num ·1=12;

[0334] The starting index position in the frequency domain is determined by k0 = mod(CellID, 12), but here we use k0 = 1 to illustrate.

[0335] The lowest-order MCS mode, MCS1, has a time-domain start symbol position of 0.

[0336] The lowest-order MCS has a RE single-layer symbol spacing configuration of 4 / 7 / 13.

[0337] In this embodiment, based on the parameter configuration and resource mapping generation criterion example 3 described above, the resource mapping pattern can be determined as shown in Figures 16, 17, and 18. Each RB includes 12*14 REs, where 12 represents the number of frequency domain resource partitions (e.g., subcarriers) and 14 represents the number of time domain resource partitions (e.g., OFDM symbols). In scenarios involving multi-stream, multi-layer (N=4) mapping of the same RE positions and mixed modulation transmission of two MCSs, the gray squares in Figures 16, 17, and 18 indicate the RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS1 in the RB, and the remaining squares represent the RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0338] Figure 16 is a schematic diagram (I) of a resource mapping pattern with the same RE position in multiple layers according to an embodiment of the present disclosure. As shown in Figure 16, the total number of mapping symbols corresponding to layers 1 / 2 / 3 / 4 of MCS1 is 2, and the interval between symbols in a single layer is 7, that is, layers 1 / 2 / 3 / 4 of MCS1 occupy time domain symbols 0 and 7. The frequency domain RE interval of MCS1 is 2, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0339] Figure 17 is a schematic diagram (II) of a resource mapping pattern with the same RE position in multiple layers according to an embodiment of this disclosure. As shown in Figure 17, the total number of mapping symbols for layers 1 / 2 / 3 / 4 of MCS1 is 2, and the interval between symbols in a single layer is 13. That is, layers 1 / 2 / 3 / 4 of MCS1 occupy time domain symbols 0 and 13, the frequency domain RE interval is 2, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 3, 5, 7, 9, 11. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0340] Figure 18 is a schematic diagram (III) of a resource mapping pattern for multiple layers mapping the same RE position according to an embodiment of this disclosure. As shown in Figure 18, the total number of mapping symbols for MCS1 layers 1 / 2 / 3 / 4 is 4, and the interval between symbols in a single layer is 4. That is, MCS1 layers 1 / 2 / 3 / 4 occupy time domain symbols 0, 4, 8, 12, the frequency domain RE interval is 4, the frequency domain starting index position is 1, and the corresponding frequency domain positions are 1, 5, 9. The remaining positions are all RE positions corresponding to MCS2 layers 1 / 2 / 3 / 4.

[0341] In another exemplary embodiment, Example 4 of the predefined resource mapping generation criteria is as follows:

[0342] The lowest-order multi-layer resource mapping is used to locate different RE positions;

[0343] The lowest-level MCS distributes RE resources equally across different layers.

[0344] The lowest-order MCS method, MCS1, has a total number of mapping symbols of l. num =2 / 3;

[0345] The lowest-order MCS mode, MCS1, has a frequency domain RE spacing of Δk = 6 / 12;

[0346] The lowest-order MCS method, MCS1, has a total RE count that satisfies the resource allocation ratio of 12 / Δk·l. num L = 12 / 16;

[0347] The symbol spacing of a single RE layer in the lowest-order MCS is 6 / 7;

[0348] The starting index position of the frequency domain of layer 1 is set according to k0 = mod(CellID, 12), and here it is shown as k0 = 1. The interval of the starting position of the frequency domain between layers is configured as 1 / 3.

[0349] In the lowest-order MCS mode, the starting symbol position of MCS1 layer 1 in the time domain is 0, and the inter-layer symbol interval is configured as 0 / 2.

[0350] In this embodiment, based on the parameter configuration and resource mapping generation criterion example 4 described above, the resource mapping patterns shown in Figures 19, 20, 21, and 22 can be determined. Each RB includes 12*14 REs, where 12 represents the number of frequency domain resource partitions (e.g., subcarriers) and 14 represents the number of time domain resource partitions (e.g., OFDM symbols). In scenarios involving multi-stream, multi-layer (N=4) mapping of different RE positions and mixed modulation transmission of two MCSs, the different padding patterns in Figures 19, 20, 21, and 22 respectively indicate the RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS1 in the RB, with the remaining positions representing the RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2. Specifically, the resource ratio configuration for MCS1 in Figure 19 is 12 / 168, and the resource ratio configuration for MCS1 in Figures 20, 21, and 22 is 16 / 168.

[0351] Figure 19 is a schematic diagram (I) of the resource mapping pattern of different RE positions in a multi-layer mapping according to an embodiment of the present disclosure. As shown in Figure 19, the total number of mapping symbols corresponding to layers 1 / 2 / 3 / 4 of MCS1 is 3, the interval between symbols in a single layer is 6, the time domain starting symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 0. That is, layers 1 / 2 / 3 / 4 of MCS1 occupy time domain symbols 0, 6, and 12, respectively. The intra-layer frequency domain RE interval is 12, the frequency domain starting index position of layer 1 of MCS1 is 1, the RE resources of different layers are evenly distributed, and the inter-layer frequency domain interval is 3. Therefore, the frequency domain positions corresponding to layers 1 / 2 / 3 / 4 of MCS1 are 1 / 4 / 7 / 10, respectively. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0352] Figure 20 is a schematic diagram (II) of the resource mapping pattern of different RE positions in a multi-layer mapping according to an embodiment of the present disclosure. As shown in Figure 20, the total number of mapping symbols for layers 1 / 2 / 3 / 4 of MCS1 is 2, the interval between symbols in a single layer is 7, the time domain start symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 0. That is, layers 1 / 2 / 3 / 4 of MCS1 occupy time domain symbols 0 and 7, and the frequency domain RE interval is 6. The frequency domain start index position of layer 1 of MCS1 is 1, and the inter-layer frequency domain interval is 1. The RE resources of different layers are evenly distributed. Therefore, the frequency domain position corresponding to layer 1 of MCS1 is 1 / 7, the frequency domain position corresponding to layer 2 of MCS1 is 2 / 8, the frequency domain position corresponding to layer 3 of MCS1 is 3 / 9, and the frequency domain position corresponding to layer 4 of MCS1 is 4 / 10. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0353] Figure 21 is a schematic diagram (III) of the resource mapping pattern of different RE positions in a multi-layer mapping according to an embodiment of the present disclosure. As shown in Figure 21, the total number of mapping symbols in MCS1 layers 1 / 2 / 3 / 4 is 2, the interval between symbols in a single layer is 7, the time domain start symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 2. That is, layer 1 of MCS1 occupies time domain symbols 0 and 7, layer 2 of MCS1 occupies time domain symbols 2 and 9, layer 3 of MCS1 occupies time domain symbols 4 and 11, and layer 4 of MCS1 occupies time domain symbols 6 and 13. The intra-layer frequency domain RE interval is 6, the frequency domain start index position of MCS1 layer 1 is 1, the inter-layer frequency domain interval is 1, and the RE resources of different layers are evenly distributed. Therefore, the frequency domain positions corresponding to layer 1 of MCS1 are 1 and 7, the frequency domain positions corresponding to layer 2 of MCS1 are 2 and 8, the frequency domain positions corresponding to layer 3 of MCS1 are 3 and 9, and the frequency domain positions corresponding to layer 4 of MCS1 are 4 and 10. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0354] Figure 22 is a schematic diagram (IV) of a resource mapping pattern for different RE positions in a multi-layer mapping according to an embodiment of this disclosure. As shown in Figure 22, the total number of mapping symbols for MCS1 layers 1 / 2 / 3 / 4 is 2, the interval between symbols in a single layer is 7, the time-domain start symbol position of layer 1 is 0, and the inter-layer symbol interval is configured as 2. That is, layer 1 of MCS1 occupies time-domain symbols 0 and 7, layer 2 of MCS1 occupies time-domain symbols 2 and 9, layer 3 of MCS1 occupies time-domain symbols 4 and 11, and layer 4 of MCS1 occupies time-domain symbols 6 and 13. The intra-layer frequency-domain RE interval is 6, the frequency-domain start index position of MCS1 layer 1 is 1, and the inter-layer frequency-domain start position interval is configured as 0. Therefore, the frequency-domain positions corresponding to layers 1 / 2 / 3 / 4 of MCS1 are 1 and 7. The remaining positions are all RE positions corresponding to layers 1 / 2 / 3 / 4 of MCS2.

[0355] In the embodiments disclosed herein, various resource mapping patterns can be flexibly generated based on different parameter configurations and resource mapping generation criteria, thereby better adapting to different communication environments and possessing stronger versatility.

[0356] According to the communication methods and communication systems proposed in the various embodiments of this disclosure, multi-level hybrid modulation of transmitted data can be realized, achieving the technical effect of predicting the channel information of the complete transmission RE part based on the low-order modulation RE, and enhancing the data parsing of other high-order modulation RE parts by combining the predicted channel estimation, thereby improving the high-order transmission performance of the pilotless communication system and greatly improving the spectral efficiency of the communication system.

[0357] The multi-level hybrid modulation method for transmission RE disclosed herein can design various resource mapping patterns for different transmission modes (single-layer / multi-layer), thereby ensuring that more accurate channel state prediction information can be obtained through low-order modulation RE when transmitting without pilots, and improving the system performance under MIMO multi-stream transmission and high-order modulation.

[0358] This disclosure also implements a receiver architecture for hierarchical parsing processing at the receiving end, which can be combined with the multi-level hybrid modulation design at the transmitting end to improve the receiver processing performance.

[0359] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this disclosure.

[0360] Embodiments of this disclosure also provide a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps in any of the above method embodiments.

[0361] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0362] Embodiments of this disclosure also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0363] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0364] Embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements the steps in any of the method embodiments described above.

[0365] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0366] It is obvious to those skilled in the art that the modules or steps of this disclosure described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this disclosure is not limited to any particular combination of hardware and software.

[0367] The above description is merely an exemplary embodiment of this disclosure and is not intended to limit this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A communication method, comprising: The original bit data is encoded to obtain N-channel encoded data, where N is an integer greater than or equal to 2; The N coded data are modulated using N modulation and coding strategies (MCS) to obtain N modulated data, where each modulated data corresponds to one MCS. The N-channel modulation data are mapped to resource blocks according to a preset physical resource mapping table; The mapped data is subjected to waveform processing to generate a time-domain signal, which is then transmitted via a wireless channel.

2. The method according to claim 1, wherein, Before encoding the raw bit data to obtain N-channel encoded data, the method further includes at least one of the following: Determine the value of N; Determine the configuration of the N types of MCS; Determine the number of layers in the transmission mode; Determine the physical resource allocation parameters for the N types of MCS; Determine the physical resource mapping table.

3. The method according to claim 2, wherein, The encoding process of the original bit data to obtain N-channel encoded data includes: Based on the configuration of the N types of MCS and the physical resource allocation parameters of the N types of MCS, the original bit data is split into N paths of bit data; The N bit data are encoded separately to obtain the N encoded data.

4. The method according to claim 2, wherein, The encoding process of the original bit data to obtain N-channel encoded data includes: Based on the configuration of the N types of MCS and the physical resource allocation parameters of the N types of MCS, determine the total bit data corresponding to the N types of MCS from the original bit data; The total bit data is encoded to obtain the total encoded data; Based on the configuration of the N types of MCS and the physical resource allocation parameters of the N types of MCS, the total encoded data is split into the N channels of encoded data.

5. The method according to claim 2, wherein, Determining the physical resource mapping table includes: In response to N equaling 2, according to the resource allocation generation criteria, a portion of the resource units in the resource block are allocated to the first type of MCS, and all remaining resource units in the resource block are allocated to the second type of MCS, so as to determine the physical resource mapping table; In response to N being greater than 2, the i-th part of the resource units in the resource block is sequentially allocated to the i-th type of MCS according to the resource allocation generation criteria, i = 1, ..., N-1, and all remaining resource units in the resource block are allocated to the N-th type of MCS to determine the physical resource mapping table; The physical resource mapping table includes resource mapping patterns for the N types of MCSs. The resource mapping patterns are used to indicate the time-domain and frequency-domain positions of the resource units corresponding to each MCS in the resource block.

6. The method according to claim 5, wherein, The resource allocation generation criteria include at least one of the following: The physical resource allocation parameters of the N types of MCS meet the preset requirements; The first type of MCS or the i-th type of MCS corresponds to multiple transport layers mapped to the same or different resource units; When multiple transport layers corresponding to the first type of MCS or the i-th type of MCS are mapped to different resource units, the resource units of the multiple transport layers corresponding to the first type of MCS or the i-th type of MCS are allocated equally. In response to N equaling 2, the multiple transport layers corresponding to the second type of MCS are mapped to the same resource unit; In response to N being greater than 2, the multiple transport layers corresponding to the Nth type of MCS are mapped to the same resource unit.

7. The method according to claim 5, wherein, The physical resource allocation parameters for the N types of MCS include at least one of the following: The number of single-layer symbols of the resource unit corresponding to the first type of MCS or the i-th type of MCS; The single-layer symbol spacing of the resource unit corresponding to the first type of MCS or the i-th type of MCS; The frequency domain starting position of the resource unit corresponding to the first type of MCS or the i-th type of MCS; Frequency domain spacing of resource units corresponding to the first type of MCS or the i-th type of MCS; The resource proportion of the resource unit corresponding to the first type of MCS or the i-th type of MCS; The resource percentage of the resource unit corresponding to the Nth type of MCS; The starting symbol of the resource units of multiple transport layers corresponding to the first type of MCS or the i-th type of MCS; The symbol spacing between resource units of multiple transport layers corresponding to the first type of MCS or the i-th type of MCS.

8. The method according to claim 1, wherein, The step of mapping the N channels of modulated data to resource blocks according to a preset physical resource mapping table includes: The N modulated data streams are layer-mapped according to the layer number of the transmission mode, and the layer-mapped data is mapped to corresponding resource units according to the physical resource mapping table. Each resource block includes multiple resource units, and each resource unit corresponds to one MCS and one transmission layer; or... The N modulated data streams are mapped to corresponding resource units according to the physical resource mapping table. The resource block includes multiple resource units, and each resource unit corresponds to a type of MCS.

9. The method according to claim 1, wherein, All N types of MCS employ irregular modulation constellation diagrams; The first MCS among the N types of MCS is the lowest-order MCS among the N types of MCS; The last of the N MCSs is the highest-order MCS among the N MCSs.

10. A communication method, wherein, include: The time-domain signal is received through a wireless channel, and the time-domain signal is subjected to waveform decoding. The de-waveform data is demapped according to a preset physical resource mapping table corresponding to N modulation and coding strategies (MCS) to obtain N channels of frequency domain received data, where N is an integer greater than or equal to 2. The N frequency domain received data are subjected to hierarchical equalization demodulation and decoding processing according to the N types of MCS to obtain N decoded data, wherein each decoded data corresponds to one type of MCS; The N decoded data streams are combined to obtain the parsed bit data.

11. The method according to claim 10, wherein, Before performing demapping processing on the de-waveformed data according to a preset physical resource mapping table corresponding to N modulation and coding strategies (MCS) to obtain N channels of frequency domain received data, the method further includes at least one of the following: Determine the value of N; Determine the configuration of the N types of MCS; Determine the number of layers in the transmission mode; Determine the physical resource allocation parameters for the N types of MCS; Determine the physical resource mapping table.

12. The method according to claim 11, wherein, The step of performing layered equalization demodulation and decoding processing on the N channels of frequency domain received data according to the N types of MCS to obtain N channels of decoded data includes: Based on the first MCS among the N types of MCS, perform layered equalization demodulation and decoding processing on the first frequency domain received data in the N frequency domain received data to obtain the first decoded data, wherein the first MCS is the lowest order MCS among the N types of MCS; Channel estimation processing is performed on the first frequency domain received data to obtain the original channel estimation information; Based on the original channel estimation information and the physical resource mapping table, channel estimation information for the j-th MCS among the N types of MCS is generated. Then, based on the channel estimation information of the j-th MCS and the j-th frequency domain received data, hierarchical equalization demodulation and decoding processing are performed to obtain the j-th decoded data, where j = 2, ..., N.

13. The method according to claim 12, wherein, The step of performing layered equalization demodulation and decoding processing on the first channel of frequency domain received data from the N channels of frequency domain received data according to the first MCS among the N types of MCS, to obtain the first channel of decoded data, includes: Blind detection equalization parsing processing is performed on the first frequency domain received data according to the first type of MCS to obtain the first equalization parsing result. The first path equalization parsing result is subjected to de-layer mapping processing according to the layer number of the transmission mode to obtain the first path de-layer mapping data; The first demodulated data is obtained by demodulating the first layer-by-layer mapping data according to the first type of MCS. The first demodulated data is decoded to obtain the first decoded data.

14. The method according to claim 13, wherein, The step of performing channel estimation processing based on the first frequency domain received data to obtain raw channel estimation information includes: Hard decision processing is performed based on the first equalization parsing result to reconstruct the transmitting end data; or, encoding, modulation and layer mapping processing are performed again based on the first decoded data to reconstruct the transmitting end data. Channel estimation processing is performed based on the first frequency domain received data and the reconstructed transmitter data to obtain the original channel estimation information.

15. The method according to claim 14, wherein, The step of generating channel estimation information for the j-th MCS among the N MCSs based on the original channel estimation information and the physical resource mapping table includes: The original channel estimation information is then subjected to noise reduction processing; Based on the physical resource mapping table and the original channel estimation information after noise reduction, channel estimation interpolation is performed on the resource location of the j-th type of MCS to obtain the channel estimation information of the j-th type of MCS.

16. The method of claim 14, wherein, The step of performing hierarchical equalization demodulation and decoding processing based on the channel estimation information of the j-th type of MCS and the j-th frequency domain received data to obtain the j-th decoded data includes: Based on the channel estimation information of the j-th type of MCS and the j-th frequency domain received data, perform multi-input multi-output MIMO equalization parsing processing to obtain the j-th equalization parsing result; The j-th equalization parsing result is subjected to de-layer mapping processing according to the layer number of the transmission mode to obtain the j-th de-layer mapping data; Demodulate the j-th delayer mapping data according to the j-th type of MCS to obtain the j-th demodulated data. The j-th demodulated data is decoded to obtain the j-th decoded data.

17. A communication system, comprising: The transmitting end is used to encode the original bit data to obtain N coded data, where N is an integer greater than or equal to 2; to perform N modulation processing on the N coded data according to N modulation and coding strategies (MCS) to obtain N modulated data, where each modulated data corresponds to one MCS; to map the N modulated data to resource blocks according to a preset physical resource mapping table; to perform waveform processing on the mapped data to generate a time-domain signal, and to transmit the time-domain signal through a wireless channel; The receiving end is configured to receive the time-domain signal through the wireless channel and perform waveform de-processing on the time-domain signal; perform de-mapping processing on the de-waveformed data according to the physical resource mapping table to obtain N channels of frequency-domain received data; perform hierarchical equalization demodulation and decoding processing on the N channels of frequency-domain received data according to the N types of MCS to obtain N channels of decoded data, wherein each channel of decoded data corresponds to one type of MCS; and merge the N channels of decoded data to obtain parsed bit data.

18. A computer-readable storage medium storing a computer program, wherein, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 16.

19. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 16.

20. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1 to 16.

Images