Joint de-mapping and decoding method and apparatus, decoder, integrated circuit, device, and equipment

Abstract

A joint de-mapping and decoding method and apparatus, a decoder, an integrated circuit, a device, and equipment, applied to the technical field of digital signal processing. A received symbol comprising a plurality of components is first acquired, wherein each component of the received symbol is jointly determined by a plurality of encoded bits involved in symbol mapping; when state transition is performed during a decoding process, a likelihood value of each symbol value is computed on the basis of the value of the received symbol, and branch metrics of each state transition branch is obtained on the basis of the likelihood values.

Description

Joint de-mapping and decoding method, apparatus, decoder, integrated circuit, device and equipment

[0001] The present application claims priority from the Chinese patent application No. 202410622969.6 filed on May 17, 2024 and entitled "Method, apparatus, integrated circuit, electromagnetic wave device and user terminal equipment of joint de-mapping and decoding", the contents of which should be understood as incorporated by reference into the present application. TECHNICAL FIELD

[0002] The present disclosure relates to, but is not limited to, the technical field of signal processing, and in particular to a joint de-mapping and decoding method, apparatus, decoder, integrated circuit, device and equipment. BACKGROUND

[0003] UWB (Ultra Wide Band) is a wireless communication technology, and its physical layer (PHY) defines the way of signal transmission and reception. UWB technology transmits data by using an extremely wide frequency spectrum (usually between 3.1 GHz and 10.6 GHz) and short pulses (time domain width in nanoseconds), which can provide higher data transmission rate and more accurate positioning capability, but its decoding performance needs to be improved. SUMMARY

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] An embodiment of the present disclosure provides a joint de-mapping and decoding method, comprising:

[0006] Obtaining a received symbol comprising a plurality of components, each component of the received symbol being jointly determined by a plurality of coded bits participating in symbol mapping;

[0007] When the decoding process is in state transition, calculating a likelihood value of each value of the symbol according to a value of the received symbol, and obtaining a branch metric of each state transition branch based on the likelihood value.

[0008] An embodiment of the present disclosure also provides a joint de-mapping and decoding method, comprising: obtaining a modulation constellation of non-gray format; and decoding based on the correlation between mapped symbols.

[0009] An embodiment of the present disclosure also provides a joint de-mapping and decoding method, comprising: obtaining a modulation constellation of non-gray format; and decoding in a maximum log approximation manner.

[0010] An embodiment of the present disclosure further provides a joint demapping and decoding device, comprising a memory and a processor, the memory storing a computer program, wherein the processor can implement the joint demapping and decoding method according to any embodiment of the present disclosure when executing the computer program.

[0011] An embodiment of the present disclosure further provides a decoder, comprising a branch metric generation module and a path processing module, wherein:

[0012] The branch metric generation module is configured to obtain a received symbol comprising a plurality of components from an input end, obtain branch metrics of each state transition branch according to the joint demapping and decoding method according to any embodiment of the present disclosure, and output to the path processing module;

[0013] The path processing module is configured to update and record path metrics of each state based on the branch metrics, obtain a path with the largest path metric by backtracking when reaching the end of the path, and obtain a coded bit sequence after decoding based on state transition branches of the path with the largest path metric.

[0014] An embodiment of the present disclosure further provides an integrated circuit, comprising a radio frequency module, an analog signal processing module and a digital signal processing module connected in sequence; the radio frequency module is configured to generate and emit electromagnetic wave signals, and receive electromagnetic wave signals; the analog signal processing module is configured to perform frequency reduction processing on the received electromagnetic wave signals to obtain intermediate frequency signals; the digital signal processing module is configured to perform analog-to-digital conversion on the intermediate frequency signals to obtain digital signals, and process the digital signals; wherein the digital signal processing module comprises the decoder according to any embodiment of the present disclosure.

[0015] An embodiment of the present disclosure further provides an electromagnetic wave device, comprising: a carrier; the integrated circuit according to any embodiment of the present disclosure disposed on the carrier; and an antenna disposed on the carrier and integrated with the integrated circuit as an integrated device or disposed separately; wherein the integrated circuit is connected with the antenna, and used for emitting the electromagnetic wave signals and / or receiving the electromagnetic wave signals.

[0016] An embodiment of the present disclosure further provides a terminal device, comprising: a device body; and the electromagnetic wave device according to any embodiment of the present disclosure disposed on the device body; wherein the electromagnetic wave device is used for target detection and / or communication, to provide reference information for the operation of the device body.

[0017] An embodiment of the present disclosure further provides a non-transitory computer readable storage medium, having a computer program stored thereon, the computer program being executable by a processor to implement the joint demapping and decoding method according to any embodiment of the present disclosure.

[0018] Other aspects can become apparent from a review of the drawings and detailed description.

[0019] SUMMARY

[0020] The accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the present disclosure and together with the description serve to explain the principles of the present disclosure. The drawings are provided for merely the purposes of illustration and do not reflect an actual scale or proportions to the present disclosure. The embodiments of the present disclosure are illustrated by way of example and not limitation in the figures of the accompanying drawings in which:

[0021] FIG. 1A is a schematic diagram of encoding and symbol mapping of a UWB physical layer in an embodiment, and FIG. IB is a schematic diagram of symbol demapping and decoding in the embodiment;

[0022] FIG. 2 is a schematic diagram of symbol mapping and constellation in different modes of a UWB physical layer in an embodiment;

[0023] FIG. 3 is a schematic diagram of a structure of an apparatus for calculating a log-likelihood ratio of a symbol and decoding in an embodiment;

[0024] FIG. 4 is a flowchart of a joint demapping and decoding method in an embodiment of the present disclosure;

[0025] FIG. 5 is a schematic diagram of a structure of a decoder in an embodiment of the present disclosure;

[0026] FIG. 6 is a comparison diagram between error correction performance of a joint demapping and decoding method in an embodiment of the present disclosure and error correction performance of a demapping and decoding method in other methods;

[0027] FIG. 7A is a module diagram of a decoder in an embodiment of the present disclosure;

[0028] FIG. 7B is a schematic diagram of an integrated circuit in an embodiment of the present disclosure;

[0029] FIG. 8 is a schematic diagram of a terminal device in an embodiment of the present disclosure;

[0030] FIG. 9 is a schematic diagram of a joint demapping and decoding apparatus in an embodiment of the present disclosure;

[0031] FIG. 10a is a non-gray code diagram of BPM-BPSK joint modulation;

[0032] FIG. 10b is a gray code diagram of BPSK / QPSK modulation;

[0033] FIG. 11 is a schematic diagram of state transition in a Viterbi decoding process;

[0034] FIG. 12 is a non-gray code diagram of HRP-ERDEV mode;

[0035] FIG. 13 is a performance comparison diagram of schemes;

[0036] FIG. 14 is a flow chart of a joint de-mapping and decoding method according to another embodiment of the present disclosure;

[0037] FIG. 15 is a flow chart of a joint de-mapping and decoding method according to yet another embodiment of the present disclosure.

[0038] DETAILED DESCRIPTION

[0039] A number of embodiments of the present disclosure are described, but the description is exemplary rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described in the present disclosure.

[0040] In the description of the present disclosure, the word "exemplary" or "for example" is used to mean an example, an illustration, or another example. Any embodiment described as "exemplary" or "for example" in the present disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. In the present disclosure, "and / or" is used to associate associated objects, which means that there are three relationships, for example, A and / or B, which means that there are three cases, A alone, A and B together, and B alone. "Multiple" means two or more than two. In addition, in order to clearly describe the technical solutions of the embodiments of the present disclosure, the same items or similar items with basically the same functions and effects are distinguished by "first", "second", etc. The person skilled in the art can understand that "first", "second", etc. do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different.

[0041] In describing representative example embodiments, the specification can have presented the method and / or process as a particular sequence of steps. However, to the extent that the method or process depends on more than one step, the method or process should not be limited to the particular sequence of steps described. Other sequences of steps can be possible, and are within the spirit and scope of the embodiments of the present disclosure. Therefore, the particular order in which the steps are presented in the specification is not an absolute limitation on the embodiments of the present disclosure. Moreover, the specification has described several embodiments of the method and / or process. However, the person skilled in the art can easily understand that the claims are not limited to the steps written in the order, and the order can be changed, and still remain within the spirit and scope of the embodiments of the present disclosure.

[0042] The embodiment of the present disclosure provides a joint demapping and decoding method, a decoder, an integrated circuit, a sensor and a device, which can be applied to a sensor system but is not limited thereto. In the case that each component of a received symbol is jointly determined by a plurality of coded bits participating in symbol mapping, when a state transition is performed in a decoding process, a likelihood value of each value of the symbol is calculated according to a value of the received symbol, and a branch metric of each state transition branch is obtained based on the likelihood value, so that performance loss caused by calculating a log-likelihood ratio of a single component in the received symbol and then merging to obtain the branch metric is avoided, and thus the decoding performance of a receiver can be improved without increasing the calculation complexity.

[0043] First, some English abbreviations and English full names of terms used in the present text are given as follows:

[0044] Physical Layer Service Data Unit: PSDU

[0045] Physical Layer Header: PHR

[0046] Single Error Correction, Double Error Detection: SECDED

[0047] Reed-Solomon: RS

[0048] High Rate Pulse: HRP

[0049] Enhanced Relative Error Detection and Verification: ERDEV

[0050] Base Pulse Repetition Frequency: BPRF

[0051] Binary(burst) Position Modulation: BPM

[0052] Binary Phase Shift Keying: BPSK

[0053] Quadrature Phase Shift Keying: QPSK

[0054] Constraint Length: CL, Constraint Length

[0055] Log Likelihood Ratio: LLR, log likelihood ratio

[0056] According to the protocol specified in IEEE Std 802.15.4 and IEEE Std 802.15.4z, the UWB physical layer adopts convolutional coding with a code rate of 0.5 for both PHR and PSDU to be transmitted at the transmitting end, and then performs specific symbol mapping, so as to be modulated and beamformed subsequently. In the baseband processing at the receiving end, the data obtained after demodulation needs to be subjected to corresponding demapping and convolutional code decoding. As shown in FIG. 1A, at the transmitting end, the PHR is input into a SECDED encoder 11, and the PSDU is input into an RS encoder 13 for encoding, and the outputs of the SECDED encoder 11 and the RS encoder 13 are both input into a convolutional encoder 15 for encoding with a code rate of 0.5, and the output of the convolutional encoder 15 is further subjected to processing by a symbol mapping module 17 and then sent to a radio frequency module 19 for modulation, and then transmitted through an antenna. As shown in FIG. 1B, the signal received by the antenna at the receiving end is subjected to synchronization, channel equalization and demodulation at the radio frequency module 21, and the data obtained after demodulation is subjected to symbol demapping at a symbol demapper 23, and then decoded by a Viterbi decoder 25, and one way is sent to an RS decoder 29 to obtain decoded PSDU, and the other way is sent to a SECDED decoder 27 to obtain decoded PHR.

[0057] The symbol mapping rules of the UWB physical layer under different configurations are shown in FIG. 2. When the UWB physical layer works in HRP mode or BPRF mode as an HRP-ERDEV device (indicated as HRP-ERDEV BPRF mode in the figure), the modulation mode adopts a combination of BPM and BPSK modulation (BPM-BPSK). At this time, each symbol is equally divided into two segments, and the pulse with information is only transmitted in one segment. Each modulated symbol contains two bits of information, wherein the first bit indicates the position of the pulse, i.e., in the first half or the second half of the symbol, and the second information bit determines the phase of the pulse, i.e., +1 or -1; each bit in the symbol can also be referred to as a component of the symbol. When the UWB physical layer works in HPRF mode as an HRP-ERDEV device, the modulation mode is similar to QPSK, and the symbol mapping rules are different according to the constraint length of the convolutional code (CL=3 or CL=7).

[0058] As shown in Fig. 2, when the UWB physical layer works in HRP mode or works in BPRF mode as a HRP-ERDEV device (with BPM-BPSK modulation), the mapping relationship between two coded bits and a symbol is: 00 maps to symbol (1, 0), 01 maps to symbol (-1, 0), 10 maps to symbol (0, 1), and 11 maps to symbol (0, -1). When the UWB physical layer works in HPRF mode as a HRP-ERDEV device and the constraint length of the convolutional code is equal to 3, the mapping relationship between two coded bits and a symbol is: 00 maps to symbol (1, 1), 01 maps to symbol (-1, -1), 10 maps to symbol (-1, 1), and 11 maps to symbol (1, -1). In these two cases, the value of each component of the symbol needs to be determined jointly by the two coded bits participating in the symbol mapping. Correspondingly, when the UWB physical layer works in HPRF mode as a HRP-ERDEV device and the constraint length of the convolutional code is equal to 7, the mapping relationship between two coded bits and a symbol is: 00 maps to symbol (1, 1), 01 maps to symbol (1, -1), 10 maps to symbol (-1, 1), and 11 maps to symbol (-1, -1). One component (real part) of the symbol is determined by the first coded bit, and the other component (imaginary part) is determined by the second coded bit, and the two are completely independent.

[0059] In the baseband data processing at the receiving end, referring to FIG. IB and FIG. 3, the log-likelihood ratio (LLR) of each coded bit is usually calculated by the LLR generation module 31 of the symbol demapping module 23 based on the received signal after channel equalization, descrambling, etc., and the result is output to the Viterbi decoder for decoding. As shown in FIG. 3, in the Viterbi decoder, the branch metric is first calculated by the Branch Metric Generator 33 based on the LLR to evaluate the "goodness" of different paths, and then the decoding based on soft information is performed based on the ACS (Add-Compare-Select) array 35, the State metric memory 37, the Path record memory 39, the Path traceback module 41 and the Decoded HB memory 43, etc. The exemplary process of the Viterbi decoder is as follows: receiving signal, i.e. receiving the signals transmitted through the channel, which can be affected by noise and interference; path metric calculation, i.e. calculating the path metric of each possible path to evaluate the "goodness" of different paths during the decoding process. This step involves adding, summing and selecting the optimal path for the branch metric of each state; traceback operation, i.e. after completing the processing of all time steps, the information stored in the Path record memory is used for traceback to determine the optimal decoding path, which traces the derived state sequence; outputting coded bits, i.e. the coded bits sent by the sending end are deduced according to the state sequence obtained by the traceback and output.

[0060] In the first embodiment, taking the processing in the HRP mode or the BPRF mode of the HRP-ERDEV device (both modes use BPM-BPSK modulation) as an example, it is assumed that the input signal obtained by the demapping module at the receiving end only contains the influence of Gaussian white noise. Let the two components of a received symbol be y0, y1, which are represented as: y0=x0+n0, y1=x1+n1, where x0, x1 are the two components of the transmitted symbol, and n0, n1 are two independent and identically distributed noise samples. Let the coded bits corresponding to the transmitted symbol be b0, b1, and their log-likelihood ratios be defined as: L0=logPr(b0=0|y0y1)-logPr(b0=1|y0y1) L1=logPr(b1=0|y0y1)-logPr(b1=1|y0y1)

[0061] where Pr(b0=0|y0y1) represents the probability of b0 being 0 given y0 and y1; Pr(b0=1|y0y1) represents the probability of b0 being 1 given y0 and y1; Pr(b1=0|y0y1) represents the probability of b1 being 0 given y0 and y1; and Pr(b1=1|y0y1) represents the probability of b1 being 1 given y0 and y1.

[0062] According to the Bayes rule and the assumption that the probabilities of 0 and 1 in the coded bits are equal, the posterior probabilities in the log-likelihood ratio can be converted into conditional probabilities: L0=logPr(y0y1|b0=0)-logPr(y0y1|b0=1) L1=logPr(y0y1|b1=0)-logPr(y0y1|b1=1)

[0063] Since y0, y1 are determined by b0, b1 together, the conditional probabilities can be written as:

[0064] The above equation and the Gaussian probability density function are brought into the calculation of the log-likelihood ratio to obtain:

[0065] According to the approximate relationship: log(exp(x)+exp(y))≈max(x,y), the expression of the log-likelihood ratio can be further simplified as (the approximation error is very small and has almost no numerical impact):

[0066] where σ represents the standard deviation of the Gaussian distribution.

[0067] The LLR generation module 31 in FIG. 3 (corresponding to the symbol demapping module 23 in FIG. 1B) performs the above calculation. However, this formula cannot be inversely deduced to the received signals y0 and y1. This also shows that the method of performing demapping and decoding in steps has performance loss. In the Viterbi decoder in FIG. 3, each two LLR inputs correspond to a state transition, and 4 branch metric values need to be calculated, respectively corresponding to the likelihood values of the state transitions with the outputs of 00 / 01 / 10 / 11: γ 00 =L0+L1, γ 01 =L0-L1, γ 10 =-L0+L1, γ 11 =-L0-L1.

[0068] According to these branch metric values, the Viterbi decoder constantly updates the path metric, and finally finds the decoding path with the maximum path metric to obtain the optimal decoding result.

[0069] The above embodiment adopts a manner of calculating log-likelihood ratio of each encoding bit first and then merging the log-likelihood ratio in branch metric calculation of the decoder. The default assumption is that two bits corresponding to each state transition are independent of each other. However, from the perspective of demapping, the embodiment does not consider the characteristics of symbol mapping, that is, two encoding bits corresponding to the same symbol are related, and the performance loss will be caused by the step-by-step demapping and decoding adopted by the embodiment. In the case of HRP-ERDEV equipment in HPRF mode and convolutional code constraint length equal to 3, two encoding bits corresponding to the same symbol are also related, and the performance loss problem also exists.

[0070] To this end, an embodiment of the present disclosure provides a joint demapping and decoding method, as shown in FIG. 4, which comprises the following steps:

[0071] In step 110, a received symbol including multiple components is obtained, each component of the received symbol being jointly determined by multiple encoding bits participating in symbol mapping.

[0072] In step 120, when a state transition is performed in a decoding process, a likelihood value of each value of a symbol is calculated according to a value of the received symbol, and a branch metric of each state transition branch is obtained based on the likelihood value.

[0073] In an example of the embodiment, each state transition of the decoding process generates a symbol, and the step of calculating, when a state transition is performed in the decoding process, a likelihood value of each value of a symbol according to a value of the received symbol comprises the step of calculating, when each state transition of the decoding process is performed, a likelihood value of each value of a symbol according to a value of the received symbol.

[0074] The method can be used in the case where the result of symbol mapping needs to be determined by two encoding bits jointly, and when a convolutional decoder is used for convolutional decoding at the receiving end, the likelihood value of state transition can be directly calculated by the distance between the received symbol and the constellation point, that is, joint demapping and decoding are performed. Since the demapping and convolutional decoding at the receiving end are based on the mapped symbol, that is, two bits are processed, compared with processing in units of single bits, the performance of the receiver can be significantly improved. The method of the embodiment can be used in a UWB receiver, since the UWB physical layer uses a convolutional code with a code rate of 0.5, each original input bit corresponds to the output of two encoding bits, that is, the position of a symbol is determined.

[0075] Based on the symbol mapping method specified by the UWB physical layer, in HRP mode or BPRF mode of HRP-ERDEV devices (both modes employing BPM-BPSK modulation), or in HPRF mode of HRP-ERDEV devices with a convolutional code constraint length of 3, the symbol mapping result is jointly determined by two coded bits. This disclosure proposes an embodiment of a method for joint demapping and convolutional decoding at the receiver. This method can significantly improve the decoding performance of the receiver without increasing computational complexity.

[0076] Therefore, embodiments of this disclosure propose that when calculating the branch metric in the Viterbi decoder, the likelihood value of a particular symbol should be considered, rather than calculating the likelihood values ​​of two bits separately and then combining them. Specifically, the branch metric is defined as the likelihood value of the corresponding symbol, thereby quantifying the probability of a state transition occurring.

[0077] Taking BPM-BPSK modulation as an example, the four branch metrics can be defined as follows:

[0078] In Viterbi decoding, updating the path metric for each state involves choosing between two arrival paths. Since the constant summation and positive constant multipliers in the branch metric calculation do not change with state or time, they do not affect path selection. Therefore, it can be simplified to:

[0079] Add to each item Removing the common factor 2 will not affect the path selection, therefore we can obtain: γ 00 =y0,γ 01 =-y0,γ 10 =y1,γ 11 =-y1.

[0080] In an exemplary embodiment of this disclosure, each state transition in the decoding process generates a symbol, and the mapping relationship between the encoded bits and the symbols is as follows: 00 is mapped to symbol (1,0), 01 is mapped to symbol (-1,0), 10 is mapped to symbol (0,1), and 11 is mapped to symbol (0,-1).

[0081] The likelihood value for each possible value of the symbol is calculated using the following formula: γ 00 =y0,γ 01 =-y0,γ 10 =y1,γ 11 =-y1

[0082] Where, γ 00 γ represents the likelihood value with a sign of 00. 01 γ represents the likelihood value with a sign of 0 or 1.10 denotes the likelihood value of the symbol taking value 10, y0is the first component in the received symbol, and y1is the second component in the received symbol. 11 denotes the likelihood value of the symbol taking value 11, y0is the first component in the received symbol, and y1is the second component in the received symbol.

[0083] The method of the embodiment can be applied to an ultra-wideband wireless communication system; a physical layer of the ultra-wideband wireless communication system works in an HRP mode or works in a BPRF mode as an HRP-ERDEV device; the physical layer of the ultra-wideband wireless communication system adopts a BPM-BPSK modulation mode, and every two coded bits are mapped to one symbol.

[0084] The Viterbi decoder of the embodiment calculates the likelihood value of each state transition according to a received signal as a branch metric. The branch metric is summed with a current path metric of each state, and a path with a larger sum is selected from two paths reaching each state, and the path metric of each state is updated. When a terminal point of the path is reached, the decoder obtains a path with a largest path metric, and a decoded bit sequence can be obtained by backtracking, which corresponds to a maximum likelihood solution of decoding.

[0085] Similarly, when the UWB physical layer works in the HPRF mode as the HRP-ERDEV device and the constraint length of the convolution code is equal to 3, the calculation can be obtained as follows: 00 = y0+ y1, γ 01 = -y0- y1, γ 10 = -y0+ y1, γ 11 = y0- y1.

[0086] It can be seen that the calculation of the branch metric is very simple in the joint demapping and decoding scheme.

[0087] In another exemplary embodiment of the disclosure, each state transition of the decoding process generates one symbol, and the mapping relationship between the coded bits and the symbol is as follows: 00 is mapped to the symbol (1, 1), 01 is mapped to the symbol (-1, -1), 10 is mapped to the symbol (-1, 1), and 11 is mapped to the symbol (1, -1).

[0088] The likelihood value of each value of the symbol is calculated by the following formula: 00 = y0+ y1, γ 01 = -y0- y1, γ 10 = -y0+ y1, γ 11 = y0- y1

[0089] wherein γ 00 denotes the likelihood value of the symbol taking value 00, γ 01 denotes the likelihood value of the symbol taking value 01, γ 10denotes the likelihood value of the symbol taking value 10, y0 is the first component in the received symbol, and y1 is the second component in the received symbol. 11 denotes the likelihood value of the symbol taking value 11, y0 is the first component in the received symbol, and y1 is the second component in the received symbol.

[0090] The method of the embodiment can be applied to an ultra-wideband wireless communication system, a physical layer of the ultra-wideband wireless communication system working in an HPRF mode as an HRP-ERDEV device, and a constraint length of a convolution code being equal to 3, and every two coded bits being mapped to one symbol.

[0091] In an example embodiment of the present disclosure, the branch metric of each state transition branch is obtained based on the likelihood value, including: taking the calculated likelihood value of each value of the symbol as the branch metric of a corresponding state transition branch.

[0092] The implementation block diagram of the joint demapping and decoding proposed in the present solution is shown in FIG. 5. Compared with FIG. 3, the main difference is that the LLR calculation module in the front end of the decoder is removed, the decoder directly receives the demodulated signal, and the branch metric (BM) calculation module is modified.

[0093] The effect can be verified through simulation experiments: FIG. 5 shows the block error rate (BLER) of a test example varying with the signal-to-noise ratio, in which a PSDU with a length of 20 Byte is used, the modulation mode is BPM-BPSK, and the channel model is an additive white Gaussian noise channel. The line marked with BPM-BPSK, LLR in the figure corresponds to the first embodiment solution, and the line marked with BPM-BPSK, symb corresponds to the embodiment solution of the present disclosure. It can be seen that, at a working point of BLER = 1%, the present solution has achieved a performance gain of nearly 2 dB compared with the prior art. If the symbol mapping mode is independent for two coded bits (for example, when the UWB physical layer works in an HPRF mode as an HRP-ERDEV device and the constraint length of the convolution code is equal to 7), the prior art and the present solution are equivalent, and the decoding performance thereof corresponds to the line marked with BPSK in the figure. The line marked with BPM-BPSK, symb, list-2 in the figure is obtained by using a list algorithm (with a size of 2) on the Viterbi decoder based on the present solution, and it can be seen that the decoding performance is further improved, indicating that the present solution can be used together with other optimization algorithms.

[0094] For the symbol mapping mode satisfying the condition that the existence symbol component is jointly determined by multiple participating mapping encoding bits rather than determined separately, the joint demapping and decoding scheme proposed by the scheme avoids the performance loss caused by calculating the log-likelihood ratio of a single component in the received symbol first and then combining to obtain the branch metric, and can achieve performance gain compared with the prior art. In the above embodiment, the code rate of the Viterbi decoder has a matching relationship with the modulation mode: the convolutional code with a code rate of 0.5 generates two encoding bits per state transition, which can be mapped to a modulation symbol. However, the present disclosure is not limited to the condition that "convolutional code generates one symbol per state transition".

[0095] When the number of encoding bits corresponding to each original bit and the number of encoding bits contained in each symbol have a multiple relationship, for example, in an example, the number of encoding bits contained in each symbol is equal to N times the number of encoding bits corresponding to each original bit, that is, N state transitions generate one symbol, and N≥2, the Viterbi decoder can adopt a design similar to Radix-4, that is, processing N state transitions (such as twice state transition) per step, combining N state transitions into 1 time, and the calculation of the branch metric can directly adopt the symbol likelihood value-based method of the present scheme, and the likelihood value of each value of the symbol is the branch metric of each branch of the corresponding state transition.

[0096] In another example, if the number of encoding bits corresponding to each original bit is equal to M times the number of encoding bits contained in each symbol, that is, one state transition generates M symbols, and M≥2, the likelihood values of M symbols (such as two symbols) can be combined when calculating the branch metric, for example: in each state transition of the decoding process, the likelihood value of each value of M symbols is calculated according to the value of M received symbols, and then the branch metric of each state transition branch is obtained by accumulation. In summary, the embodiments of the present disclosure can be used in baseband receivers with modulation and encoding modes satisfying the above conditions, and the application in the UWB system is only one example, and it can also be used in other communication systems.

[0097] An embodiment of the present disclosure further provides a joint demapping and decoding apparatus, as shown in FIG. 9, comprising a memory 50 and a processor 60, the memory 50 storing a computer program, wherein the processor 60 can implement the joint demapping and decoding method according to any embodiment of the present disclosure when executing the computer program. The processor of the embodiment can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a microprocessor, etc., or other conventional processors, etc. The processor can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a ready programmable gate array (FPGA), discrete logic or other programmable logic device, discrete gate or transistor logic, discrete hardware component, or a combination thereof. That is, the processor of the above-mentioned embodiments can be any processing device or combination of devices that implement the methods, steps and logic block diagrams disclosed in the embodiments of the present disclosure. If the embodiments of the present disclosure are implemented partially in software, the instructions for the software can be stored in a suitable non-transitory computer readable storage medium, and the instructions can be executed in hardware using one or more processors to implement the methods of the embodiments of the present disclosure.

[0098] An embodiment of the present disclosure further provides a decoder, as shown in FIG. 7A, comprising a branch metric generation module 1011 and a path processing module 1012, wherein:

[0099] The branch metric generation module 1011 is configured to obtain a received symbol comprising a plurality of components from an input terminal, and obtain the branch metric of each state transition branch according to the joint demapping and decoding method of any embodiment of the present disclosure and output to the path processing module;

[0100] The path processing module 1012 is configured to update and record the path metric of each state based on the branch metric, determine a decoding path with the maximum path metric by backtracking when reaching the end of the decoding path, and obtain a sequence of decoded encoded bits based on the sequence of states contained in the determined decoding path.

[0101] In an exemplary embodiment of the present disclosure, the decoder is a Viterbi decoder, and the Viterbi decoder decodes a convolutional code with a code rate of 0.5.

[0102] An embodiment of the present disclosure further provides an integrated circuit, as shown in FIG. 7B, comprising a radio frequency module 2011, an analog signal processing module 2012 and a digital signal processing module 2013 connected in sequence, wherein:

[0103] The radio frequency module 2011 is configured to generate and emit electromagnetic wave signals, and receive electromagnetic wave signals;

[0104] The analog signal processing module 2012 is configured to down-convert the received electromagnetic wave signal to obtain an intermediate frequency signal; and

[0105] The digital signal processing module 2013 is configured to perform analog-to-digital conversion on the intermediate frequency signal to obtain a digital signal, and process the digital signal; wherein the digital signal processing module further comprises the decoder of any of the embodiments of the present disclosure.

[0106] In an example embodiment of the present disclosure, the integrated circuit is applied to an ultra-wideband system chip.

[0107] In some optional embodiments of the present disclosure, the integrated circuit can be an AiP (Antenna-In-Package) chip structure, an AoP (Antenna-On-Package) chip structure, an AoC (Antenna-On-Chip) chip structure, an RoP (Radiator on Package) chip, or the like. The RoP is a structure in which a radiator structure is arranged on a chip package (Package), and an air waveguide structure can be formed around the radiator structure by using solder balls, i.e., the radio frequency (RF) signal generated by the chip can be transmitted to an external antenna through the air cavity waveguide structure formed by the solder balls and the air waveguide built in the PCB, and then radiated to a target area.

[0108] An electromagnetic wave device is also provided in an embodiment of the present disclosure, as shown in FIG. 12, comprising: a carrier 4; an integrated circuit 5 according to any of the embodiments of the present disclosure arranged on the carrier 4; an antenna 6 arranged on the carrier 4 and integrated with the integrated circuit 5 as an integrated device (i.e., the antenna at this time can be an antenna arranged in an AiP, AoP, AoC, or RoP structure) or arranged separately; wherein the integrated circuit 5 is connected to the antenna 6 (i.e., the antenna at this time can be an antenna arranged in an AiP, AoP, AoC, or RoP structure), for transmitting and / or receiving the electromagnetic wave signal. The carrier can be a printed circuit board (PCB), and the integrated circuit and the antenna are connected through PCB traces.

[0109] The electromagnetic wave device can realize functions such as target detection and / or communication by transmitting and receiving electromagnetic wave signals, to provide the device body with detection target information and / or communication information, and further assist or even control the operation of the device body.

[0110] An embodiment of the present disclosure further provides a terminal device, as shown in FIG. 8, comprising: a device body; and an electromagnetic wave device as described in any embodiment of the present disclosure arranged on the device body; wherein the electromagnetic wave device is configured to perform target detection and / or communication to provide reference information for operation of the device body.

[0111] For example, on the basis of the above-mentioned embodiments, in one optional embodiment of the present disclosure, the electromagnetic wave device can be arranged outside the device body, or arranged inside the device body, and in other optional embodiments of the present disclosure, the electromagnetic wave device can also be partially arranged inside the device body and partially arranged outside the device body. The embodiments of the present disclosure do not limit this, and the specific arrangement can be determined as appropriate.

[0112] In one optional embodiment, the above-mentioned device body can be a component and product applied to fields such as smart city, smart residence, transportation, smart home, consumer electronics, security monitoring, industrial automation, in-cabin detection (such as smart cockpit), medical devices and health care, etc. For example, the device body can be a smart transportation device (such as a car, a bicycle, a motorcycle, a ship, a subway, a train, etc.), a security device (such as a camera), a liquid level / flow rate detection device, a smart wearable device (such as a bracelet, glasses, etc.), a smart home device (such as a sweeping robot, a door lock, a television, an air conditioner, a smart lamp, etc.), various communication devices (such as a mobile phone, a tablet computer, etc.), etc., and can also be, such as a barrier gate, a smart traffic light, a smart signboard, a traffic camera, various industrialized mechanical arms (or robots), etc., and can also be various instruments for detecting vital characteristic parameters and various devices carrying the instruments, such as in-cabin vital characteristic detection of a car, indoor personnel monitoring, a smart medical device, a consumer electronic device, a car digital key, a mouse, etc.

[0113] An embodiment of the present disclosure further provides a non-transitory computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the joint demapping and decoding method according to any embodiment of the present disclosure.

[0114] Hereinafter, the technical solutions of the present disclosure will be described in detail with UWB as an example:

[0115] In this document, decoding can also be referred to as demapping.

[0116] In UWB technology, HRP (High Rate Pulse) refers to a high-rate pulse mode. It is a mode in UWB communication, corresponding to LRP (Low Rate Pulse) mode. HRP mode is used in UWB communication to achieve high-rate data transmission. It uses a higher pulse repetition rate to transmit information by sending narrow pulses in the nanosecond level. These narrow pulses have a very wide bandwidth and can carry a large amount of information, and can provide better performance in multipath environments.

[0117] In the physical layer technology of UWB, HRP mode defines different frequency bands and channels to meet different application requirements. For example, HRP UWB can define Sub GHz frequency band, Low Band frequency band and High Band frequency band, etc., and provide multiple channels for selection in each frequency band. Some of these channels support larger bandwidth to achieve higher data transmission rate.

[0118] HRP UWB PHY refers to High Rate Pulse Ultra-Wideband physical layer. HRP UWB PHY is based on IEEE 802.15.4a / z standards, etc., and uses narrow pulses in the nanosecond level for data transmission. It defines different frequency bands and channels to meet various application requirements, and has the advantages of low system complexity, low transmit signal power spectral density, low sensitivity to channel fading, low interception ability, high positioning accuracy, etc. It is especially suitable for high-speed wireless access and accurate positioning in dense multipath places such as indoor.

[0119] In addition, HRP UWB PHY also supports higher pulse repetition frequency to achieve higher data transmission rate. And in order to enhance the security of ranging devices, STS (Scrambled Time Stamp Sequence) technology is introduced.

[0120] In IEEE 802.15.4z standard, for HRP-ERDEV (Enhanced Ranging Device), two modes of BPRF (Base pulse repetition frequency) and HPRF (Higher pulse repetition frequency) are defined.

[0121] In UWB communication, especially in HRP (High Rate Pulse) UWB mode, BPM-BPSK or BPSK modulation strategies can be employed to transmit the encoded bit sequence. Among them, BPM (Binary (burst) Position Modulation) modulation is a position modulation method, in which information is represented by the position of the pulse (burst), i.e. the position of each pulse can correspond to a specific data symbol or bit combination. BPSK (Binary Phase-shift Keying) modulation is a phase modulation method, in which information is represented by changing the phase of the carrier. In BPSK, there are usually two phases, each representing a binary value (0 or 1).

[0122] When the two modulation methods are used together, i.e. BPM-BPSK joint modulation, the two modulation methods can jointly act on the encoded bit sequence to generate a composite modulation signal. That is, this signal contains both the pulse position information provided by BPM and the phase information provided by BPSK, to provide higher data transmission rate and / or better anti-interference ability, i.e. to effectively improve the efficiency and reliability of data transmission. In practical applications, this composite modulation strategy may require specific receiving algorithms to correctly decode and recover the original bit sequence. And the performance of the system will be affected by channel conditions, noise interference and other factors.

[0123] In UWB technology, modulation constellation is a graphical representation used to represent the positions of different modulation symbols in signal space. Each constellation point corresponds to a specific symbol, which is represented by a certain number of bits.

[0124] Gray code is a binary number system in which consecutive values differ by only one bit. In communication, using a Gray code constellation means that there is only one bit difference between adjacent constellation points, which helps to reduce errors caused by noise or interference, because when a symbol is misjudged as an adjacent symbol, only one bit will be wrong.

[0125] In UWB communication, due to the use of modulation constellation that is not arranged in Gray code, adjacent constellation points may differ in more than one bit, which usually increases the error rate of the original bits in communication. That is, if the modulation constellation is not Gray, i.e. "non-Gray", adjacent constellation points may differ in more than one bit. This means that when a misjudgment occurs, multiple bits may be wrong, thus increasing the severity of the error.

[0126] For a communication device using a BPM-BPSK joint modulation, the modulation constellation is in non-Gray format. Using bit-wise soft information based decoding can increase the error rate of subsequent data transmission and decoding. Although some error correction mechanisms can improve the reliability of transmission and reduce the error rate of decoding to some extent, the error correction result still cannot meet the current product requirements, and further improvement is urgently needed.

[0127] For example, for HRP-ERDEV devices in HRP UWB devices in BPRF mode, they can all use a combination of binary position modulation and binary phase shift keying to modulate the encoded bit sequence, i.e., they can all use BPM-BPSK joint modulation, so that the modulation constellation generated after modulation is in non-Gray format, which means that there can be more than one bit difference between adjacent constellation points. This usually increases the error rate of the original bits during decoding because the difference between adjacent symbols is large. In addition, HRP-ERDEV devices in HRP UWB devices in HPRF mode, when using convolutional codes with a constraint length of 3, the modulation mapping after modulation is also non-Gray, which also increases the error rate of subsequent decoding.

[0128] UWB uses convolutional codes with a rate of 0.5 for channel coding to correct errors and improve the reliability of data transmission after modulation. At the receiving end, soft Viterbi decoding algorithm can also be used for decoding, i.e., using the soft information of the received signal (such as log likelihood ratio, abbreviated as LLR) to improve decoding performance. However, for the above modulation (non-Gray code) - decoding (bit-wise LLR based Viterbi) method, since the standard LLR calculation method does not use the correlation between symbols introduced by non-Gray symbol mapping, some information that can help decoding can be lost, which can cause decoding error rate to deteriorate, resulting in a decrease in system sensitivity, thus failing to meet the current high-precision information transmission requirements.

[0129] In some optional embodiments of the present disclosure, a joint demapping and decoding method is proposed, as shown in FIG. 14, including: step 210, obtaining a modulation constellation in non-Gray format, i.e., obtaining a received symbol including multiple components, each component of the received symbol being jointly determined by multiple encoded bits participating in symbol mapping; and step 220, decoding based on the correlation between mapping symbols.

[0130] In one example of the embodiment, the decoding based on the correlation between the mapped symbols comprises decoding based on a level of correlation between the mapped symbols to calculate a posterior probability.

[0131] The method of the above embodiment of the present disclosure can be applied in a UWB PHY layer, and by effectively utilizing the inter-symbol correlation introduced by the non-Gray symbol mapping, better performance than the LLR-based decoding can be achieved without increasing the complexity. That is, by jointly operating the demapping and decoding, the accuracy of the decoding can be improved without increasing the complexity of the system, thereby enhancing the reliability of the communication system.

[0132] For example, for a BPM-BPSK modulation model, let b represent a convolutional encoded bit, let x represent a modulated symbol, and let y represent a received symbol, the corresponding convolutional encoded pair (b0, b1) is non-Grayly mapped to the modulated symbol pair (x0, x1), and the specific mapping relationship can be referred to in Table 1 below (where the power of each symbol is a unit power):

[0133] Table 1

[0134] The constellation diagram corresponding to the above Table 1 can be referred to in FIG. 10a, and compared with the Gray code constellation diagram shown in FIG. 10b, it can be seen that in the non-Gray code constellation diagram in FIG. 10a, there can be more than one bit difference between adjacent constellation points (such as two bit differences between 00 and 11).

[0135] It should be noted that the modulated symbol pair (x0, x1) is determined by the corresponding convolutional encoded pair (b0, b1) together, rather than being mapped from (b0) to (x0) and (b1) to (x1) separately.

[0136] For an Additive White Gaussian Noise (AWGN) channel, in the corresponding received symbol pair (y0, y1), y0=x0+n0, y1=x1+n1. Where the Energy per bit of each bit is 1 / 2, that is, the sum of the energy of two bits is 1; n0, n1 are noise samples, which are i.i.d. Gaussian with variance 2 .

[0137] ​That is, for the modulation model of BPM-BPSK, the pair of convolutional coded bits (b0, b1) is mapped to a two-dimensional modulation symbol (x0, x1), and since the mapping is non-Grey, it means that adjacent symbols can differ in multiple bits. In addition, when the mapped modulation symbol is transmitted through an additive white Gaussian noise channel, noise is added to the received symbol pair (y0, y1), that is, the two-dimensional modulation symbol (x0, x1) and the noise (n0, n1), and the energy per bit is related to the noise variance. Since in the actual receiver system, after the baseband signal processing of the previous stage, such as synchronization, channel estimation, channel equalization and other operations, the channel used by the demapping and decoding module can be approximately considered as an additive white Gaussian noise channel, therefore, based on the model, another demodulation method is proposed after the new research of the embodiment of the disclosure, which can be specifically:

[0138] When decoding the BPM-BPSK modulation signal, the LLR (log likelihood ratio) value generated by the demodulator can also be used as the input of the soft Viterbi decoder, and since the LLR value can be used as a measure of the possibility of each coded bit being “0” or “1”, that is, for the BPM-BPSK modulation model in UWB, by introducing the LLR value into the decoding process, the correlation between symbols can be introduced into the decoding process, so that the decoder can more accurately estimate the value of each coded bit, thereby improving the decoding performance.

[0139] For example, the expression of the above-mentioned LLR can be: L i = log Pr(b i = 0 | y0y1) - log Pr(b i = 1 | y0y1), i = 0, 1

[0140] Based on the above formula, by using the Bayes rule and the equally probable input assumption, it can be further obtained that: L i = log Pr(y0y1|b i = 0) - log Pr(y0y1|b i = 1) = 1

[0141] Therefore, for the BPM-BPSK joint modulation mode, based on the definition of conditional probability and the independent and identically distributed Gaussian noise (i.i.d. Gaussian noise), it can be obtained that:

[0142] wherein, L i represents the value of LLR, L0 represents the value of LLR when the coded bit is "0", and L1 represents the value of LLR when the coded bit is "1".

[0143] That is, for BPM-BPSK modulation, since each symbol is determined by two bits together, there are two LLR values L0 and L1, which correspond to two coded bits respectively, and in the process of obtaining the above LLR value L i , the received received symbol pair (y0, y1), the energy of each bit 1 / 2, the noise variance, and the possible values of coded bits are introduced, so as to introduce the correlation between symbols in the decoding process, so that the decoder can more accurately estimate the value of the coded bit, thereby improving the performance of the communication system.

[0144] In addition, in some optional embodiments, the calculation of LLR can also be greatly simplified without sacrificing performance by using max-log approximation. The formula of max-log approximation is: log(exp(x)+exp(y))≈max(x,y)

[0145] That is, for BPM-BPSK joint modulation mode, based on the formula of the above LLR value L i , it can be simplified as:

[0146] However, this LLR calculation method may cause information loss, and L0, L1 cannot recover the original information, i.e., y0, y1 corresponding.

[0147] For example, the above LLR values L0, L1 are used as the input of the Viterbi decoder, and the architecture of convolutional decoding is shown in FIG. 3. That is, in the decoding process of the communication system, the use of LLR can help to extract the original information (i.e., the information sent during transmission) from the received signal. When LLR is obtained in a conventional manner, it may involve relatively complex operation processing. The present disclosure provides a method of using max-log approximation, which greatly simplifies the operation processing operation of LLR under the premise of maintaining certain decoding performance, or even maintaining the decoding performance unchanged, thereby effectively improving the decoding efficiency and reducing the system complexity.

[0148] As shown in FIG. 11, in the process of Viterbi decoding, each state transition on the trellis is associated with an information bit and the corresponding encoded bits.

[0149] The branch metric (BM) can be used to measure the value of the likelihood of a state transition at a certain time, and in a communication system, the BM can be used as a measure to measure the difference between the received signal and each possible transmitted signal. Therefore, it is common to use the branch metric (BM) to measure the likelihood of a state transition in the above HRP UWB, which can generally be represented by a combination of a series of LLR values. For example, for a convolutional code with a rate of 1 / 2 in UWB, the formula of the branch metric γ can be: γ = (1 - 2b0) · L0 + (1 - 2b1) · L1

[0150] Based on the above formula, the basic assumption is that from the perspective of modulation, b0 and b1 are independent of each other. However, for HRP UWB, b0 and b1 are obviously not independent of each other, because the modulation symbol pair (x0, x1) is determined by the corresponding convolutional code pair (b0, b1) jointly, rather than simply combining b0 to map to x0 and b1 to map to x1 to obtain the modulation symbol pair (x0, x1).

[0151] In some optional embodiments of the present disclosure, a joint demapping and decoding method is also provided, as shown in FIG. 15, which includes: step 310, obtaining a non-gray format modulation map; and step 320, using a maximum log approximation method for decoding.

[0152] In an example of the present embodiment, in scenarios such as reducing bit error rate by using a non-gray format to enhance the correlation between modulation map symbol keys, etc., the modulation map obtained by the UWB device using BPM-BPSK joint modulation can be obtained first, that is, the non-gray format modulation map can be the modulation map obtained by the UWB device using BPM-BPSK joint modulation; or for HRP-ERDEV devices in HPRF mode, the non-gray format modulation map is the mapping map after modulation when using a convolutional code with a constraint length of 3.

[0153] In an example of the present embodiment, the branch metric obtained based on the symbol pair is used for decoding operation.

[0154] In an example of the embodiment, the likelihood of each value of the symbol is calculated by the following equation: γ 00 = y0, γ 01 = -y0, γ 10 = y1, γ 11 = -y1

[0155] Alternatively, the likelihood of each value of the symbol is calculated by the following equation: γ 00 = y0+y1, γ 01 = -y0-y1, γ 10 = -y0+y1, γ 11 = y0-y1

[0156] where γ 00 represents the likelihood of the symbol taking the value 00, γ 01 represents the likelihood of the symbol taking the value 01, γ 10 represents the likelihood of the symbol taking the value 10, and γ 11 represents the likelihood of the symbol taking the value 11, y0 is the first component of the received symbol, and y1 is the second component of the received symbol.

[0157] The posteriori probability is calculated at the symbol level, rather than at the bit level. This is because each state transition corresponds to 2 encoded bits that map to one symbol, so calculating the posteriori probability at the symbol level preserves more information than calculating the posteriori probability at the bit level.

[0158] For example, for the BPM-BPSK modulation scheme, the branch metric can be set as γ ∝ Pr(b0b1|y0y1), i.e.

[0159] For the Viterbi decoding process, since the same constant term and positive scaling do not affect the results of path selection, the branch metric equation above can be simplified as: γ 00 ~ -(y0-1) 2 -y1 2 ~ y0 γ 01 ~ -(y0+1) 2 -y1 2 ~ -y0 γ 10 ~ -y0 2 -(y1-1) 2 ~ y1 γ 11 ~ -y0 2 -(y1+1) 2 ~ -y1

[0160] The value of the branch metric mentioned above can be directly used as the ACS unit in the Viterbi decoder (ACS array shown in Figure 5, compared with the architecture shown in Figure 3, in the example shown in Figure 5, since there is no LLR value for the bit, only 4 soft information channels for the symbol can be used, i.e. the LLR generator module shown in Figure 3 can be omitted.

[0161] In some optional embodiments, for the HRP-ERDEV in the HPRF mode, when the convolution code constraint length is 3, the modulation scheme is not BPM-BPSK, but its mapping is also non-Grey code (as shown in Table 2 below).

[0162] The specific mapping relationship can be referred to Table 2 below (where the power of each symbol is a unit power):

[0163] Table 2

[0164] The constellation diagram corresponding to the above table in Table 2 is shown in Figure 12. At this time, the symbol-based branch metric can be calculated based on the following formula: γ 00 = y0+ y1 γ 01 = -y0- y1 γ 10 = -y0+ y1 γ 11 = y0- y1

[0165] That is, based on the similar idea as BPM-BPSK, compared with the decoding mode of LLT, the scheme in this embodiment improves the decoding performance by using the symbol-based branch metric without increasing the calculation complexity, thereby effectively improving the decoding efficiency and reducing the system complexity.

[0166] Compared with the conventional scheme, the performance index achieved by the technical scheme described in the embodiments of the present disclosure is effectively improved, regardless of the comparison from the performance indicators such as decoding accuracy and / or block-error-rate. For example, as can be known from the performance comparison diagram shown in FIG. 13, when transmitting 20 bytes of payload data, the reliability of data transmission is improved by using the additive white Gaussian noise (AWGN) channel and Reed-Solomon (RS) encoding / decoding technology. In terms of performance comparison, the technical scheme proposed in the embodiments of the present disclosure (curve 1) can significantly improve the communication performance compared with the conventional scheme (curve 2), that is, the performance advantage of the present scheme can be clearly shown by comparing the curves 1 and 2. Curve 4 is a reference, and the corresponding modulation mode is the system performance when the BPSK is used. At this time, due to the use of Gray coding, LLR-based decoding and the performance of the present scheme are approximately the same. Curve 3 is the effect of combining a common method for improving the performance of Viterbi decoding (list Viterbi) with the present scheme, which can illustrate that the present scheme generally does not conflict with other optimization algorithms and can be combined for further performance improvement. Among them, curve 1 is BPM-BPSK, symb; curve 2 is BPM-BPSK, LLR; curve 3 is BPM-BPSK, symb, list-2; and curve 4 is BPSK.

[0167] It should be noted that the scheme described in the embodiments of the present disclosure is not limited to the modulation and coding scheme (MCS) specified in the UWB PHY (physical layer), such as the BPM-BPSK mode, but can also be applied to other schemes such as the encoding modulation system using Viterbi decoding as the channel decoding scheme, as long as the code rate and modulation order meet the preset conditions, for example:

[0168] When one state transition produces one modulation symbol in the MCS scheme, in the UWB PHY scenario, the branch metric can be obtained based on the embodiments provided in the embodiments of the present disclosure.

[0169] When one state transition produces multiple modulation symbols, the branch metric can be set equal to the sum of Euclidean distances to the target constellation points.

[0170] When multiple state transitions produce one modulation symbol, the constellation points can be grouped, each group corresponding to one state transition, and the sum of Euclidean distances of each group can be calculated; or, multiple stages can be processed at one time when passing the Trellis forward (similar to a Radix-4 Viterbi decoder).

[0171] In summary, the technical solutions in the embodiments of the present disclosure have wide applicability and flexibility, which are not limited to specific modulation and coding schemes (MCS) in UWB PHY, but can also be applied to different types of coded modulation systems, such as systems using Viterbi decoding as the channel decoding scheme, as long as the code rate and modulation order of these systems meet the preset conditions. In some optional embodiments, flexible ways of calculating branch metrics according to different MCS are also provided based on the similar ideas described above. For example, when one state transition produces one modulation symbol, the branch metric can be calculated according to the content described in the above embodiments. When one state transition produces multiple modulation symbols, the branch metric is set equal to the sum of Euclidean distances of these modulation symbols to their respective target constellation points. When multiple state transitions produce one modulation symbol, two processing methods can be used: one is to group the constellation points, each group corresponding to one state transition, and then calculate the sum of Euclidean distances of each group as the branch metric; the other is to process multiple stages at one time in the forward process of Viterbi decoding, similar to a Radix-4 Viterbi decoder.

[0172] The embodiments of the present disclosure further provide an integrated circuit, which can include a radio frequency module and a signal processing module connected in sequence. The signal processing module can be based on the joint de-mapping and decoding method described in the embodiments of the present disclosure, and for BPM-BPSK modulation, the LLR value is introduced into the decoding process, and then the correlation between symbols is introduced into the decoding process, so that the decoder can more accurately estimate the value of each coded bit, thereby improving the decoding performance. In some alternative embodiments, the signal processing module can also be based on the joint de-mapping and decoding method described in the embodiments of the present disclosure, and the posterior probability is calculated at the symbol level instead of the bit level. This is because each state transition corresponds to 2 coded bits mapped to a symbol, so calculating the posterior probability at the symbol level preserves more information than calculating the posterior probability at the bit level. In some alternative embodiments, the signal processing module can also be based on the joint de-mapping and decoding method described in the embodiments of the present disclosure, and for HRP-ERDEV in HPRF mode, when the convolutional code constraint length is 3, the decoding performance is improved by using symbol-level branch metrics without increasing the computational complexity, thereby effectively improving the decoding efficiency and reducing the system complexity. The radio frequency received signal can be a backscatter signal formed by the target transmitting and / or scattering the radio frequency transmitted signal, or a radio frequency transmitted signal transmitted by another device. Optionally, the integrated circuit can further include a data processing module for processing digital signals to achieve target detection and / or wireless communication, for example, the integrated circuit can be a UWB chip (chip or die).

[0173] Those of ordinary skill in the art will realize and understand that all or some of the steps in the methods disclosed above and the functional modules / units in the systems and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Some or all of the components can be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on computer-readable media, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, it is common and well understood by those of ordinary skill in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and can include any information delivery media.

Claims

1. A method of joint demapping and decoding, comprising: obtaining a received symbol comprising a plurality of components, each component of the received symbol being jointly determined by a plurality of coded bits participating in symbol mapping; calculating a likelihood value of each value of the symbol based on a value of the received symbol when a state transition of a decoding process occurs, and obtaining a branch metric of each state transition branch based on the likelihood value.

2. The method of claim 1, wherein: each state transition of the decoding process generates a symbol, and the calculating a likelihood value of each value of the symbol based on a value of the received symbol when a state transition of a decoding process occurs comprises calculating a likelihood value of each value of the symbol based on a value of the received symbol when each state transition of the decoding process occurs.

3. The method of claim 1, wherein: each state transition of the decoding process generates a symbol, and a mapping relationship between coded bits and the symbol is that 00 is mapped to symbol (1, 0), 01 is mapped to symbol (-1, 0), 10 is mapped to symbol (0, 1), and 11 is mapped to symbol (0, -1); the likelihood value of each value of the symbol is calculated by the following formula: γ 00 = y0,γ 01 = -y0,γ 10 = y1,γ 11 = -y1 wherein γ 00 denotes the likelihood value for a symbol value of 00, γ 01 denotes the likelihood value for a symbol value of 01, γ 10 denotes the likelihood value for a symbol value of 10, γ 11 denotes the likelihood value for a symbol value of 11, y0is the first component of the received symbol, and y1is the second component of the received symbol.

4. The method of claim 3, wherein: the method is applied to an ultra-wideband wireless communication system; a physical layer of the ultra-wideband wireless communication system operates in an HRP mode or operates in a BPRF mode as an HRP-ERDEV device; the physical layer of the ultra-wideband wireless communication system adopts a BPM-BPSK modulation mode, and each two coded bits are mapped to one symbol.

5. The method of claim 1, wherein: each state transition of the decoding process generates a symbol, and a mapping relationship between coded bits and the symbol is that 00 is mapped to symbol (1, 1), 01 is mapped to symbol (-1, -1), 10 is mapped to symbol (-1, 1), and 11 is mapped to symbol (1, -1); the likelihood value of each value of the symbol is calculated by the following formula: γ 00 = y0 + y1, γ 01 = -y0 - y1, γ 10 = -y0 + y1, γ 11 = y0 - y1 wherein γ 00 denotes the likelihood value for a symbol value of 00, γ 01 denotes the likelihood value for a symbol value of 01, γ 10 denotes the likelihood value for a symbol value of 10, γ 11 denotes the likelihood value for a symbol value of 11, y0is the first component of the received symbol, and y1is the second component of the received symbol.

6. The method of claim 5, wherein: the method is applied to an ultra-wideband wireless communication system, a physical layer of the ultra-wideband wireless communication system operates in an HPRF mode as an HRP-ERDEV device, and a constraint length of a convolution code is equal to 3, and each two coded bits are mapped to one symbol.

7. The method of any one of claims 3 to 6, wherein: the obtaining a branch metric of each state transition branch based on the likelihood value comprises taking the calculated likelihood value of each value of the symbol as a branch metric of a corresponding state transition branch.

8. A method of joint demapping and decoding, comprising: obtaining a modulation constellation of a non-gray format; and decoding based on a correlation between mapped symbols.

9. The method of claim 8, wherein, The decoding based on the correlation between mapped symbols comprises decoding based on a level of the correlation between mapped symbols.

10. A method of joint demapping and decoding, comprising: obtaining a modulation constellation of a non-gray format; and decoding in a maximum log approximation manner.

11. The method of claim 10, wherein, The modulation constellation of the non-gray format is obtained by a UWB device adopting BPM-BPSK joint modulation; or, The modulation pattern of the non-gray format is a mapping pattern after modulation when a convolutional code with constraint length 3 is used for the HRP-ERDEV device in the HPRF mode.

12. The method of claim 11, wherein, The branch metrics obtained based on the symbols are decoded.

13. The method of claim 12, wherein, The likelihood value of each value of the symbol is calculated by the following formula: γ 00 = y0,γ 01 = -y0,γ 10 = y1,γ 11 = -y1 Or, the likelihood value of each value of the symbol is calculated by the following formula: γ 00 = y0+ y1, γ 01 = -y0- y1, γ 10 = -y0+ y1, γ 11 = y0- y1; wherein γ 00 denotes the likelihood value for the symbol value 00, γ 01 denotes the likelihood value for the symbol value 01, γ 10 denotes the likelihood value for the symbol value 10, γ 11 denotes the likelihood value for the symbol value 11, y0is the first component of the received symbol, and y1is the second component of the received symbol.

14. A joint de-mapping and decoding apparatus comprising a memory and a processor, said memory storing a computer program, wherein, The processor, when executing the computer program, can implement the joint demapping and decoding method of any one of claims 1-13.

15. A decoder comprising a branch metric generation module and a path processing module, wherein: The branch metric generation module is configured to obtain received symbols comprising a plurality of components from an input terminal, obtain branch metrics of each state transition branch according to the joint demapping and decoding method of any one of claims 1-13, and output to the path processing module; The path processing module is configured to update and record path metrics of each state based on the branch metrics, determine a decoding path with the largest path metric by backtracking when reaching the end of the decoding path, and obtain a sequence of decoded coded bits based on a sequence of states contained in the determined decoding path.

16. The decoder of claim 15, wherein: The decoder is a Viterbi decoder, and the Viterbi decoder decodes a convolutional code with a code rate of 0.

5.

17. An integrated circuit comprising a radio frequency module, an analog signal processing module, and a digital signal processing module connected in sequence; The radio frequency module is configured to generate and emit electromagnetic wave signals, and receive electromagnetic wave signals; The analog signal processing module is configured to down-convert the received electromagnetic wave signals to obtain intermediate frequency signals; The digital signal processing module is configured to perform analog-to-digital conversion on the intermediate frequency signals to obtain digital signals, and process the digital signals; wherein The digital signal processing module comprises the decoder of claim 15 or 16, or is configured to implement the joint demapping and decoding method of any one of claims 1-13.

18. The integrated circuit of claim 17, wherein, The integrated circuit is applied to an ultra-wideband system chip.

19. An electromagnetic wave device comprising: a carrier body; the integrated circuit of claim 17 or 18 disposed on the carrier body; an antenna disposed on the carrier body, integrated with the integrated circuit as an integrated device or disposed separately; wherein the integrated circuit is connected with the antenna to emit the electromagnetic wave signals and / or receive the electromagnetic wave signals.

20. A terminal device comprising: a device body; and the electromagnetic wave device of claim 19 disposed on the device body; wherein the electromagnetic wave device is configured to perform target detection and / or communication to provide reference information for the operation of the device body.

21. A non-transitory computer readable storage medium having stored thereon a computer program, wherein, The computer program is executed by the processor to implement the joint demapping and decoding method of any one of claims 1-13. The computer program is executed by the processor to implement the joint demapping and decoding method of any one of claims 1-13.

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