Data quantization method, device and storage medium

Abstract

The present invention provides a data quantization method, device, and storage medium, relating to the field of wireless communication technology. The method includes: performing digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; the first quantization bit width is determined based on the peak-to-average ratio of the input signal; performing channel estimation and equalization processing on the baseband signal based on a second quantization bit width; the second quantization bit width is obtained based on real-time calculation of the power of pilot symbols in the baseband signal; demodulating the baseband signal after channel estimation and equalization processing, and dynamically truncating the demodulated soft information based on the second quantization bit width and modulation mode to obtain truncated soft information; performing saturation quantization truncation processing on the truncated soft information, and outputting the truncated soft information to a decoder. This optimizes signal quantization accuracy and resource efficiency.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a data quantization method, device and storage medium. Background Art

[0002] In single-carrier communication systems, especially military wireless frequency-hopping systems, each hop of transmission and reception uses a different frequency, resulting in varying frequency-selective fading at each hop. This results in varying amplitudes of the data received at the receiver. Multi-carrier communication systems generally have wider bandwidths and employ orthogonal frequency division multiplexing (OFDM) combined with high-order dual modulation. This results in a high peak-to-average power ratio (peak power to average power ratio) at the transmitter, resulting in large sample amplitude fluctuations in the time domain. OFDM multiple-input multiple-output (MIMO) systems, in particular, often experience multipath fading, which further exacerbates the amplitude fluctuations of the time-domain signal.

[0003] If the communication system uses amplitude modulation (with phase modulation), such as 8-phase shift keying (8PSK), 16-quadrature amplitude modulation (QAM), or higher-order 64QAM or 256QAM amplitude modulation, the amplitude is critical to the overall baseband reception performance. If simple full-scale quantization is used, the entire reception processing data volume and buffer are relatively large. If fixed-amplitude quantization is used, the reception performance will be degraded. Summary of the Invention

[0004] The present invention provides a data quantization method, device and storage medium to solve the defects in the prior art of simple full-scale quantization that the entire receiving and processing data volume and cache are relatively large, and fixed-amplitude quantization processing loses receiving performance, thereby optimizing signal quantization accuracy and resource efficiency.

[0005] The present invention provides a data quantization method, which is applied to a communication system and includes the following steps:

[0006] Performing digital down-conversion processing on the input signal based on a first quantization bit width to obtain a baseband signal; wherein the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0007] performing channel estimation and equalization processing on the baseband signal based on a second quantization bit width; wherein the second quantization bit width is calculated in real time based on power of pilot symbols in the baseband signal;

[0008] Demodulating the baseband signal after the channel estimation and equalization processing, and dynamically truncating the demodulated soft information based on the second quantization bit width and the modulation mode to obtain truncated soft information;

[0009] The truncated soft information is subjected to saturation quantization and truncation processing, and is output to a decoder.

[0010] According to a data quantization method provided by the present invention, a method for determining the first quantization bit width includes:

[0011] Determining a first quantization bit width according to a peak-to-average ratio of the input signal and a corresponding relationship that 1 bit corresponds to 6 dB;

[0012] The first quantization bit width is used as the number of sign bits of the input of the first stage filter of digital down conversion; in the processing process of the multi-stage filter of digital down conversion, the number of sign bits of the input and output of each stage is consistent.

[0013] According to a data quantization method provided by the present invention, a method for calculating the second quantization bit width includes:

[0014] Calculate the power sum of the pilot set within a preset minimum scheduling unit;

[0015] A second quantization bit width is calculated based on the power sum of the pilot set.

[0016] According to a data quantization method provided by the present invention, when the communication system is a single-carrier system, the minimum scheduling unit is a set of multiple pilot symbols and multiple data symbols; the power sum of the pilot set is calculated in the time domain;

[0017] In the case where the communication system is a multi-carrier system, the minimum scheduling unit is a set of frequency domain resource elements and user data resource elements; and the power sum of the pilot set is calculated in the frequency domain.

[0018] According to a data quantization method provided by the present invention, based on the second quantization bit width and the modulation mode, dynamic bit width truncation is performed on the soft information obtained by demodulation to obtain the truncated soft information, including:

[0019] Determining a starting position for dynamically truncating the demodulated soft information based on the second quantization bit width;

[0020] Determining, based on the modulation mode, a third quantization bit width for dynamically truncating the soft information obtained by demodulation;

[0021] Based on the starting position and the third quantization bit width, dynamic bit width truncation is performed on the demodulated soft information to obtain truncated soft information.

[0022] According to a data quantization method provided by the present invention, saturation quantization truncation processing is performed on the truncated soft information, including:

[0023] Merging the soft information after multiple truncation, and expanding the bit width of the merged soft information;

[0024] Based on the third quantization bit width, truncation processing is performed on the soft information after the bit width expansion.

[0025] The present invention also provides a data quantization device, which is applied to a communication system and includes the following modules:

[0026] a first quantization module, configured to perform digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; wherein the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0027] A second quantization module is configured to perform channel estimation and equalization processing on the baseband signal based on a second quantization bit width, wherein the second quantization bit width is calculated in real time based on the power of pilot symbols in the baseband signal;

[0028] a third quantization module, configured to demodulate the baseband signal after the channel estimation and equalization processing, and dynamically truncate the demodulated soft information based on the second quantization bit width and modulation mode to obtain truncated soft information;

[0029] The fourth quantization module is configured to perform saturation quantization and truncation processing on the truncated soft information and output the truncated soft information to a decoder.

[0030] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described data quantization methods when executing the computer program.

[0031] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which implements any of the above-mentioned data quantization methods when executed by a processor.

[0032] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned data quantization methods.

[0033] The data quantization method, device and storage medium provided by the present invention determine a first quantization bit width based on the peak-to-average ratio of the input signal, perform digital down-conversion processing on the input signal according to the first quantization bit width, obtain a second quantization bit width based on real-time calculation of the power of pilot symbols in the baseband signal, perform channel estimation and equalization processing on the baseband signal according to the second quantization bit width, and dynamically truncate the soft information obtained by demodulation based on the second quantization bit width and the modulation mode, and perform saturation quantization truncation processing on the truncated soft information, thereby optimizing signal quantization accuracy and resource efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 It is a processing flow diagram of a communication receiving system provided by related technology.

[0036] Figure 2 It is a flow chart of the data quantification method provided by the present invention.

[0037] Figure 3 It is a schematic diagram of the overall flow of a quantitative embodiment of a communication system provided by the present invention.

[0038] Figure 4 The figure is a schematic diagram of an example of maximum sign bit quantization of DDC down-conversion based on peak-to-average ratio provided by the present invention.

[0039] Figure 5 It is a schematic diagram of the pilot bit width quantization estimation provided by the present invention.

[0040] Figure 6 This is a schematic diagram of the association quantization of the average energy sign bit and the modulation mode provided by the present invention.

[0041] Figure 7 It is a schematic diagram of the saturation quantization of the decoding front end provided by the present invention.

[0042] Figure 8 It is a structural schematic diagram of the data quantization device provided by the present invention.

[0043] Figure 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0044] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0045] Figure 1 It is a processing flow diagram of a communication receiving system provided by related technology, such as Figure 1 As shown in the figure, a typical communication receiving system includes RF-level processing (including RF processing and AD sampling), symbol-level processing (including DDC digital down-conversion to baseband, FFT Fourier transform for multi-carrier systems, time-frequency synchronization for multi-carrier and single-carrier systems, and subsequent channel estimation, equalization, and demodulation), and bit-level processing (including descrambling, rate matching, and decoding of the demodulated bit stream). The RF analog portion (i.e., the portion between RF processing and AD sampling) typically uses analog automatic gain control (AGC) to ensure that the input signal amplitude is within a certain range.

[0046] Existing technologies usually focus on quantizing data at a fixed bit width at a single node, which has the following problems:

[0047] ① The dynamic range and quantization accuracy are poorly matched. When the signal peak-to-average ratio fluctuates, fixed quantization will cause signal truncation distortion or inefficient quantization.

[0048] ② Resource waste: Fixed high-bit quantization leads to waste of power consumption and computing resources, and insufficient modulation matching leads to resource waste;

[0049] ③ Existing technologies only design at a single point in the receiving link, without considering the entire digital domain link of the receiving system. For example, they only consider the input of the decoding front end, that is, the combined quantization of rate matching or Hybrid Automatic Repeat reQuest (HARQ) combined quantization;

[0050] ④ The quantization parameter is based on statistics and belongs to the category of non-real-time quantization technology. It cannot truly reflect the actual soft information amplitude of the current block to be decoded, thus reducing the decoding performance.

[0051] Similarly, some technologies use simple full-scale quantization for the entire link, resulting in a relatively large amount of data and cache for the entire receiving process. Some technologies use fixed-amplitude quantization, and when different modulation modes, such as QPSK and 64QAM, use the same quantization parameters, the 64QAM decoding performance will be greatly reduced.

[0052] To this end, the present invention provides a data quantization method, device and storage medium.

[0053] Figure 2 It is a flow chart of the data quantification method provided by the present invention, such as Figure 2 As shown, the method is applied to a communication system and includes the following steps:

[0054] Step 200: Perform digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; the first quantization bit width is determined based on a peak-to-average ratio of the input signal.

[0055] Step 201: Perform channel estimation and equalization processing on a baseband signal based on a second quantization bit width; the second quantization bit width is obtained by real-time calculation based on the power of pilot symbols in the baseband signal.

[0056] Step 202: Demodulate the baseband signal after channel estimation and equalization processing, and dynamically truncate the demodulated soft information based on the second quantization bit width and the modulation mode to obtain truncated soft information.

[0057] Step 203: Perform saturation quantization and truncation processing on the truncated soft information, and output it to the decoder.

[0058] Specifically, the method provided by the present invention is applied to a receiving end of a communication system, and optimizes signal processing accuracy and resource efficiency through a dynamic quantization strategy.

[0059] First, in embodiments of the present invention, the first quantization bit width can be determined based on the Peak-to-Average Ratio (PAR) of the input signal. The input signal in embodiments of the present invention refers to a digitized signal of intermediate or high frequency (e.g., 16-bit IQ sampled data after AD conversion) obtained by analog-to-digital conversion at a receiving end of a communication system.

[0060] The input signal can be digitally down-converted (DDC) based on the first quantization bit width. The DDC moves the signal to baseband through mixing and filtering, and reduces the sampling rate through a multi-stage decimation filter. The output of this step is a baseband signal with a bit width consistent with the first quantization bit width.

[0061] The second quantization bit width can then be calculated in real time by calculating the power of the pilot symbols in the baseband signal. Channel estimation and equalization are then performed on the baseband signal based on the second quantization bit width. The channel estimation module calculates the channel response using the pilot symbols, and the equalization module corrects the data symbols based on the channel response.

[0062] It is understandable that since channel conditions may change rapidly, the second quantization bit width is dynamically adjusted according to the power of the pilot symbols in the baseband signal, thereby ensuring the accuracy of the intermediate calculation process of channel estimation and equalization processing, while avoiding the waste of resources caused by high bit width.

[0063] After obtaining the baseband signal after channel estimation and equalization, it can be demodulated, and the soft information can be dynamically truncated based on the second quantization bit width and modulation method. The demodulation process maps the baseband signal to soft information. The bit width of the soft information can be adjusted based on the dynamically adjusted second quantization bit width and the complexity of the modulation method used for the received signal.

[0064] Finally, the truncated soft information can be subjected to saturation quantization and output to the decoder. Saturation quantization prevents overflow by limiting the value range and further compresses the data size to meet the decoder's input requirements. This operation should be based on dynamic truncation of soft information, ensuring that key characteristics of soft information are maintained while reducing data complexity, thereby achieving efficient and reliable signal recovery during the decoding stage.

[0065] The data quantization method provided by the present invention determines a first quantization bit width based on a peak-to-average ratio of an input signal, performs digital down-conversion processing on the input signal according to the first quantization bit width, obtains a second quantization bit width based on real-time calculation of the power of pilot symbols in the baseband signal, performs channel estimation and equalization processing on the baseband signal according to the second quantization bit width, and dynamically truncates the soft information obtained by demodulation based on the second quantization bit width and a modulation mode, and performs saturation quantization truncation processing on the truncated soft information, thereby optimizing signal quantization accuracy and resource efficiency.

[0066] According to a data quantization method provided by the present invention, a method for determining the first quantization bit width includes:

[0067] Determining a first quantization bit width according to a peak-to-average ratio of the input signal and a corresponding relationship that 1 bit corresponds to 6 dB;

[0068] The first quantization bit width is used as the number of sign bits of the input of the first stage filter of digital down-conversion; in the processing process of the multi-stage filter of digital down-conversion, the number of sign bits of the input and output of each stage is consistent.

[0069] Specifically, in embodiments of the present invention, the first quantization bit width can be determined based on the peak-to-average power ratio (PAR) of the input signal and the relationship between 1 bit and 6 dB. PAR represents the ratio of peak power to average power (in dB) of a signal and reflects the required dynamic range of the signal.

[0070] For example, if the PAR of the input signal is 12dB@0.01% (the probability of the peak power to average power ratio dB=12DB occurring is 0.01%), then according to the rule that 1 bit covers 6dB of dynamic range, 2 sign bits can be retained (12dB ÷ 6dB / bit = 2 bits).

[0071] The process of determining the first quantization bit width is completed by real-time statistics of the PAR value of the input signal, ensuring that the quantization bit width can cover the signal peak amplitude while avoiding resource waste.

[0072] The first quantization bit width can then be used as the input sign bit count for the first-stage filter of the digital down-conversion. For example, if the input signal is 16-bit IQ data with a PAR of 12dB, the first-stage filter input retains the highest 2 sign bits (e.g., MSB[15:14] in a 16-bit format) and truncates the remaining lower bits.

[0073] In this embodiment of the present invention, during the multi-stage digital down-conversion filter processing, the number of sign bits for each input and output must remain consistent. For example, the output of the first-stage filter may be expanded to 33-40 bits due to the multiplication and accumulation operation, but it must be truncated to 16 bits while retaining the same 2-bit sign bit as the input. This rule is repeated for subsequent filter stages to ensure that the input and output of each stage use the same sign bit width.

[0074] According to a data quantization method provided by the present invention, a method for calculating the second quantization bit width includes:

[0075] Calculate the power sum of the pilot set within a preset minimum scheduling unit;

[0076] A second quantization bit width is calculated based on the power sum of the pilot set.

[0077] Specifically, during the calculation of the second quantization bit width, the sum of the pilot set power can be calculated within a preset minimum scheduling unit. The minimum scheduling unit is the basic data unit processed by the receiving end and typically consists of a set of pilot symbols and data symbols. The pilot set includes all pilot symbols. Pilot symbols are known reference signals, and their power directly reflects the current channel state.

[0078] In some implementations, during the power sum calculation process, all pilot symbols within the minimum scheduling unit may be extracted; then, the instantaneous power (I 2 +Q 2 ); Finally, the power of all pilot symbols is accumulated to obtain the total power (accu_power).

[0079] After calculating the power sum of the pilot set, a second quantization bit width may be calculated based on the power sum. The second quantization bit width is used to guide quantization truncation in the channel estimation and equalization process.

[0080] In some implementations, the second quantization bit width is calculated based on the power sum as follows:

[0081] First, convert the total power sum (accu_power) to average power (avg_power):

[0082] avg_power=accu_power / N; where N represents the number of symbols contained in the pilot set.

[0083] Then, calculate the magnitude (abs_mag):

[0084] abs_mag = abs(avg_power);

[0085] Finally, the quantization bit width (est_width) is determined based on the amplitude (abs_mag):

[0086] est_width=log2(abs_mag).

[0087] All intermediate quantization bits in channel estimation and equalization calculations use est_width as a reference and are dynamically scaled to around this bit width, thereby ensuring quantization accuracy throughout symbol processing while optimizing resource efficiency.

[0088] According to a data quantization method provided by the present invention, when the communication system is a single-carrier system, the minimum scheduling unit is a set of multiple pilot symbols and multiple data symbols; the power sum of the pilot set is calculated in the time domain;

[0089] In the case where the communication system is a multi-carrier system, the minimum scheduling unit is a set of frequency domain resource elements and user data resource elements; the power sum of the pilot set is calculated in the frequency domain.

[0090] Specifically, different calculation methods for the sum of the power of the pilot sets may be designed according to the characteristics of the communication system to adapt to different channel estimation requirements.

[0091] In a single-carrier system, the minimum scheduling unit consists of a collection of multiple pilot symbols and multiple data symbols. Pilot symbols are typically designed in the time domain. Within the minimum scheduling unit's time-domain symbol, pilot symbols are distributed at the beginning, middle, or end of the symbol, or in a combination of these. There is typically only one pilot port, so pilot symbol power statistics are performed in the time domain.

[0092] During the calculation process, the I / Q components of the time-domain pilot symbols are extracted, the instantaneous power of each symbol is calculated, and the power of all pilot symbols is accumulated to obtain the total power. This time-domain statistical method is consistent with the continuity of single-carrier signals and facilitates real-time tracking of channel status.

[0093] In multi-carrier systems, such as Long Term Evolution (LTE), the minimum scheduling unit consists of a set of frequency-domain resource elements (REs) and user data REs. Pilots are distributed in the frequency domain and the number of ports is configurable (1, 2, or 4). Based on the sparseness of pilot symbols, port-based pilot power statistics are performed to estimate the quantization bit width of each port. Pilot power statistics are performed in the frequency domain.

[0094] During the calculation process, the frequency domain I / Q values of each pilot RE are extracted, their power is calculated, and then accumulated. The frequency domain statistical method matches the discrete subcarrier structure of multicarrier signals and can accurately reflect the frequency domain channel response.

[0095] According to a data quantization method provided by the present invention, based on a second quantization bit width and a modulation mode, soft information obtained by demodulation is dynamically truncated to obtain truncated soft information, including:

[0096] Determining a starting position for dynamically truncating the demodulated soft information based on the second quantization bit width;

[0097] Determining, based on the modulation mode, a third quantization bit width for dynamically truncating the soft information obtained by demodulation;

[0098] Based on the starting position and the third quantization bit width, dynamic bit width truncation is performed on the demodulated soft information to obtain truncated soft information.

[0099] Specifically, in the process of dynamically truncating the soft information obtained by demodulation according to the second quantization bit width and the modulation mode, first, the starting position of the dynamic bit width truncation can be determined according to the second quantization bit width.

[0100] As mentioned above, the second quantization bit width is a quantization parameter calculated in real time using the pilot power (e.g., est_width = 12). Its value can indicate the high-order segment of the main energy distribution in the soft information. For example, if the second quantization bit width is 12, the truncation start position of the 16-bit soft information is the 12th bit (e.g., MSB

[12] ), ensuring that the high-order segment covers the signal peak amplitude and avoids truncation distortion.

[0101] Then, the third quantization bit width may be determined according to the modulation mode.

[0102] The modulation method determines the density and noise immunity of the constellation points, and can be used to match different quantization accuracies. High-order modulation (such as 256QAM) requires more quantization bits to distinguish dense constellation points, while low-order modulation (such as QPSK) only requires a small number of bits to retain key symbol information.

[0103] For example, if the modulation mode is 256QAM and the second quantization bit width is 12, the third quantization bit width is 8 bits; if it is QPSK, the third quantization bit width is 2 bits.

[0104] This mapping relationship can be implemented through a preset rule table (for example, 256QAM→8bit, QPSK→2bit), ensuring that the quantization accuracy is consistent with the modulation complexity.

[0105] Finally, based on the starting position and the third quantization bit width, the demodulated soft information is dynamically truncated to obtain truncated soft information. The truncation range is from the starting position down to the length of the third quantization bit width.

[0106] For example, if the starting position is 12 and the third quantization bit width is 8 bits, the 12th bit to the 5th bit (a total of 8 bits, recorded as [12:5]) are intercepted; if the starting position is 12 and the third quantization bit width is 2 bits, the 12th bit to the 11th bit ([12:11]) are intercepted.

[0107] According to a data quantization method provided by the present invention, saturation quantization and truncation processing is performed on the truncated soft information, including:

[0108] Merging the soft information after multiple truncation, and expanding the bit width of the merged soft information;

[0109] Based on the third quantization bit width, truncation processing is performed on the soft information after the bit width expansion.

[0110] Specifically, considering that multi-channel soft information may be merged during rate matching, a saturation quantization and truncation process needs to be added in the embodiment of the present invention.

[0111] First, multiple channels of truncated soft information are combined and their bit width is expanded. This soft information may come from HARQ retransmission combining or MIMO multi-stream detection (e.g., combining four channels of signals). Because combining operations (e.g., summing) expand the range of values, bit width expansion is necessary to prevent overflow.

[0112] The expanded soft information is then truncated based on the third quantization bit width. This third quantization bit width is typically determined by the previous modulation scheme (e.g., 8 bits for 256QAM and 2 bits for QPSK). It truncates the expanded high-bit-width data back to the target bit width, while also preventing overflow through saturation.

[0113] For example, 16QAM has 4 bits of input soft information, with a maximum of 4 channels of soft information, namely soft0, soft1, soft2, and soft3. The combined soft information is summed up to get (soft0+soft1+soft2+soft3), which is expanded to 6 bits. The 6 bits are then saturated and truncated to 4 bits for output to the decoder input.

[0114] The data quantification method provided by the present invention is further described below through examples in specific application scenarios.

[0115] Figure 3 This is a schematic diagram of the overall process of the quantitative embodiment of the communication system provided by the present invention. Figure 3 As shown, this embodiment includes the following four parts:

[0116] 1. Maximum sign bit quantization of DDC down-conversion based on peak-to-average ratio

[0117] Figure 4 FIG. 1 is a schematic diagram of an example of maximum sign bit quantization of DDC down-conversion based on peak-to-average ratio provided by the present invention, as shown in FIG. Figure 4 As shown, after the AD analog-to-digital conversion, if it is zero intermediate frequency, the multi-stage DDC sampling rate is directly changed to the required baseband sampling rate. If it is real sampling, it first undergoes orthogonal mixing, and then the multi-stage DDC sampling rate is changed to the required baseband sampling rate. Anti-aliasing filtering is required during the multi-stage DDC sampling rate change process, and the last stage requires shaping filtering. The input and output of the filter need to be quantized, and the peak-to-average ratio of the input signal after sampling determines the number of sign bits of the first-stage IQ.

[0118] For example, if the estimated peak-to-average ratio of the input signal is 12dB@0.01% (the probability of the peak power to average power ratio dB=12DB occurring is 0.01%), and the IQ bit width of the AD output is 16 bits, then the peak-to-average ratio of the signal is 12dB, and the 1-bit quantization dB value is 6dB. Then the quantization symbol retained by I or Q is 2bit@16bit, that is, the MSB[15:14] of 16bit-[15:0] is the reserved sign bit, which is the input of the first-stage mixing or anti-aliasing filter. Then the output I or Q bit width of the first-stage anti-aliasing filter (internal multiplication and accumulation operation) is usually 33bit~40bit (depending on the filter coefficient). The output of the first-stage filter is the input of the second-stage filter. The input I or Q is often required to be no more than 16bit, so 33bit~40bit to 16bit needs to be truncated and quantized. The quantization rule is to keep the quantization symbol retained by the input I or Q of the first-stage filter at 2bit, that is, the input I of the second-stage anti-aliasing filter Or the quantization symbol retained by Q is also 2bit@16bit, and the input and output of the subsequent multi-stage filter follow the same rules.

[0119] For example, if the peak-to-average ratio of the input signal after single-carrier sampling is 6dB@0.01%, the quantization symbol retained by I or Q is 1bit@16bit, that is, the MSB

[15] of 16bit-[15:0] is the reserved symbol bit, that is, the input of the first-stage mixing or anti-aliasing filter. Similarly, the output of the first-stage filter is the input of the second-stage filter, so the output 33bit~40bit to 16bit needs to be truncated and quantized. The quantization rule is to keep the quantization symbol retained by the input I or Q of the first-stage filter at 1bit, that is, the quantization symbol retained by the input I or Q of the second-stage anti-aliasing filter is also 1bit@16bit. The input and output of the subsequent multi-stage filters follow the same rule.

[0120] 2. Channel estimation and equalization calculation quantization based on pilot power

[0121] Figure 5 Schematic diagram of the pilot bit width quantization estimation provided by the present invention, such as Figure 5 As shown, channel estimation and equalization calculation based on pilot power are quantized. The pilot symbols in the received data are divided by port (or pilot samples). The power of one or several groups of pilots belonging to the same port within the current scheduling granularity is counted, and the quantization bit width is estimated in real time. The intermediate calculation processes of channel estimation and equalization calculation all refer to this quantization bit width for real-time dynamic quantization truncation processing.

[0122] In a single-carrier system, the pilot is usually designed in the time domain. On the time domain symbol of the minimum scheduling unit, it is distributed at the front, middle, or tail of the symbol, or in a combination of distributions. There is usually only one pilot port, so the power statistics of the pilot symbol are performed in the time domain.

[0123] In multi-carrier systems, such as LTE, pilots are distributed in the frequency domain and the number of ports is configurable (1, 2, or 4). Based on the sparseness of pilot symbols, port-based pilot power statistics are performed to estimate the quantization bit width of each port. Pilot power statistics are performed in the frequency domain.

[0124] First, let's explain the definition of the minimum scheduling unit, which is a data set of multiple time domain symbols. This data set is a data input set for a single decoding. For example, the single-carrier time domain minimum scheduling unit includes pilots (multiple time domain pilot symbols (samples)) and data (multiple data symbols (samples)). The pilot set is used for channel estimation, and the data set is used for equalized data input. The data set of equalized output is then demodulated to obtain a soft information set, which is rate-matched and input for decoding. Finally, the bit stream set is decoded, which is the wireless communication information carried by the minimum scheduling unit.

[0125] The multi-carrier minimum scheduling unit is similar. The difference is that the multi-carrier system pilot set extraction is in the frequency domain, and the pilots are distributed on specific symbols in the frequency domain (the data or pilot within the frequency domain symbol is also called RE (resource element, which is different from the definition of time domain symbol (sample point))). The multi-carrier port-based pilot RE can be called a pilot set after collection, and the multi-carrier user-based data RE can be called a user data set after collection. Similarly, the pilot set is used for channel estimation, and the data set is used as equalization data input. The equalization output data set is then demodulated to obtain a soft information set, and the soft information set is rate-matched and input decoded. Finally, the decoding obtains a bit stream set, which is the wireless communication information carried by the minimum scheduling unit.

[0126] Pilot power estimation and quantization bit width calculation: multiple IQ (I_0+Q_0 1j,I_1+Q_1 1j,I_2+Q_2 1j,…,I_n-1+Q_n-1 1j) Calculate the sum of the sample power or resource RE power, that is, accu_power = sum(I_0^2 + Q_0^2 + I_1^2 + Q_1^2 + I_2^2 + Q_2^2 + … + I_n-1^2 + Q_n-1^2), average power = avg_power = accu_power / N, amplitude abs_mag = abs(avg_power), calculate the quantization bit width = est_width = log2(abs_mag), quantization bit width range is 1 to 16.

[0127] All intermediate quantization bits in channel estimation and equalization calculations use est_width as a reference and are dynamically scaled to around this bit width, thereby ensuring quantization accuracy throughout symbol processing while optimizing resource efficiency.

[0128] 3. Quantization based on average energy symbol bit and modulation mode association

[0129] Figure 6 This is a schematic diagram of the association quantization of the average energy sign bit and the modulation mode provided by the present invention, such as Figure 6 As shown, the previous stage has est_width parameter information, and the average energy symbol bit can be determined based on the est_width parameter. Here, the equalized output data is first demodulated and converted into 16-bit soft information. For example, the current est_width = 12, when the modulation mode is:

[0130] 256QAM, dynamic quantization is 8 bits, from [15:0], truncate [12:5] 8 bits and output the truncation soft information;

[0131] 64QAM, dynamic quantization is 6 bits, from [15:0], truncate [12:7] 6 bits and output the truncation soft information;

[0132] 16QAM, dynamic quantization is 4 bits, from [15:0], truncate [12:9] 4 bits and output the truncated soft information;

[0133] 8PSK, dynamic quantization is 3 bits, from [15:0], truncate [12:10] 3 bits and output the truncated soft information;

[0134] QPSK and BPSK are dynamically quantized to 2 bits, and the soft information after truncation is output from [15:0] and [12:11] 2 bits.

[0135] 4. Saturation quantization of decoding front end

[0136] Figure 7 Schematic diagram of the saturation quantization of the decoding front end provided by the present invention, such as Figure 7 As shown in the figure, considering that there may be multi-channel soft information merging in the rate matching process, that is, soft information of different precisions (8bit / 6bit / 4bit / 2bit) enters the input buffer (BUF) and is merged through the circular BUF, saturation quantization and truncation processing must be added here. For example, for 16QAM 4-bit input soft information, a maximum of 4 channels are merged, sum (soft0+soft1+soft2+soft3), expanded to 6 bits, and then the 6-bit saturation truncation is reduced to 4 bits and output to the decoder input.

[0137] The data quantization device provided by the present invention is described below. The data quantization device described below and the data quantization method described above can be referenced to each other.

[0138] Figure 8 : is a schematic diagram of the structure of the data quantization device provided by the present invention, such as Figure 8 As shown, the device is applied to a communication system and includes the following modules:

[0139] A first quantization module 800 is configured to perform digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0140] A second quantization module 810 is configured to perform channel estimation and equalization processing on the baseband signal based on a second quantization bit width; the second quantization bit width is calculated in real time based on the power of pilot symbols in the baseband signal;

[0141] The third quantization module 820 is configured to demodulate the baseband signal after channel estimation and equalization processing, and dynamically truncate the demodulated soft information based on the second quantization bit width and the modulation mode to obtain truncated soft information;

[0142] The fourth quantization module 830 is configured to perform saturation quantization and truncation processing on the truncated soft information and output the truncated soft information to the decoder.

[0143] According to a data quantization device provided by the present invention, a method for determining the first quantization bit width includes:

[0144] Determining a first quantization bit width according to a peak-to-average ratio of the input signal and a corresponding relationship that 1 bit corresponds to 6 dB;

[0145] The first quantization bit width is used as the number of sign bits of the input of the first stage filter of digital down-conversion; in the processing process of the multi-stage filter of digital down-conversion, the number of sign bits of the input and output of each stage is consistent.

[0146] According to a data quantization device provided by the present invention, a method for calculating the second quantization bit width includes:

[0147] Calculate the power sum of the pilot set within a preset minimum scheduling unit;

[0148] A second quantization bit width is calculated based on the power sum of the pilot set.

[0149] According to a data quantization device provided by the present invention, when the communication system is a single-carrier system, the minimum scheduling unit is a set of multiple pilot symbols and multiple data symbols; the power sum of the pilot set is calculated in the time domain;

[0150] In the case where the communication system is a multi-carrier system, the minimum scheduling unit is a set of frequency domain resource elements and user data resource elements; the power sum of the pilot set is calculated in the frequency domain.

[0151] According to a data quantization device provided by the present invention, based on a second quantization bit width and a modulation mode, dynamic bit width truncation is performed on soft information obtained by demodulation to obtain truncated soft information, including:

[0152] Determining a starting position for dynamically truncating the demodulated soft information based on the second quantization bit width;

[0153] Determining, based on the modulation mode, a third quantization bit width for dynamically truncating the soft information obtained by demodulation;

[0154] Based on the starting position and the third quantization bit width, dynamic bit width truncation is performed on the demodulated soft information to obtain truncated soft information.

[0155] According to a data quantization device provided by the present invention, saturation quantization and truncation processing is performed on truncated soft information, including:

[0156] Merging the soft information after multiple truncation, and expanding the bit width of the merged soft information;

[0157] Based on the third quantization bit width, truncation processing is performed on the soft information after the bit width expansion.

[0158] Figure 9 Schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 9 As shown, the electronic device may include: a processor 910, a communication interface 920, a memory 930, and a communication bus 940, wherein the processor 910, the communication interface 920, and the memory 930 communicate with each other via the communication bus 940. The processor 910 may call logic instructions in the memory 930 to execute a data quantization method, which includes:

[0159] Based on a first quantization bit width, digital down-converting the input signal to obtain a baseband signal; the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0160] Based on the second quantization bit width, channel estimation and equalization processing are performed on the baseband signal; the second quantization bit width is obtained based on real-time calculation of power of pilot symbols in the baseband signal;

[0161] Demodulating the baseband signal after channel estimation and equalization processing, and dynamically truncating the soft information obtained by demodulation based on the second quantization bit width and the modulation mode to obtain truncated soft information;

[0162] The truncated soft information is subjected to saturation quantization and truncation processing and output to the decoder.

[0163] Furthermore, the logic instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0164] In another aspect, the present invention further provides a computer program product, comprising a computer program. The computer program may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the data quantization method provided by each of the above methods, the method comprising:

[0165] Based on a first quantization bit width, digital down-converting the input signal to obtain a baseband signal; the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0166] Based on the second quantization bit width, channel estimation and equalization processing are performed on the baseband signal; the second quantization bit width is obtained based on real-time calculation of power of pilot symbols in the baseband signal;

[0167] Demodulating the baseband signal after channel estimation and equalization processing, and dynamically truncating the soft information obtained by demodulation based on the second quantization bit width and the modulation mode to obtain truncated soft information;

[0168] The truncated soft information is subjected to saturation quantization and truncation processing and output to the decoder.

[0169] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program is implemented to perform the data quantization method provided by the above methods, the method comprising:

[0170] Based on a first quantization bit width, digital down-converting the input signal to obtain a baseband signal; the first quantization bit width is determined based on a peak-to-average ratio of the input signal;

[0171] Based on the second quantization bit width, channel estimation and equalization processing are performed on the baseband signal; the second quantization bit width is obtained based on real-time calculation of power of pilot symbols in the baseband signal;

[0172] Demodulating the baseband signal after channel estimation and equalization processing, and dynamically truncating the soft information obtained by demodulation based on the second quantization bit width and the modulation mode to obtain truncated soft information;

[0173] The truncated soft information is subjected to saturation quantization and truncation processing and output to the decoder.

[0174] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0175] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A data quantization method, characterized in that: Applications in communication systems include: Performing digital down-conversion processing on the input signal based on a first quantization bit width to obtain a baseband signal; wherein the first quantization bit width is determined based on a peak-to-average ratio of the input signal; performing channel estimation and equalization processing on the baseband signal based on a second quantization bit width; wherein the second quantization bit width is calculated in real time based on power of pilot symbols in the baseband signal; Demodulating the baseband signal after the channel estimation and equalization processing, and dynamically truncating the demodulated soft information based on the second quantization bit width and the modulation mode to obtain truncated soft information; The truncated soft information is subjected to saturation quantization and truncation processing, and is output to a decoder.

2. The data quantization method according to claim 1, characterized in that: The method for determining the first quantization bit width includes: Determining a first quantization bit width according to a peak-to-average ratio of the input signal and a corresponding relationship that 1 bit corresponds to 6 dB; The first quantization bit width is used as the number of sign bits of the input of the first stage filter of digital down conversion; in the processing process of the multi-stage filter of digital down conversion, the number of sign bits of the input and output of each stage is consistent.

3. The data quantization method according to claim 1, characterized in that: The calculation method of the second quantization bit width includes: Calculate the power sum of the pilot set within a preset minimum scheduling unit; A second quantization bit width is calculated based on the power sum of the pilot set.

4. The data quantization method according to claim 3, characterized in that: In the case where the communication system is a single-carrier system, the minimum scheduling unit is a set of multiple pilot symbols and multiple data symbols; the power sum of the pilot set is calculated in the time domain; In the case where the communication system is a multi-carrier system, the minimum scheduling unit is a set of frequency domain resource elements and user data resource elements; and the power sum of the pilot set is calculated in the frequency domain.

5. The data quantization method according to claim 1, 3 or 4, characterized in that: Dynamically truncating the demodulated soft information based on the second quantization bit width and the modulation mode to obtain truncated soft information includes: Determining a starting position for dynamically truncating the demodulated soft information based on the second quantization bit width; Determining, based on the modulation mode, a third quantization bit width for dynamically truncating the soft information obtained by demodulation; Based on the starting position and the third quantization bit width, dynamic bit width truncation is performed on the demodulated soft information to obtain truncated soft information.

6. The data quantization method according to claim 5, characterized in that: Performing saturation quantization truncation processing on the truncated soft information includes: Merging the soft information after multiple truncation, and expanding the bit width of the merged soft information; Based on the third quantization bit width, truncation processing is performed on the soft information after the bit width expansion.

7. A data quantization device, characterized in that: Applications in communication systems include: a first quantization module, configured to perform digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; wherein the first quantization bit width is determined based on a peak-to-average ratio of the input signal; A second quantization module is configured to perform channel estimation and equalization processing on the baseband signal based on a second quantization bit width, wherein the second quantization bit width is calculated in real time based on the power of pilot symbols in the baseband signal; a third quantization module, configured to demodulate the baseband signal after the channel estimation and equalization processing, and dynamically truncate the demodulated soft information based on the second quantization bit width and modulation mode to obtain truncated soft information; The fourth quantization module is configured to perform saturation quantization and truncation processing on the truncated soft information and output the truncated soft information to a decoder.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the data quantization method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the data quantization method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the data quantization method according to any one of claims 1 to 6 is implemented.

Images