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

Abstract

A joint de-mapping and decoding method, device, decoder, integrated circuit, device and equipment are applied to the technical field of digital signal processing, a receiving symbol comprising a plurality of components is firstly acquired, and each component of the receiving symbol is jointly decided by a plurality of coding bits participating in symbol mapping; when state transition is carried out in a decoding process, calculating a likelihood value of each value of the symbol according to the value of the received symbol, and obtaining a branch metric of each state transition branch based on the likelihood value; the embodiment of the invention can improve the decoding performance.

Description

[0001] Cross-references to related applications

[0002] This disclosure claims priority to Chinese Patent Application No. 202410622969.6, filed on May 17, 2024, with the China National Intellectual Property Administration, entitled “Method, Apparatus, Integrated Circuit, Electromagnetic Wave Device and User Terminal Equipment for Joint Inverse Mapping and Decoding”, the contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to, but is not limited to, signal processing techniques, and more specifically, to a joint demapping and decoding method, apparatus, decoder, integrated circuit, device, and equipment. Background Technology

[0004] Ultra Wide Band (UWB) is a wireless communication technology whose physical layer (PHY) defines how signals are transmitted and received. UWB technology uses an extremely wide spectrum (typically between 3.1 GHz and 10.6 GHz) and short pulses (time-domain width on the nanosecond level) to transmit data, providing higher data transmission rates and more accurate positioning capabilities, but its decoding performance still needs improvement. Summary of the Invention

[0005] To address the aforementioned technical problems, embodiments of this disclosure provide a joint demapping and decoding method, decoder, integrated circuit, sensor, and device, applicable to, but not limited to, communication systems. When each component of a received symbol is jointly determined by multiple coded bits involved in symbol mapping, during state transitions in the decoding process, the likelihood value for each possible value of the received symbol is calculated based on the received symbol value. Then, a branch metric for each state transition branch is obtained based on the likelihood value. This avoids the performance loss caused by first calculating the log-likelihood ratio of a single component in the received symbol and then combining them to obtain the branch metric. Thus, the decoding performance of the receiver can be improved without increasing computational complexity.

[0006] One embodiment of this disclosure provides a joint demapping and decoding method, including:

[0007] Obtain a received symbol comprising multiple components, each component of which is jointly determined by multiple coded bits involved in the symbol mapping;

[0008] During the state transition in the decoding process, the likelihood value of each possible value of the symbol is calculated based on the value of the received symbol, and the branch metric of each state transition branch is obtained based on the likelihood value.

[0009] An embodiment of the present disclosure further provides a joint demapping and decoding method, comprising: obtaining a modulation constellation in a non-gray format; and decoding based on correlation between mapped symbols.

[0010] An embodiment of the present disclosure further provides a joint demapping and decoding method, comprising: obtaining a modulation constellation in a non-gray format; and decoding in a maximum log approximation manner.

[0011] 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.

[0012] An embodiment of the present disclosure further provides a decoder, comprising a branch metric generation module and a path processing module, wherein:

[0013] The branch metric generation module is configured to obtain received symbols comprising a plurality of components from an input end, and obtain branch metrics of each state transition branch and output to the path processing module according to the joint demapping and decoding method according to any embodiment of the present disclosure.

[0014] 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.

[0015] 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.

[0016] 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.

[0017] An embodiment of the present disclosure further provides a terminal device, comprising: a device body; and an electromagnetic wave device as described in any of the embodiments of the present disclosure arranged on the device body; wherein the electromagnetic wave device is used for target detection and / or communication to provide reference information for operation of the device body.

[0018] An embodiment of the present disclosure further provides a non-transitory computer readable storage medium, having stored thereon a computer program, which, when executed by a processor, is capable of implementing the joint demapping and decoding method according to any of the embodiments of the present disclosure.

[0019] Other features and advantages of the present disclosure will be set forth in the following description, and in part will become apparent from the description, or can be learned by practice of the present disclosure. Other advantages of the present disclosure will be realized and attained by those of ordinary skill in the art, including studying the following description and appended claims as well as practicing the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings are included to provide an understanding of the present technical solution, and constitute a part of the specification, and are used together with the embodiments of the present disclosure to explain the present technical solution, and do not constitute a limitation on the present technical solution. The shapes and sizes of the components in the drawings do not reflect the true proportions, and the purpose is only to schematically illustrate the present disclosure.

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

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

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

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

[0025] Figure 5 is a structural schematic diagram of a decoder in an embodiment of the present disclosure;

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

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

[0028] Figure 7Bis a schematic diagram of an integrated circuit according to an embodiment of the present disclosure;

[0029] Figure 8 is a schematic diagram of a terminal device according to an embodiment of the present disclosure;

[0030] Figure 9 is a schematic diagram of a joint de-mapping and decoding device according to an embodiment of the present disclosure;

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

[0032] Figure 10b is a BPSK / QPSK modulation gray code diagram;

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

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

[0035] Figure 13 is a performance comparison diagram of a scheme implementation;

[0036] Figure 14 is a flowchart of a joint de-mapping and decoding method according to another embodiment of the present disclosure;

[0037] Figure 15 is a flowchart of a joint de-mapping and decoding method according to still another embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] The present disclosure describes a plurality of embodiments, but the description is exemplary rather than limiting, and it is obvious to those skilled in the art that there can be more embodiments and implementation schemes within the scope of the embodiments described in the present disclosure.

[0039] In the description of the present disclosure, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. 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. "And / or" in this text is a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases of 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. Those skilled in the art can understand that "first", "second", etc. do not limit the quantity and execution order, and "first", "second", etc. also do not necessarily mean different.

[0040] In describing representative exemplary embodiments, the specification may have presented the method and / or process as a particular sequence of steps. However, to the extent that the method or process depends on the particular order of steps, the method or process should not be limited to the particular sequence of steps presented in this specification. Other sequences of steps can be possible, and should be understood as falling within the spirit and scope of the present disclosure. As examples of the above, U.S. Patent No. 6,301,579, filed on October 24, 2000, entitled "Method and Apparatus for Providing Location Based Services in a Wireless Environment," and U.S. Patent No. 6,735,000, filed on May 8, 2002, entitled "Method and Apparatus for Providing Location Based Services in a Wireless Environment," both of which are incorporated by reference herein, describe methods and apparatuses for providing location based services in a wireless environment. The steps of the methods and / or processes described in the specification are not necessarily limited to the specific sequences of steps presented in this specification. Other sequences of steps can be possible, and should be understood as falling within the spirit and scope of the present disclosure. The specific sequences of steps presented in the specification are exemplary and should not be construed as limitations on the scope of the claims. Furthermore, the claims should not be limited to the steps of the methods and / or processes in the specific order presented, as other sequences of steps can also be possible and should be understood as falling within the spirit and scope of the present disclosure.

[0041] First, some English abbreviations and English full names of terms used in this document are given as follows:

[0042] Physical Layer Service Data Unit: PSDU

[0043] Physical Layer Header: PHR

[0044] Single Error Correction, Double Error Detection: SECDED

[0045] Reed-Solomon: RS

[0046] High Rate Pulse: HRP

[0047] Enhanced Relative Error Detection and Verification: ERDEV

[0048] Base Pulse Repetition Frequency: BPRF

[0049] Binary (burst) Position Modulation: BPM

[0050] Binary Phase Shift Keying: BPSK

[0051] Quadrature Phase Shift Keying: QPSK

[0052] Constraint Length: CL

[0053] Log-likelihood ratio (LLR):

[0054] According to the IEEE Std 802.15.4 and IEEE Std 802.15.4z protocols, the UWB physical layer at the transmitter uses convolutional coding with a code rate of 0.5 for both the PHR and PSDU to be transmitted, followed by specific symbol mapping for subsequent modulation and beamforming. At the receiver's baseband processing, the demodulated data requires corresponding demapping and convolutional code decoding. For example... Figure 1A As shown, at the transmitting end, the PHR input is to the SECDED encoder 11, and the PSDU input is to the RS encoder 13 for encoding. The outputs of both the SECDED encoder 11 and the RS encoder 13 are input to a convolutional encoder 15 with a code rate of 0.5 for encoding. The output of the convolutional encoder 15 is then processed by the symbol mapping module 17 and other modules before being sent to the radio frequency module 19 for modulation, and then transmitted through the antenna. Figure 1B As shown, the signal received by the receiving antenna is synchronized, channel equalized and demodulated in the radio frequency module 21. The data is then symbol demapped in the symbol demapper 23, and then decoded by the Viterbi decoder 25. One path is sent to the RS decoder 29 to obtain the decoded PSDU, and the other path is sent to the SECDED decoder 27 to obtain the decoded PHR.

[0055] The symbol mapping rules for the UWB physical layer under different configurations are as follows: Figure 2 As shown. When the UWB physical layer operates in HRP mode or as an HRP-ERDEV device in BPRF mode (represented as HRP-ERDEV BPRF mode in the figure), the modulation method uses a combination of BPM and BPSK modulation (BPM-BPSK). In this case, each symbol is divided into two equal segments, and the pulse carrying the information is transmitted only in one segment. Each modulated symbol contains two bits of information: the first bit indicates the position of the pulse, i.e., in the first or second half of the symbol, and the second bit determines the phase of the pulse, i.e., +1 or -1; each bit in the symbol can also be called a component of the symbol. When the UWB physical layer operates as an HRP-ERDEV device in HPRF mode, the modulation method is similar to QPSK, and the symbol mapping rules differ depending on the constraint length of the convolutional code (CL=3 or CL=7).

[0056] like Figure 2As shown, when the UWB physical layer works in HRP mode or works in BPRF mode as an HRP-ERDEV device (using BPM-BPSK modulation), the mapping relationship between two coded bits and a symbol is: 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). When the UWB physical layer works in HPRF mode as an HRP-ERDEV device and the constraint length of the convolution code is equal to 3, the mapping relationship between two coded bits and a symbol is: 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). In these two cases, the value of each component of the symbol needs to be jointly determined by the two coded bits participating in the symbol mapping. Correspondingly, when the UWB physical layer works in HPRF mode as an HRP-ERDEV device and the constraint length of the convolution code is equal to 7, the mapping relationship between two coded bits and a symbol is: 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). 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, which are completely independent.

[0057] In the baseband data processing at the receiving end, referring to Figure 1B and Figure 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 Figure 3As shown, in the Viterbi decoder, first, the Branch Metric Generator 33 calculates branch metrics based on the LLRs 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 signals, i.e. receiving signals transmitted through a 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, using the information stored in the path record memory to perform traceback to determine the optimal decoding path, which traces the derived state sequence; outputting the encoded bits, i.e. according to the state sequence obtained by traceback to deduce the encoded bits sent by the sending end and output.

[0058] 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 of 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 encoded bits corresponding to the transmitted symbol be b0, b1, and their log-likelihood ratios be defined as:

[0059] L0=logPr(b0=0|y0y1)-logPr(b0=1|y0y1)

[0060] 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 Bayes' rule and the assumption that the probabilities of 0 and 1 in the coded bits are equal, the posterior probability in the log-likelihood ratio can be converted into conditional probability:

[0063] L0= logPr(y0y1|b0= 0) - logPr(y0y1|b0= 1)

[0064] L1= logPr(y0y1|b1= 0) - logPr(y0y1|b1= 1)

[0065] Since y0, y1are determined by b0, b1together, combined with the mapping relationship between coded bits and symbols under BPM-BPSK modulation shown in Figure 2 , the conditional probability can be written as:

[0066]

[0067] The above equation and the Gaussian probability density function are brought into the calculation of the log-likelihood ratio to obtain:

[0068]

[0069]

[0070] According to the approximate relationship: log(exp(x) + exp(y)) ≈ max(x, y), the expression of the log-likelihood ratio can be further simplified (the approximation error is very small and has almost no numerical impact):

[0071]

[0072] where σ represents the standard deviation of the Gaussian distribution.

[0073] Figure 3 The LLR generation module 31 in Figure 1B corresponding to the symbol demapping module 23 in Figure 3 performs the above calculation. However, this formula cannot be inversely deduced to the received signals y0and y1. This also shows that the method of performing demapping and decoding in steps has performance loss. In Figure 3 the Viterbi decoder, every two LLR inputs correspond to a state transition, and 4 branch metric values are calculated, respectively corresponding to the likelihood values of state transitions with outputs of 00 / 01 / 10 / 11:

[0074] γ 00 = L0+ L1, γ 01 = L0- L1, γ 10 = -L0+ L1, γ 11 = -L0- L1.

[0075] According to the branch metric values, the Viterbi decoder continuously updates the path metric and finally finds a decoding path that maximizes the path metric, thereby obtaining an optimal decoding result.

[0076] The above embodiment adopts a manner of first calculating the log-likelihood ratio of each encoding bit and then merging the log-likelihood ratio in branch metric calculation of the decoder. The default assumption is that the 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, the two encoding bits corresponding to the same symbol are related, and the step-by-step demapping and decoding adopted by the embodiment will cause performance loss. In the case of HRP-ERDEV equipment in HPRF mode and convolutional code constraint length equal to 3, the two encoding bits corresponding to the same symbol are also related, and there is also a performance loss problem.

[0077] To this end, an embodiment of the present disclosure provides a joint demapping and decoding method, as shown in the formula (1), comprising: Figure 4

[0078] In step 110, a received symbol including multiple components is obtained, and each component of the received symbol is jointly determined by multiple encoding bits participating in symbol mapping.

[0079] 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.

[0080] In an example of the embodiment, each state transition of the decoding process generates a symbol, and the calculation of the likelihood value of each value of the symbol according to the value of the received symbol when the state transition is performed in the decoding process comprises: the calculation of the likelihood value of each value of the symbol according to the value of the received symbol when each state transition of the decoding process is performed.

[0081] The method 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, determines the position of a symbol.

[0082] ​Based on the symbol mapping mode specified in the UWB physical layer, in the HRP mode or the BPRF mode of the HRP-ERDEV device (both modes use BPM-BPSK modulation), or in the HPRF mode of the HRP-ERDEV device and the convolution code constraint length is equal to 3, the result of symbol mapping is determined by two encoding bits jointly, and an embodiment of the present disclosure proposes a method of joint demapping and convolution decoding at the receiving end. The method can significantly improve the decoding performance of the receiver without increasing the calculation complexity.

[0083] Therefore, an embodiment of the present disclosure proposes that, when calculating the branch metric of the Viterbi decoder, the likelihood value of a certain symbol is considered instead of calculating the likelihood values of two bits respectively and then combining them. Specifically, the branch metric is defined as the likelihood value of the corresponding symbol, so as to quantify the possibility of state transition.

[0084] Taking BPM-BPSK modulation as an example, four branch metrics can be defined as:

[0085]

[0086] In the Viterbi decoding process, the update of the path metric of each state involves the selection from two arriving paths. Since the constant addition term and the normal number multiplier in the branch metric calculation do not change with the state and time, they will not affect the path selection, and thus can be simplified, so as to obtain:

[0087]

[0088] Adding to each term and removing the common factor 2 will not affect the path selection, and thus the following can be obtained:

[0089] γ 00 =y0,γ 01 =-y0,γ 10 =y1,γ 11 =-y1。

[0090] In an exemplary embodiment of the present disclosure, each state transition of the decoding process generates a symbol, and the mapping relationship between the encoding bits and the symbol is: 00 is mapped to the symbol (1, 0), 01 is mapped to the symbol (-1, 0), 10 is mapped to the symbol (0, 1), and 11 is mapped to the symbol (0, -1);

[0091] The likelihood value of each value of the symbol is calculated by the following formula:

[0092] γ 00 =y0,γ 01 =-y0,γ 10 =y1,γ11 = -y1

[0093] wherein γ 00 represents the likelihood value of the symbol taking value 00, γ 01 represents the likelihood value of the symbol taking value 01, γ 10 represents the likelihood value of the symbol taking value 10, γ 11 represents 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.

[0094] The method of the embodiment can be applied to an ultra-wideband wireless communication system; the physical layer of the ultra-wideband wireless communication system works in HRP mode or works in BPRF mode as an HRP-ERDEV device; the physical layer of the ultra-wideband wireless communication system adopts BPM-BPSK modulation mode, and every two coded bits are mapped to one symbol.

[0095] The Viterbi decoder of the embodiment calculates the likelihood value of each state transition according to the received signal as a branch metric. The branch metric is summed with the current path metric of each state, and the path with the larger sum is selected from the two paths reaching each state, and the path metric of each state is updated. When the end point of the path is reached, the decoder obtains the path with the largest path metric, and the decoded bit sequence can be obtained by backtracking, which corresponds to the maximum likelihood solution of decoding.

[0096] Similarly, when the UWB physical layer works in HPRF mode as an HRP-ERDEV device and the constraint length of the convolutional code is equal to 3, the calculation can be obtained as follows:

[0097] wherein γ 00 = y0 + y1, γ 01 = -y0 - y1, γ 10 = -y0 + y1, γ 11 = y0 - y1.

[0098] It can be seen that the calculation of the branch metric is very simple in the joint demapping and decoding scheme.

[0099] 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 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);

[0100] The likelihood value of each value of the symbol is calculated by the following formula:

[0101] wherein γ 00 = y0 + y1, γ 01= -y0 - y1, γ 10 = -y0 + y1, γ 11 = y0 - y1

[0102] where 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 10 denotes the likelihood value of the symbol taking value 10, γ 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.

[0103] 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.

[0104] In an example embodiment of the present disclosure, the branch metric of each state transition branch is obtained based on the likelihood values, including: taking the calculated likelihood value of each value of the symbol as the branch metric of the corresponding state transition branch.

[0105] The implementation block diagram of the joint demapping and decoding is shown in Figure 5 Compared with Figure 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.

[0106] The effect can be verified through simulation experiments: Figure 5The block error rate (BLER) of a test example is shown, in which a PSDU of 20 Byte length 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 corresponds to the first embodiment scheme, and the line marked with BPM-BPSK, symb corresponds to the embodiment scheme of the present disclosure. It can be seen that, at a working point of BLER = 1%, the embodiment scheme has a performance gain of nearly 2 dB compared with the prior art. If the symbol mapping mode is independent for two encoded bits (for example, when the UWB physical layer works in the HPRF mode as an HRP-ERDEV device and the constraint length of the convolutional code is equal to 7), the prior art and the embodiment scheme are equivalent, and the decoding performance corresponds to the line marked with BPSK in the figure. The line marked with BPM-BPSK, symb, list-2 is obtained by using a list algorithm (with a size of 2) for the Viterbi decoder on the basis of the embodiment scheme. It can be seen that the decoding performance is further improved, which indicates that the embodiment scheme can be used together with other optimization algorithms.

[0107] For the symbol mapping mode satisfying the condition that the symbol component is jointly determined by multiple encoded bits participating in mapping rather than being determined separately, the joint demapping and decoding scheme proposed in the embodiment avoids the performance loss caused by calculating the log-likelihood ratio of a single component of the received symbol and then combining to obtain the branch metric, and can obtain a performance gain compared with the prior art. In the above embodiment, the code rate of the Viterbi decoder is matched with the modulation mode: the convolutional code with a code rate of 0.5 generates two encoded bits per state transition, which can be mapped to a modulation symbol. However, the present disclosure is not limited to the condition that the convolutional code generates one symbol per state transition.

[0108] When the number of encoded bits corresponding to each original bit and the number of encoded bits contained in each symbol have a multiple relationship, for example, in an example, the number of encoded bits contained in each symbol is equal to N times the number of encoded bits corresponding to each original bit, that is, N state transitions generate one symbol, and N ≥ 2. The Viterbi decoder can be designed similarly to Radix-4, that is, N state transitions (for example, twice state transitions) are processed per step, and N state transitions are combined into one, and the calculation of the branch metric can use the symbol likelihood value-based method of the embodiment scheme, and the likelihood value of each symbol value is the branch metric of each branch of the corresponding state transition.

[0109] In another example, if the number of coded bits corresponding to a raw bit is equal to M times the number of coded bits in each symbol (i.e., M symbols are generated in one state transition, M≥2), then the likelihood values ​​of the M symbols (e.g., two symbols) can be combined when calculating the branch metric. For example, during each state transition in the decoding process, the likelihood value of each of the M received symbols is calculated based on their values, and then accumulated to obtain the branch metric for each state transition branch. In summary, the embodiments of this disclosure can be used in baseband receivers whose modulation and coding methods meet the above conditions. Its application in UWB systems is just one example; it can also be used in other sensing systems.

[0110] An embodiment of this disclosure also provides a joint demapping and decoding apparatus, such as Figure 9 As shown, the system includes a memory 50 and a processor 60. The memory 50 stores a computer program, and the processor 60, when executing the computer program, is capable of implementing the joint demapping and decoding method as described in any embodiment of this disclosure. The processor in this embodiment can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a microprocessor, etc., or other conventional processors; the processor can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), discrete logic or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components; or a combination of the above devices. That is, the processor in the above embodiments can be any processing device or combination of devices that implements the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. If the embodiments of this disclosure are implemented in part in software, then instructions for software can be stored in a suitable non-volatile computer-readable storage medium, and one or more processors can be used to execute the instructions in hardware to implement the methods of the embodiments of this disclosure.

[0111] One embodiment of this disclosure also provides a decoder, such as Figure 7A As shown, it includes a branch metric generation module 1011 and a path processing module 1012, wherein:

[0112] The branch metric generation module 1011 is configured to obtain received symbols including multiple components from the input end, and according to the joint demapping and decoding method described in any embodiment of this disclosure, obtain the branch metric of each state transition branch and output it to the path processing module.

[0113] 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 decoded bit sequence based on a state sequence contained in the determined decoding path.

[0114] In an example 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.

[0115] An integrated circuit is also provided in an example embodiment of the present disclosure, as shown in the accompanying drawings, which comprises a radio frequency module 2011, an analog signal processing module 2012 and a digital signal processing module 2013 connected in sequence, wherein: Figure 7B

[0116] The radio frequency module 2011 is configured to generate and emit electromagnetic wave signals, and receive electromagnetic wave signals;

[0117] The analog signal processing module 2012 is configured to down-convert the received electromagnetic wave signals to obtain intermediate frequency signals; and

[0118] The digital signal processing module 2013 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 further comprises the decoder according to any one of the embodiments of the present disclosure.

[0119] In an example embodiment of the present disclosure, the integrated circuit is applied to an ultra-wideband system chip.

[0120] 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, etc. 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) signals generated by the chip can be transmitted to an external antenna through the air cavity waveguide structure formed by the above-mentioned radiator structure and the air waveguide built in the PCB, and then radiated to a target area.

[0121] An electromagnetic wave device is also provided in an example embodiment of the present disclosure, as shown in the accompanying drawings, which comprises a radio frequency module 2011, an analog signal processing module 2012 and a digital signal processing module 2013 connected in sequence, wherein: Figure 12 ​As shown, it comprises: a carrier 4; an integrated circuit 5 as described in any of the embodiments of the present disclosure, arranged on the carrier 4; an antenna 6 arranged on the carrier 4, 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 with 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. Wherein the carrier can be a printed circuit board (PCB), and the integrated circuit and the antenna are connected through PCB wiring.

[0122] It should be noted that the electromagnetic wave device can realize functions such as target detection and / or communication by transmitting and receiving electromagnetic wave signals, to provide detection target information and / or communication information to the device body, thereby assisting or even controlling the operation of the device body. The present disclosure also provides a terminal device, such as Figure 8 As shown, it comprises: a device body; and an electromagnetic wave device as described in any of the embodiments 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 the operation of the device body.

[0123] Specifically, 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, which can be determined as appropriate.

[0124] In one optional embodiment, the above-mentioned device body can be a component and product applied in 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 various instruments for detecting vital sign parameters and various devices carrying the instruments, such as in-cabin vital sign detection of a car, indoor personnel monitoring, smart medical devices, consumer electronic devices, car digital key, mouse, etc.

[0125] An embodiment of the present disclosure also provides a non-transitory computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the joint demapping and decoding method according to any one of the embodiments of the present disclosure.

[0126] The related technical solutions of the present disclosure will be described in detail below taking UWB as an example:

[0127] In this article, decoding can also be referred to as decoding, and demapping can also be referred to as inverse decoding.

[0128] 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) or 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 nanosecond-level narrow pulses. These narrow pulses have a very wide bandwidth and can carry a large amount of information, and can provide good performance in a multipath environment.

[0129] 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 in each frequency band for selection. Some of these channels support larger bandwidths to achieve higher data transmission rates.

[0130] HRP UWB PHY refers to a high-rate pulse (High Rate Pulse) ultra-wideband (Ultra-Wideband) physical layer. HRP UWB PHY is based on standards such as IEEE 802.15.4a / z, and uses nanosecond-level narrow pulses 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, insensitivity to channel fading, low interception ability, high positioning accuracy, etc. It is particularly suitable for high-speed wireless access and accurate positioning in dense multipath places such as indoor places.

[0131] In addition, HRP UWB PHY also supports higher pulse repetition frequency to achieve higher data transmission rate. At the same time, in order to enhance the security of the ranging device, STS (Scrambled Time Stamp Sequence) and other technologies are introduced.

[0132] In the IEEE 802.15.4z standard, two modes, BPRF (Base pulse repetition frequency) and HPRF (Higher pulse repetition frequency), are also defined for HRP-ERDEV (Enhanced Ranging Device).

[0133] In UWB communication, especially in HRP (High Rate Pulse) UWB mode, BPM-BPSK or BPSK modulation strategies can be used to transmit the encoded bit sequence. BPM (Binary (burst) Position Modulation) is a position modulation method, where information is represented by the position of the burst, i.e. the position of each pulse can correspond to a specific data symbol or bit combination. BPSK (Binary Phase-shift Keying) is a phase modulation method, where 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).

[0134] 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. 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. At the same time, the performance of the system will be affected by channel conditions, noise interference and other factors.

[0135] In UWB technology, modulation constellation is a graphical representation of the positions of different modulation symbols in the signal space. Each constellation point corresponds to a specific symbol, which is represented by a certain number of bits.

[0136] 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.

[0137] In UWB communications, the modulation constellations used are not Gray coded, so that adjacent constellation points can differ in more than one bit. This typically increases the error rate of the raw bits in the communication. That is, if the modulation constellation is not Gray, i.e. "non-Gray", then adjacent constellation points can differ in more than one bit. This means that when a misjudgment occurs, more than one bit can be in error, increasing the severity of the error.

[0138] For a communication device using a BPM-BPSK joint modulation, the modulation constellation is non-Gray. 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.

[0139] 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 is non-Gray. This means that adjacent constellation points can differ in more than one bit. This typically increases the error rate of the raw bits in the decoding, because the difference between adjacent symbols is large. At the same time, HRP-ERDEV devices in HRP mode, when using convolutional codes with a constraint length of 3, the modulation mapping is also non-Gray, which also increases the error rate of subsequent decoding.

[0140] 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 the decoding performance. However, for the above modulation (non-Gray) - 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, so it cannot meet the current requirements of high-precision information transmission.

[0141] In some optional embodiments of the present disclosure, a joint demapping and decoding method is proposed, as shown in Figure 14 includes: step 210, obtaining a non-gray format modulation constellation, that is, obtaining a received symbol including a plurality of components, each component of the received symbol being jointly determined by a plurality of encoded bits participating in symbol mapping; and step 220, decoding based on the correlation between mapped symbols.

[0142] In one example of the present embodiment, the decoding based on the correlation between mapped symbols includes: decoding based on the level of correlation between mapped symbols to calculate the posterior probability.

[0143] The method of the above-mentioned embodiments of the present disclosure can be applied to the UWB PHY layer, and by effectively utilizing the correlation between symbols introduced by non-gray symbol mapping, better performance than LLR-based decoding can be achieved without increasing complexity. That is, by joint operation of demapping and decoding, the accuracy of decoding can be improved without increasing the complexity of the system, thereby enhancing the reliability of the communication system.

[0144] Specifically, for the BPM-BPSK modulation model, let b represent the convolutional encoded bit, let x represent the modulated symbol, and let y represent the received symbol. The corresponding convolutional encoded pair (b0, b1) is non-grayly mapped to the modulated symbol pair (x0, x1). The specific mapping relationship can be referred to in Table 1 below (where the power of each symbol is a unit power):

[0145] (b0, b1) [(x0, x1)] (0，0) (1，0) (0，1) (-1，0) (1，0) (0，1) (1，1) (0，-1)

[0146] Table 1

[0147] The constellation diagram corresponding to the above-mentioned Table 1 can be referred to in Figure 10a As shown in the Gray code constellation diagram shown in Figure 10b As shown in the Gray code constellation diagram shown in Figure 10a The non-gray code constellation diagram in the

[0148] It should be noted that the modulated symbol pair (x0, x1) is jointly determined by the corresponding convolutional encoded pair (b0, b1), rather than being mapped from (b0) to (x0) and (b1) to (x1) separately.

[0149] For the Additive White Gaussian Noise (AWGN) channel, the corresponding received symbol pair (y0, y1) is y0=x0+n0, y1=x1+n1. Where the Energy per bit (Epb) is 1 / 2, i.e. the sum of the energy of two bits is 1; n0, n1 are noise samples, which are i.i.d. Gaussian with variance 2 . .

[0150] 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). Since the mapping is non-gray, it means that adjacent symbols may differ in multiple bits. At the same time, if the mapped modulation symbol is sent through an additive white Gaussian noise channel, noise will be added at the receiving end, that is, the received symbol pair (y0, y1) is the sum of 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, after the new research based on this model in the embodiment of the disclosure, another demodulation method is proposed, which can be specifically:

[0151] 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. Since the LLR value can be used as a measure of the possibility of each coded bit being "0" or "1", i.e. 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.

[0152] Specifically, the expression of the above LLR can be:

[0153] L i = log Pr(b i = 0 | y0y1) - log Pr(b i = 1 | y0y1), i = 0, 1

[0154] Based on the above formula, by using Bayes rule and the equally probable input assumption, it can be further obtained that:

[0155] L i = log Pr(y0y1|b i = 0) - log Pr(y0y1|b i = 1) = 1

[0156] Therefore, for the BPM-BPSK joint modulation mode, based on the definition of conditional probability and i.i.d. Gaussian noise, it can be obtained that:

[0157]

[0158]

[0159] 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".

[0160] That is, for the 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 value of the coded bit 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.

[0161] In addition, in some optional embodiments, by using max-log approximation, the calculation of LLR can be greatly simplified without sacrificing performance. The formula of max-log approximation is:

[0162] log(exp(x) + exp(y)) ≈ max(x, y)

[0163] That is, for the BPM-BPSK joint modulation mode, based on the formula of the above LLR value L i , it can be simplified as:

[0164]

[0165] However, this LLR calculation method can cause information loss, and based on L0, L1 cannot recover the original information, i.e., corresponding y0, y1.

[0166] Specifically, the values L0, L1 of the above LLR are used as inputs of a Viterbi decoder to perform convolutional decoding, and the architecture is as shown in Figure 3 As shown in the figure, in the decoding process of a communication system, LLR can be used to help extract the original information (i.e., the information sent during transmission) from the received signal. When LLR is obtained in a conventional manner, it can involve complex operation processing. In the embodiments of the present disclosure, a maximum likelihood approximation method is provided, which greatly simplifies the operation processing 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.

[0167] As shown in Figure 11 In the process of Viterbi decoding, each state transition on the trellis is associated with an information bit and the corresponding encoded bits.

[0168] Branch metric (BM) can be used to measure the value of the likelihood of a state transition from a certain state to another state at a certain time. In a communication system, BM can be used as a measurement standard to measure the difference between the received signal and each possible transmitted signal. Therefore, it is conventional to use branch metric (BM) to measure the likelihood of a state transition in the above HRP UWB, which can be generally 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 branch metric γ can be:

[0169] γ = (1-2b0) · L0 + (1-2b1) · L1

[0170] 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 being simply combined by b0 mapping to x0 and b1 mapping to x1 separately to obtain the modulation symbol pair (x0, x1).

[0171] In some optional embodiments of the present disclosure, a joint demapping and decoding method is also provided, as shown in the formula (1), comprising the steps of: Figure 15 As shown in the formula (1), the method comprises the steps of: step 310, obtaining a non-Golay format modulation map; and step 320, performing decoding in a maximum log approximation manner.

[0172] In an example of the present embodiment, in scenarios such as reducing bit error rate by using a non-Golay format to enhance the correlation between modulation map symbol keys, etc., a map modulated by a UWB device using BPM-BPSK joint modulation can be obtained first, that is, the non-Golay format modulation map can be a map modulated by a UWB device using BPM-BPSK joint modulation; or, for an HRP-ERDEV device in HPRF mode, the non-Golay format modulation map is a mapping map modulated when a convolutional code with a constraint length of 3 is used.

[0173] In an example of the present embodiment, decoding is performed based on the branch metric obtained by the symbol pair.

[0174] In an example of the present embodiment, the likelihood value of each value of the symbol is calculated by the following formula:

[0175] γ 00 = y0, γ 01 = -y0, γ 10 = y1, γ 11 = -y1

[0176] Alternatively, the likelihood value of each value of the symbol is calculated by the following formula:

[0177] γ 00 = y0+y1, γ 01 = -y0-y1, γ 10 = -y0+y1, γ 11 = y0-y1

[0178] Wherein, γ 00 represents the likelihood value of the symbol value being 00, γ 01 represents the likelihood value of the symbol value being 01, γ 10 represents the likelihood value of the symbol value being 10, and γ 11denotes the likelihood value of the symbol taking value 1, y0is the first component of the received symbol, and y1is the second component of the received symbol.

[0179] The posterior 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 are mapped to one symbol, so calculating the posterior probability at the symbol level preserves more information than calculating the posterior probability at the bit level.

[0180] Specifically, for the BPM-BPSK modulation mode, the branch metric can be set as γ ∝ Pr(b0b1|y0y1), i.e.

[0181]

[0182] For the Viterbi decoding process, since the same constant term and the positive scaling do not affect the results of path selection, the branch metric formula can be simplified as:

[0183] γ 00 ~ -(y0- 1) 2 - y1 2 ~ y0

[0184] γ 01 ~ -(y0+ 1) 2 - y1 2 ~ -y0

[0185] γ 10 ~ -y0 2 -(y1- 1) 2 ~ y1

[0186] γ 11 ~ -y0 2 -(y1+ 1) 2 ~ -y1

[0187] That is, the value of the branch metric can be directly used as the ACS unit (such as the ACS array shown in Figure 5 , compared with the architecture shown in Figure 3 , the Figure 5 in the example shown in Figure 3 does not need to generate the LLR value for the bit, so only the 4 soft information channels for the symbol are needed, i.e., the LLR generator module shown in

[0188] 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-gray code (as shown in Table 2 below).

[0189] The specific mapping relationship can be referred to the following table (where the power of each symbol is unit power):

[0190]

[0191]

[0192] Table 2

[0193] The constellation diagram corresponding to the above table is shown in Figure 12 At this time, the symbol-based branch metric can be calculated based on the following formula:

[0194] γ 00 = y0+ y1

[0195] γ 01 = -y0- y1

[0196] γ 10 = -y0+ y1

[0197] γ 11 = y0- y1

[0198] That is, based on the similar idea as BPM-BPSK, compared with the decoding method of LLT, the scheme in the embodiment improves the decoding performance by using symbol-based branch metric without increasing the calculation complexity, thereby effectively improving the decoding efficiency and reducing the system complexity.

[0199] No matter from the decoding accuracy and / or block-error-rate and other performance indicators, compared with the traditional scheme, the performance indicators achieved by the technical scheme recorded in the embodiment of the disclosure are effectively improved. For example, referring to Figure 13As shown in the performance comparison chart, when transmitting 20 bytes of payload data through an additive white Gaussian noise (AWGN) channel and using Reed-Solomon (RS) encoding / decoding technology to improve data transmission reliability, the technical solution proposed in the embodiment of the present disclosure (curve 1) can significantly improve the communication performance compared with the traditional scheme (curve 2), that is, the performance advantage of the present scheme can be clearly shown by comparing curve 1 with curve 2. Curve 4 is a reference, and the corresponding modulation mode is the system performance when 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 of 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.

[0200] It should be noted that the scheme described in the embodiment 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 coding modulation systems that use Viterbi decoding as a channel decoding scheme, as long as the code rate and modulation order meet the preset conditions, for example:

[0201] 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.

[0202] When one state transition produces multiple modulation symbols in the MCS scheme, the branch metric can be set to be equal to the sum of Euclidean distances to the target constellation points.

[0203] 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 the Euclidean distances of each group is calculated; or, multiple stages can be processed at one time when the Trellis is forward-passing (similar to Radix-4 Viterbi decoder).

[0204] 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 as the sum of the 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 the 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 Radix-4 Viterbi decoder.

[0205] 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).

[0206] 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 a 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 a 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 a 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: 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); and the likelihood value of each value of the symbol is calculated by the following formula:

4. The method of claim 3, wherein: 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. 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 a 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: 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); and the likelihood value of each value of the symbol is calculated by the following formula:

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, a constraint length of a convolutional code is equal to 3, and each two coded bits are mapped to a symbol. 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.

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. The decoding based on the correlation between the mapped symbols comprises decoding based on a level of the correlation between the mapped symbols.

10. A method of joint demapping and decoding, comprising:

9. The method of claim 8, wherein, 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 pattern of the non-Golay format is a pattern modulated by a UWB device using BPM-BPSK joint modulation; or For the HRP-ERDEV device in the HPRF mode, the modulation pattern of the non-Golay format is a mapping pattern modulated when a convolution code with a constraint length of 3 is used.

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, characterized in that, 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, from an input end, a received symbol comprising a plurality of components, 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 convolution code with a code rate of 0.

5.

17. An integrated circuit, comprising: The radio frequency module, the analog signal processing module, and the digital signal processing module are 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. The integrated circuit is applied to an ultra-wideband system chip.

18. The integrated circuit of claim 17, wherein, The integrated circuit comprises:

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

20. A terminal device, comprising: a device body; and the electromagnetic wave device of claim 19 disposed on the device body; The electromagnetic wave device is configured to perform target detection and / or communication to provide reference information for the operation of the device body. The computer program is executed by the processor to implement the joint demapping and decoding method of any one of claims 1-13.

21. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, 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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