WO2018014733A1 - 一种适用于OvXDM***译码方法、装置及OvXDM*** - Google Patents

一种适用于OvXDM***译码方法、装置及OvXDM*** Download PDF

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Publication number
WO2018014733A1
WO2018014733A1 PCT/CN2017/091961 CN2017091961W WO2018014733A1 WO 2018014733 A1 WO2018014733 A1 WO 2018014733A1 CN 2017091961 W CN2017091961 W CN 2017091961W WO 2018014733 A1 WO2018014733 A1 WO 2018014733A1
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node
measure
branch
decoding
ovxdm
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PCT/CN2017/091961
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English (en)
French (fr)
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刘若鹏
季春霖
徐兴安
张莎莎
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深圳超级数据链技术有限公司
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Priority to KR1020197005107A priority Critical patent/KR102204320B1/ko
Priority to EP17830367.3A priority patent/EP3490176A4/en
Priority to JP2019503454A priority patent/JP6723429B2/ja
Publication of WO2018014733A1 publication Critical patent/WO2018014733A1/zh
Priority to US16/254,557 priority patent/US20190238254A1/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J99/00—Subject matter not provided for in other groups of this subclass
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0052—Realisations of complexity reduction techniques, e.g. pipelining or use of look-up tables
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0059—Convolutional codes
    • H04L1/006—Trellis-coded modulation

Definitions

  • the present application relates to the field of signal processing, and in particular, to a decoding method and apparatus applicable to an OvXDM system, and an OvXDM system.
  • overlapping multiplex systems whether it is Overlapped Time Division Multiplexing (OvTDM), Overlapped Frequency Division Multiplexing (OvFDM), or Overlapped Code Division Multiplexing (OvCDM) System, overlapping space division multiplexing (OvSDM, Overlapped Space Division Multiplexing) system, Overlapped Hybrid Multiplexing (OvHDM) system, etc., when decoding, it is necessary to continuously access the corresponding grid pattern of the system.
  • the nodes in (Trellis) and set up two memories for each node, one for storing the relative best path to the node and one for storing the measure corresponding to the relatively best path to the node.
  • the conventional method In calculating the above-mentioned measure corresponding to the relatively optimal path to the node, the conventional method generally obtains the current time by adding the accumulated branch measure of the node at the previous moment to the instantaneous branch measure of the node at the current time. Accumulate the branch measure. Although the accumulative branch measure of such a node has wide applicability, when decoding an overlapping multiplex system, it is often necessary to traverse all state nodes and their extended paths as described above to obtain a more accurate decoding result. .
  • the present application provides a decoding method, apparatus, and OvXDM system suitable for an OvXDM system.
  • the present application provides a decoding method suitable for an OvXDM system, comprising the following steps:
  • the accumulated branch measure of any node is calculated by the following steps:
  • the average branch measure of the current time node is added to the accumulated branch measure of the previous time node to obtain the accumulated branch measure of the current time node.
  • the accumulated branch measure of the previous time node is first multiplied by a weighting factor.
  • the present application provides a decoding apparatus suitable for an OvXDM system, including:
  • a node accumulating branch measure calculation module for calculating a cumulative branch measure of the node
  • a decoding module configured to decode according to the calculated accumulated branch measure
  • the node cumulative branch measure calculation module includes:
  • An extension module configured to extend L nodes backwards to a node at a previous time to obtain all branches of the segment data stream of length L, where L is an integer greater than one;
  • a first calculating module configured to separately calculate measures of each branch of the segmented data stream of length L, to obtain a segment path measure of each branch;
  • a comparison module configured to compare the segment path measures of the branches to select a minimum measure
  • An average branch measure calculation module configured to divide the minimum measure by L to obtain an average branch measure of a node at a current time
  • the adding module is configured to add the average branch measure of the current time node to the accumulated branch measure of the node at the previous time to obtain the accumulated branch measure of the current time node.
  • the decoding device for applying the segment path measure further comprises a weighting factor module, configured to: when the adding module adds the average branch measure of the current time node to the accumulated branch measure of the node at the previous time, Multiply the accumulated branch measure of the node at the previous moment by a weighting factor.
  • a weighting factor module configured to: when the adding module adds the average branch measure of the current time node to the accumulated branch measure of the node at the previous time, Multiply the accumulated branch measure of the node at the previous moment by a weighting factor.
  • the present application provides an OvXDM system comprising the above-described decoding apparatus applying a segment path measure.
  • the average branch measure of the current time node is added to the accumulated branch measure of the node at the previous time to obtain the accumulated branch measure of the current time node. Therefore, the information of the accumulated branch measure of the current node includes not only the branch measure information before the current node, but also certain information of the branch measure after the current node, which makes the accumulated branch measure of the current node more
  • the reference makes the decoding reliability higher, and the selected decoding path is more accurate and reliable.
  • the application improves the calculation of the accumulated branch measure of the node, it is not necessary to traverse all the state nodes as in the conventional method. And its extension path, Very accurate decoding results can also be obtained.
  • FIG. 1 is a schematic flowchart of a decoding method applicable to an OvXDM system according to an embodiment of the present application
  • FIG. 2 is a schematic flowchart of an accumulated branch measure of a computing node in a decoding method applicable to an OvXDM system according to an embodiment of the present application;
  • FIG. 3 is a schematic structural diagram of a decoding apparatus applicable to an OvXDM system according to an embodiment of the present application
  • FIG. 4 is a schematic structural diagram of a node accumulation branch measurement calculation module in a decoding apparatus applicable to an OvXDM system according to an embodiment of the present application;
  • FIG. 5 is a schematic structural diagram of a transmitting end of an OvFDM system in the prior art
  • FIG. 6 is a schematic diagram of symbolic code superposition of an OvFDM system in the prior art
  • FIG. 7(a) is a block diagram of signal reception at the receiving end of the OvFDM system in the prior art
  • Figure 7 (b) is a block diagram of the received signal detection at the receiving end of the OvFDM system
  • FIG. 11 is a schematic diagram of a decoding path of an OvFDM system in the first embodiment
  • FIG. 12 is a schematic structural diagram of a transmitting end of an OvTDM system in the prior art
  • FIG. 13 is a schematic diagram of symbol encoding superposition of an OvTDM system in the prior art
  • FIG. 14(a) is a schematic diagram of a preprocessing unit at a receiving end of an OvTDM system in the prior art
  • Figure 14 (b) is a schematic diagram of a sequence detecting unit at the receiving end of the OvTDM system
  • 15 is a code tree diagram of an input-output relationship of an OvTDM system when the number of overlap multiplexing times is 3 in the prior art;
  • 16 is a node state transition diagram of an OvTDM system in the prior art when the number of overlapping multiplexing times is three;
  • 17 is a trellis diagram corresponding to an OvTDM system in the prior art when the number of overlapping multiplexing times is three;
  • FIG. 18 is a schematic diagram of a decoding path of an OvTDM system in a second embodiment
  • 21 is a coding matrix diagram of an OvCDM system in the prior art
  • 22 is a schematic structural diagram of a decoder of an OvCDM system in the prior art
  • FIG. 23 is a cell diagram corresponding to an OvCDM system in a third embodiment of the present application.
  • FIG. 24 is a schematic diagram of a decoding path of an OvCDM system in a third embodiment of the present application.
  • the present application discloses a decoding method suitable for an OvXDM system.
  • the OvXDM system is an OvTDM system, an OvFDM system, an OvCDM system, an OvSDM system, or an OvHDM system.
  • the Euclidean distance is the true distance between the two signals. It can truly reflect the distance between the actual signal and the ideal signal. In this patent, the Euclidean distance is defined as
  • the decoding method applicable to the OvXDM system of the present application includes steps S100 and S300, which are specifically described below.
  • Step S100 Calculate the accumulated branch measure of the node. As shown in FIG. 2, in an embodiment, the accumulated branch measure of any node passes through steps S101-S109, that is, step S100 includes steps S101-S1109.
  • the branch length L is less than or equal to the number of overlapping multiplexing times of the system, and when the branch length L is equal to the number of overlapping multiplexing times of the system, decoding is performed at this time.
  • the performance is the best; when the OvXDM system is an OvCDM system, the branch length L is less than or equal to the number of coding branches of the system.
  • the branch length L is equal to the number of coding branches of the system, the decoding performance is best.
  • step S103 Calculate the measures of each branch of the segment data stream of length L, respectively, to obtain a segment path measure of each branch.
  • the measure of the M L-1 extended branches corresponding to each arriving node of the segmented data stream of length L in step S101 is calculated as the segment path measure of each branch, including M arrivals.
  • M is the dimension of the system, and takes an integer greater than or equal to 2.
  • S105 Compare the segment path measures of the branches to select a minimum measure.
  • the segment path measure of each of the M L-1 branches of the arriving node in step S103 is compared, and the minimum measure is selected as the minimum measure corresponding to the arriving node, and a total of M minimum measures are obtained, and M is a system.
  • the dimension of the dimension which is an integer greater than or equal to 2.
  • S107 Divide the minimum measure by L to obtain an average branch measure of the current moment node. In other words, it is to find the average branch measure of each corresponding node to the corresponding path, including M average branch measures.
  • S109 Add the average branch measure of the current time node to the accumulated branch measure of the node at the previous time to obtain the accumulated branch measure of the current time node.
  • the accumulated branch measure at the current time is obtained by adding the instantaneous branch measure of the current time node to the accumulated branch measure of the node at the previous time, and the instantaneous branch measure of the current time node is the previous one. The measure of the length of the branch from the time node to the current time node.
  • the average branch measure is used instead of the instantaneous branch measure, so that the information of the accumulated branch measure of the current node includes not only the branch measure information before the current node, but also The certain information of the branch measure after the current node is included, which makes the accumulated branch measure of the current node more reference, so that the decoding reliability performed in step S300 is higher, and the selected decoding path is more accurate and reliable.
  • the initial time node does not have a previous time node, when calculating the accumulated branch measure of the node at the initial time, it is the average branch measure of the node at the initial time, that is, the accumulated branch measure of the node at the initial time.
  • the data frame length is N
  • the decoding depth reaches NL
  • the last L symbols can be used as the decoding output by the path corresponding to the selected minimum measure.
  • step S109 when the average branch measure of the current time node is added to the accumulated branch measure of the node at the previous time, the accumulated branch measure of the previous time node is multiplied by a weighting factor. Then, the accumulated branch measure multiplied by the weighting factor is added to the accumulated branch measure of the previous moment node to obtain the accumulated branch measure of the current time node.
  • the purpose of introducing the weighting factor is to make the node farther away from the current time node, and the measure has less influence on the measurement of the node at the current time.
  • the weighting factor is determined by the flat fading width of the system. In one embodiment, the weighting factor has a value ranging from greater than or equal to 0.9 and less than or equal to one.
  • Step S300 performing decoding according to the calculated accumulated branch measure.
  • the decoding rule in step S300 includes starting from the node at the initial time, and the node that selects the minimum accumulated branch measure is expanded each time.
  • the decoding rule in step S300 may also be an existing decoding rule, or a decoding rule that may appear in the future. As long as the decoding rule needs to use the measure of the node, the improved node in the present application may be applied.
  • the cumulative branch measure is a decoding rule that may appear in the future.
  • step S109 obtains M accumulated branch metrics, that is, corresponding to M arriving nodes.
  • the M accumulated branch measures are compared, and the arrival state node corresponding to the least measure is selected, and the node expansion and path selection are performed according to the above method. Repeat the above steps. From the nth step, only the first r n arrival nodes and their accumulated branch measures are retained. r n is determined by the performance loss tolerated by the system, and the path with larger average branch measure and its measurement are all discarded.
  • the present application also discloses a decoding device suitable for the OvXDM system.
  • the decoding device suitable for the OvXDM system is particularly suitable for the OvXDM system.
  • the OvXDM system is an OvTDM system, an OvFDM system, OvCDM system, OvSDM system or OvHDM system.
  • the decoding apparatus applicable to the OvXDM system of the present application includes a node accumulation branch measurement calculation module 100 and a decoding module 300, which are specifically described below.
  • the node accumulation branch measure calculation module 100 is configured to calculate the accumulated branch measure of the node.
  • the node accumulation branch measure calculation module 100 includes an expansion module 101, a first calculation module 103, a comparison module 105, an average branch measurement calculation module 107, and an addition module 109, which are preferred.
  • a weighting factor module 111 may also be included.
  • the extension module 101 is configured to extend the L nodes backwards to the node at the previous time to obtain all the branches of the segment data stream of length L, where L is an integer greater than 1.
  • L is an integer greater than 1.
  • the branch length L is less than or equal to the number of overlapping multiplexing of the system; when the OvXDM system is an OvCDM system, the branch length L is less than or equal to the coding branch of the system. Number of roads.
  • the first calculation module 103 is configured to separately calculate the measures of the branches of the segment data stream of length L to obtain the segment path measure of each branch.
  • the comparison module 105 is configured to compare the segment path measures of the branches to select a minimum measure.
  • the average branch measure calculation module 107 is configured to divide the above minimum measure by L to obtain an average branch measure of the current time node.
  • the adding module 109 is configured to add the average branch measure of the current time node to the accumulated branch measure of the previous time node to obtain the accumulated branch measure of the current time node.
  • the weighting factor module 111 is configured to multiply the accumulated branch measure of the previous time node by a weighting factor when the average branch measure of the node at the current time is added to the accumulated branch measure of the node at the previous time.
  • the weighting factor is determined by the flat fading width of the system. In one embodiment, the weighting factor has a value ranging from greater than or equal to 0.9 and less than or equal to one. The purpose of introducing the weighting factor is to make the node more distant from the current time, and the measure has less influence on the measurement of the current time node.
  • the decoding module 300 is configured to perform decoding according to the calculated accumulated branch measure.
  • the decoding module 300 includes a minimum accumulated branch measure expansion module, and the minimum accumulated branch measure expansion module is configured to start from the node at the initial time, and select the node of the minimum accumulated branch measure to expand each time.
  • the present application also discloses an OvXDM system, which includes the decoding device for applying the segment path measure of the present application.
  • the OvXDM system disclosed in the present application is an OvTDM system, an OvFDM system, an OvCDM system, an OvSDM system or OvHDM system.
  • This embodiment may be described by taking an OvFDM system as an example.
  • the transmitting end of the OvFDM system first encodes the frequency domain signal according to a certain rule, and then converts the frequency domain signal into a time domain signal, that is, inverse Fourier transform, and then the signal is obtained. Send it out.
  • an initial envelope waveform is first generated according to the design parameter; then the initial envelope waveform is shifted in a frequency domain according to a predetermined spectral interval according to the number of overlapping multiplexing, to obtain an envelope waveform of each subcarrier; The data sequence is multiplied by the corresponding subcarrier envelope waveform to obtain a modulation envelope waveform of each subcarrier; and the modulation envelope waveform of each subcarrier is superposed on the frequency domain to obtain a complex modulation envelope in the frequency domain.
  • FIG. 6 it is a schematic diagram of a superimposition process in which the modulation envelope waveform of each subcarrier is superimposed on the frequency domain in the above process.
  • the receiving end of the OvFDM system in the prior art the signal received by the antenna is a signal in the time domain.
  • the time domain signal needs to be first converted into a frequency domain signal, that is, It can only be processed after the Fourier transform. Specifically, symbol synchronization is first formed on the received signal in the time domain; then the received signal of each symbol time interval is sampled and quantized to become a received digital signal sequence; the time domain signal is converted into a frequency domain signal, and then The frequency domain signal is segmented by the spectral interval ⁇ B to form an actual received signal segmentation spectrum; and a one-to-one correspondence between the received signal spectrum and the transmitted data symbol sequence is formed, and finally, the data is detected according to the one-to-one correspondence relationship.
  • Symbol sequence For the specific decoding process, refer to FIG. 8, FIG. 9, and FIG. 10.
  • the system symbols of the OvFDM system have interrelated characteristics, but the conventional decoding method does not fully utilize this point.
  • This application is applicable to the OvFDM system in the prior art.
  • One of the improvements is that the method of calculating the accumulated branch measure of the node in the system decoding process is improved, and the average branch measure is used instead of the instantaneous branch measure, so that the information of the accumulated branch measure of the current node includes not only the current node.
  • the previous branch measurement information also includes certain information of the branch measure after the current node, which makes the accumulated branch measure of the current node more reference, so that the selected decoding path is more accurate and reliable.
  • the decoding rules of the traditional OvFDM system generally use Viterbi decoding.
  • the number of nodes determines the decoding.
  • Complexity and for a system with an overlap number of K and a modulation dimension of M (M is an integer greater than or equal to 2), the number of nodes in the steady state in the corresponding trellis diagram is M K-1 , so the decoding complexity will The index increases with the number of overlaps K.
  • the spectral efficiency of the system is 2K/symbol, so the larger the number of overlaps K, the higher the spectral efficiency.
  • the requirement of improving the spectral efficiency is such that the larger the number of overlaps K is, the better, and on the other hand, the smaller the number of times of overlap K is, the better, in order to reduce the decoding complexity, in particular, when the number of overlaps K is increased to a certain extent.
  • the value for example, if K is greater than 8, the decoding complexity increases sharply.
  • the existing decoding method is difficult to meet the requirements of real-time decoding, and the spectral efficiency, decoding complexity and decoding efficiency form a contradiction requirement.
  • the branch length L is equal to the overlap multiplexing number K, and the same effect as the complex Viterbi algorithm can be achieved.
  • the decoding rules used in the present application do not need to traverse all state nodes and their extended paths like the Viterbi algorithm, and only need to start from the node at the initial time, and select the node with the smallest accumulated branch measure to expand each time. Therefore, the decoding complexity can be greatly reduced, and the decoding efficiency can be improved.
  • the decoding complexity does not increase sharply with the increase of the number of overlapping multiplexing K as in the conventional decoding scheme, and the spectrum efficiency and decoding are solved. The contradiction between complexity and decoding efficiency.
  • the symbol data stream received by the system receiver is: y 0 , y 1 , ..., y L-1 , y L , ..., y N
  • the symbol data sent by the system sender is: u 0 , u 1 ,..., u L-1 , u L ,..., u N
  • L is the segment path length, that is, the extended branch length described above
  • N is the frame data length
  • the number of overlapping multiplexing is K
  • L is less than or equal to K
  • L K is the optimal algorithm, and its performance is completely consistent with the viterbi algorithm.
  • each node When a node is transferred in the corresponding grid pattern of the system, each node will be transferred to the next two nodes, where the transferred upper node represents the arrival node when the new input data is +1, and the lower node represents the new input data-1. Arrival nodes, we will call them the origin, the first node, the second node, etc. according to the position of the nodes in the trellis diagram.
  • the connection between adjacent nodes is the branch, and the branches are connected to form a complete polyline, which is the final decoding path.
  • L is the segment path length
  • L is as large as possible tolerate computational complexity. Because the OvFDM system symbols themselves have interrelated characteristics, the reference method of the segment path measurement is applied by the present application, and the reference between the measures is enhanced, so that the selected decoding path has higher reliability.
  • the path corresponding to the minimum measure is obtained by comparing 2 L-1 branches of length L obtained in (1), and the index j of the minimum measure corresponding to the upper and lower nodes is min + , min - respectively , and then averaged , that is, the average branch measure is obtained, and the average branch measure of the upper node is The average branch measure of the lower node is
  • ⁇ represents the weighting factor and takes the decimal value ⁇ [0.9,1], which is determined by the flat fading width of the system.
  • the meaning is that as the depth of decoding increases, the farther away from the current node, the less the influence of the measure.
  • the cumulative branch measure of 1 and the cumulative branch measure of u i -1.
  • the measure is the cumulative branch measure of the origin.
  • the cumulative branch measure of the upper and lower nodes of u i is obtained by (3), and the size is compared, and the node with smaller measure is selected to perform node expansion, and the segment data stream of length L is also selected from the current node. According to (1) ⁇ (3), node measurement is selected and extended, and one arrival node is added for each expansion.
  • only the first r n arriving nodes and their accumulated branch measures may be retained after extending to a certain node, and r n is determined by the performance loss tolerated by the system, and the path with a larger average branch measure and Its measurement is completely abandoned.
  • the segmentation path when the signal to noise ratio is high, once the measurement of a segment path is much smaller than other segment paths, the segmentation path can be directly extended forward, so that the decoding complexity is further greatly reduced.
  • the remaining data frame symbols are filtered and extended according to the manners (1) to (4), and thus, until the end of the data frame, the path decision output having the minimum average branch measure reaching the node is obtained, and the path is the final decoding. result.
  • the received sequence y i is decoded, and the decoding path thereof is referred to FIG. 11 , and finally the correct decoding result is obtained.
  • This embodiment may be described by taking an OvTDM system as an example.
  • FIG. 13 it is a schematic diagram of a superimposition process in which the modulation envelope waveforms at respective times are superimposed on the time domain and reflected on the symbol code in the above process.
  • FIG. 14 it is in the prior art.
  • the receiving end of the OvTDM system forms a sequence of received digital signals for the received signals in each frame, and then performs detection on the formed sequence of received digital signals to obtain a decision of modulating the modulated data on all symbols within the frame length.
  • the received signal is first synchronized, including carrier synchronization, frame synchronization, symbol time synchronization, etc., and then according to the sampling theorem, the received signal in each frame is digitized, and then the received waveform is sent according to the waveform.
  • the system symbols of the OvTDM system have interrelated characteristics, but the conventional decoding method does not fully utilize this point.
  • This application applies to the OvTDM system in the prior art.
  • One of the improvements is that the method of calculating the accumulated branch measure of the node in the system decoding process is improved, and the average branch measure is used instead of the instantaneous branch measure, so that the information of the accumulated branch measure of the current node includes not only the current node.
  • the previous branch measurement information also includes certain information of the branch measure after the current node, which makes the accumulated branch measure of the current node more reference, so that the selected decoding path is more accurate and reliable.
  • the decoding rules of the traditional OvTDM system generally use Viterbi decoding.
  • the number of nodes determines the decoding.
  • Complexity and for a system with an overlap number of K and a modulation dimension of M (M is an integer greater than or equal to 2), the number of nodes in the steady state in the corresponding trellis diagram is M K-1 , so the decoding complexity will The index increases with the number of overlaps K.
  • the spectral efficiency of the system is 2K/symbol, so the larger the number of overlaps K, the higher the spectral efficiency.
  • the requirement of improving the spectral efficiency is such that the larger the number of overlaps K is, the better, and on the other hand, the smaller the number of times of overlap K is, the better, in order to reduce the decoding complexity, in particular, when the number of overlaps K is increased to a certain extent.
  • the value for example, if K is greater than 8, the decoding complexity increases sharply.
  • the existing decoding method is difficult to meet the requirements of real-time decoding, and the spectral efficiency, decoding complexity and decoding efficiency form a contradiction requirement.
  • the branch length L is equal to the overlap multiplexing number K, and the same effect as the complex Viterbi algorithm can be achieved.
  • the decoding rules used in the present application do not need to traverse all state nodes and their extended paths like the Viterbi algorithm, and only need to start from the node at the initial time, and select the node with the smallest accumulated branch measure to expand each time. Therefore, the decoding complexity can be greatly reduced, and the decoding efficiency can be improved.
  • the decoding complexity does not increase sharply with the increase of the number of overlapping multiplexing K as in the conventional decoding scheme, and the spectrum efficiency and decoding are solved. The contradiction between complexity and decoding efficiency.
  • the symbol data stream received by the system receiver is: y 0 , y 1 , ..., y L-1 , y L , ..., y N
  • the symbol data sent by the system sender is: u 0 , u 1 ,..., u L-1 , u L ,..., u N
  • L is the segment path length, that is, the extended branch length described above
  • N is the frame data length
  • the number of overlapping multiplexing is K
  • L is less than or equal to K
  • L K is the optimal algorithm, and its performance is completely consistent with the viterbi algorithm.
  • each node when the nodes are transferred in the corresponding grid pattern, each node will be transferred to the next two nodes, and the transferred upper node represents the new input data + At 1 o'clock, the arrival node, the lower node represents the arrival node when the new input data -1, we will refer to the node as the origin, the first node, the second node, etc. according to the position of the node in the trellis diagram.
  • the connection between adjacent nodes is the branch, and the branches are connected to form a complete polyline, which is the final decoding path.
  • L is the segment path length
  • L is as large as possible tolerate computational complexity. Because the OvTDM system symbols have interrelated characteristics, the reference method of the segment path measurement is applied by the present application, and the reference between the measures is enhanced, so that the selected decoding path has higher reliability.
  • the path corresponding to the minimum measure is obtained by comparing 2 L-1 branches of length L obtained in (1), and the index j of the minimum measure corresponding to the upper and lower nodes is min + , min - respectively , and then averaged , that is, the average branch measure is obtained, and the average branch measure of the upper node is The average branch measure of the lower node is
  • ⁇ represents the weighting factor and takes the decimal value ⁇ [0.9,1], which is determined by the flat fading width of the system.
  • the meaning is that as the depth of decoding increases, the farther away from the current node, the less the influence of the measure.
  • the cumulative branch measure of 1 and the cumulative branch measure of u i -1.
  • the measure is the cumulative branch measure of the origin.
  • the cumulative branch measure of the upper and lower nodes of u i is obtained by (3), and the size is compared, and the node with smaller measure is selected to perform node expansion, and the segment data stream of length L is also selected from the current node. According to (1) ⁇ (3), node measurement is selected and extended, and one arrival node is added for each expansion.
  • only the first r n arriving nodes and their accumulated branch measures may be retained after extending to a certain node, and r n is determined by the performance loss tolerated by the system, and the path with a larger average branch measure and Its measurement is completely abandoned.
  • the segmentation path when the signal to noise ratio is high, once the measurement of a segment path is much smaller than other segment paths, the segmentation path can be directly extended forward, so that the decoding complexity is further greatly reduced.
  • the remaining data frame symbols are filtered and extended according to the manners (1) to (4), and thus, until the end of the data frame, the path decision output having the minimum average branch measure reaching the node is obtained, and the path is the final decoding. result.
  • the received sequence y i is decoded, and the decoding path thereof is referred to FIG. 18, and finally the correct decoding result is obtained.
  • This example may be described by taking the OvCDM system as an example.
  • the core of the overlapping code division multiplexing of the OvCDM system is overlap and multiplexing, with the aim of improving the spectral efficiency of the communication system.
  • the OvCDM system generalizes the convolutional coding coefficients to the generalized convolutional coding model of the complex domain, and generates the constraint relationship by symbol overlap.
  • the main parameters include the number of coding branches K' and the coding constraint length L'.
  • the system structure diagram is shown in Figure 19.
  • the corresponding encoder structure is shown in FIG.
  • the key of the OvCDM system is the coding matrix, that is, the convolutional expansion coefficient, which is required to satisfy the linear relationship.
  • the input sequence corresponds to the output sequence one by one, so theoretically, there is no error decoding, and generally all the larger-measurement matrix is searched by computer.
  • the coding matrix the coding matrix is arranged as shown in FIG.
  • u i u i, 0 u i, 1 u i, 2 ...
  • u 0 u 0, 0 u 0, 1 u 0 , 2 ...
  • u 1 u 1, 0 u 1, 1 u 1, 2 ....
  • OvCDM code rate Where n is the length of the substream. When n is long, the bit rate loss caused by the tailing of the shift register is negligible, so there is r OVCDM ⁇ k.
  • the traditional binary domain convolutional coding model has a code rate generally less than 1, which leads to loss of spectral efficiency.
  • the convolutional code rate of the complex domain of OvCDM is equal to 1, and the one-way convolutional coding extension does not cause spectral efficiency loss, and additional coding gain is added.
  • the receiving end After receiving the signal, the receiving end synchronizes the signal, estimates the channel, digitizes the data, and then quickly decodes the processed data.
  • the core of the decoding algorithm is to calculate the received signal and the ideal state, and use the path memory and the measure to determine the best decoding path to obtain the final detection sequence.
  • the sequence detection process block diagram is shown in Figure 22.
  • the modulation coding method used by the OvCDM system makes the system symbols of the OvCDM system have interrelated characteristics, the traditional decoding method does not fully utilize this point.
  • This application is one of the improvements of the OvCDM system in the prior art. Therefore, the method for calculating the accumulated branch measure of the node in the system decoding process is improved, and the average branch measure is used instead of the instantaneous branch measure, so that the information of the accumulated branch measure of the current node includes not only the branch before the current node.
  • the road measure information also includes certain information of the branch measure after the current node, which makes the accumulated branch measure of the current node more reference, so that the selected decoding path is more accurate and reliable.
  • the decoding rules of the traditional OvCDM system generally use Viterbi decoding.
  • the number of nodes in the corresponding state in the corresponding trellis diagram is M. K'-1 , so the decoding complexity will increase exponentially with the number of coded paths K'.
  • the number of coding branches K' is required to be as large as possible, so that the spectral efficiency is higher, but at the same time, the decoding complexity increases sharply with the increase of K', so the spectrum efficiency and decoding complexity, The decoding efficiency creates a pair of contradictory requirements.
  • the branch length L is equal to the number of coded branches K', and the same effect as the complex Viterbi algorithm can be achieved.
  • the decoding rules used in the present application do not need to traverse all state nodes and their extended paths like the Viterbi algorithm, and only need to start from the node at the initial time, and select the node with the smallest accumulated branch measure to expand each time. Therefore, the decoding complexity can be greatly reduced, and the decoding efficiency can be improved.
  • the decoding complexity does not increase sharply with the increase of the number of coding branches K' as in the conventional decoding scheme, and the spectrum efficiency and translation are solved. The contradiction between code complexity and decoding efficiency.
  • L is the segment path length
  • L is as large as possible tolerate computational complexity. Because the OvCDM system symbols have interrelated characteristics, the reference method of the segment path measurement is applied by the present application, and the reference between the measures is enhanced, so that the selected decoding path has higher reliability.
  • the segmented data stream of length L from the node i of the trellis diagram is u i , u i+1 ,..., u i+L , i represents the frame symbol sequence index, and the received symbol data streams y i , y i are respectively calculated.
  • ⁇ represents the weighting factor and takes the decimal value ⁇ [0.9,1], which is determined by the flat fading width of the system.
  • the meaning is that as the depth of decoding increases, the farther away from the current node, the less the influence of the measure.
  • the measure is the cumulative branch measure of the origin.
  • the accumulated branch measure of the current time of each arriving node of u i is obtained by (3), and the size is compared, and the node with smaller measure is selected to perform node expansion, and the segment data of length L is also selected from the current node.
  • the stream is selected and expanded by the node measure according to the methods (1) to (3), and one arrival node is added for each expansion.
  • only the first r n arriving nodes and their accumulated branch measures may be retained after extending to a certain node, and r n is determined by the performance loss tolerated by the system, and the path with a larger average branch measure and Its measurement is completely abandoned.
  • the segmentation path when the signal to noise ratio is high, once the measurement of a segment path is much smaller than other segment paths, the segmentation path can be directly extended forward, so that the decoding complexity is further greatly reduced.
  • the remaining data frame symbols are filtered and extended according to the manners (1) to (4), and thus, until the end of the data frame, the path decision output having the minimum average branch measure reaching the node is obtained, and the path is the final decoding. result.
  • OvCDM Take OvCDM as an example.
  • the lattice diagram of the corresponding OvCDM system under these parameters is shown in Figure 23.
  • u 1 ⁇ +1,-1,-1,-1,+1,+1,-1,-1 ⁇
  • the decoding method, device and OvXDM system applicable to the OvXDM system disclosed in the present application screen the access nodes in the grid map corresponding to the system in the decoding process, and improve the cumulative branch measure calculation method, and combine the weighting factors. To jointly screen the better path, and expand the node with the smallest accumulated branch measure to filter out the best decoding path, and apply this application in the decoding process of the OvXDM system with large number of overlapping multiplexing or large number of encoding branches. It will reduce the system design complexity and calculation, so that the system has a lower bit error rate, and performance is mentioned as an improvement.

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Abstract

本申请公开了一种适用于OvXDM***的译码方法、装置及OvXDM***，在译码过程中对***对应的格状图中访问节点进行筛选，通过改进累加支路测度计算方法，并结合权重因子，来共同筛选较优路径，并对累加支路测度最小的节点进行扩展，筛选出最佳译码路径，在重叠复用次数或编码支路数较大的OvXDM***译码过程中应用本申请，会降低***设计复杂度和计算量，使***具有较低误码率，同时性能提到提升。

Description

一种适用于OvXDM***译码方法、装置及OvXDM*** 技术领域
本申请涉及信号处理领域，具体涉及一种适用于OvXDM***的译码方法、装置及OvXDM***。
背景技术
对于重叠复用***——不管是重叠时分复用(OvTDM，Overlapped Time Division Multiplexing)***、重叠频分复用(OvFDM，Overlapped Frequency Division Multiplexing)***还是重叠码分复用(OvCDM，Overlapped Code Division Multiplexing)***、重叠空分复用(OvSDM，Overlapped Space Division Multiplexing)***、重叠混合复用(OvHDM，Overlapped Hybrid Division Multiplexing)***等，对其进行译码时，都需要不断访问***对应的格状图(Trellis)中的节点，并为每一个节点设置两个存储器，一个用于存储到达该节点的相对最佳路径，一个用于存储到达该节点的相对最佳路径对应的测度。在计算上述的到达该节点的相对最佳路径对应的测度时，传统的方法一般是通过将前一时刻节点的累加支路测度加上当前时刻节点的瞬时支路测度，从而可以得到当前时刻的累加支路测度。这种节点的累加支路测度虽然适用性广，但在对重叠复用***进行译码时，往往需要如上所述一样，遍历所有状态节点及其扩展路径，才能得到一个较准确的译码结果。
发明内容
为解决上述问题，本申请提供一种适用于OvXDM***的译码方法、装置及OvXDM***。
根据本申请的第一方面，本申请提供一种适用于OvXDM***的译码方法，包括以下步骤：
计算节点的累加支路测度；
根据计算得到的累加支路测度进行译码；
其中，任意一节点的累加支路测度通过以下步骤计算：
对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数；
分别计算长度为L的分段数据流各条支路的测度，以得到各支路的分段路径测度；
比较所述各支路的分段路径测度，以选取最小测度；
将所述最小测度除以L，以得到当前时刻节点的平均支路测度；
将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。
较优地，将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子。
根据本申请的第二方面，本申请提供一种适用于OvXDM***的译码装置，包括：
节点累加支路测度计算模块，用于计算节点的累加支路测度；
译码模块，用于根据计算得到的累加支路测度进行译码；
其中，节点累加支路测度计算模块包括：
扩展模块，用于对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数；
第一计算模块，用于分别计算长度为L的分段数据流各条支路的测度，以得到各支路的分段路径测度；
比较模块，用于比较所述各支路的分段路径测度，以选取最小测度；
平均支路测度计算模块，用于将所述最小测度除以L，以得到当前时刻节点的平均支路测度；
加法模块，用于将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。
较优地，所述的应用分段路径测度的译码装置还包括权重因子模块，用于在加法模块将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子。
根据本申请的第三方面，本申请提供一种OvXDM***，包括上述的应用分段路径测度的译码装置。
本申请的有益效果是：
依上述实施的适用于OvXDM***的译码方法、装置及OvXDM***，由于将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度，从而使得当前节点的累加支路测度的信息，不仅包含了当前节点之前的支路测度信息，还包括了当前节点之后的支路测度的一定信息，这使得当前节点的累加支路测度更具参考性，使得译码可靠度更高，筛选出的译码路径更准确和可靠；另外，由于本申请对节点的累加支路测度的计算提出了改进，因而无需像传统做法一样遍历所有状态节点及其扩展路径， 也可以取得很准确的译码结果。
附图说明
图1为本申请一种实施例的适用于OvXDM***的译码方法的流程示意图；
图2为本申请一种实施例的适用于OvXDM***的译码方法中计算节点的累加支路测度的流程示意图；
图3为本申请一种实施例的适用于OvXDM***的译码装置的结构示意图；
图4为本申请一种实施例的适用于OvXDM***的译码装置中的节点累加支路测度计算模块的结构示意图；
图5为现有技术中OvFDM***的发送端的结构示意图；
图6为现有技术中OvFDM***的符号编码叠加的示意图；
图7(a)为现有技术中OvFDM***的接收端的信号接受框图；
图7(b)为OvFDM***的接收端的接收信号检测框图；
图8为现有技术中重叠复用次数为3时OvFDM***的输入-输出关系的码树图；
图9为现有技术中重叠复用次数为3时OvFDM***的节点状态转移图；
图10为现有技术中重叠复用次数为3时OvFDM***对应的格状图；
图11为第一种实施例中OvFDM***的译码路径示意图；
图12为现有技术中OvTDM***的发送端的结构示意图；
图13为现有技术中OvTDM***的符号编码叠加的示意图；
图14(a)为现有技术中OvTDM***的接收端的预处理单元示意图；
图14(b)为OvTDM***的接收端的序列检测单元的示意图；
图15为现有技术中重叠复用次数为3时OvTDM***的输入-输出关系的码树图；
图16为现有技术中重叠复用次数为3时OvTDM***的节点状态转移图；
图17为现有技术中重叠复用次数为3时OvTDM***对应的格状图；
图18为第二种实施例中OvTDM***的译码路径示意图；
图19为现有技术中OvCDM***的结构示意图；
图20为现有技术中OvCDM***的编码器的结构示意图；
图21为现有技术中OvCDM***的编码矩阵图；
图22为现有技术中OvCDM***的译码器的结构示意图；
图23为本申请第三种实施例中OvCDM***对应的格状图；
图24为本申请第三种实施例中OvCDM***的译码路径示意图。
具体实施方式
下面通过具体实施方式结合附图对本申请作进一步详细说明。
本申请公开了一种适用于OvXDM***的译码方法，在一实施例中，OvXDM***为OvTDM***、OvFDM***、OvCDM***、OvSDM***或OvHDM***。
需要说明的是，本申请中的测度表示两个信号之间的距离，定义为：
Figure PCTCN2017091961-appb-000001
当p＝2时即为欧氏距离，欧氏距离是两个信号之间的真实距离，能够真实的反应实际信号和理想信号之间的距离，本专利中欧氏距离定义为
Figure PCTCN2017091961-appb-000002
如图1所示，本申请的适用于OvXDM***的译码方法包括步骤S100和S300，下面具体说明。
步骤S100、计算节点的累加支路测度。如图2所示，在一实施例中，任意一节点的累加支路测度通过步骤S101～S109，即步骤S100包括步骤S101～S1109。
S101、对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数。对于一个M维的***，M为大于或等于2的整数，每个节点扩展后包括M个到达节点，那么对前一时刻节点向后扩展L个节点后，每个到达节点对应ML-1条扩展支路，所有到达节点共计ML条支路。。在一实施例中，当OvXDM***为OvTDM***或OvFDM***时，支路长度L小于或等于***的重叠复用次数，当支路长度L等于***的重叠复用次数时，此时进行译码的性能最好；当OvXDM***为OvCDM***时，支路长度L小于或等于***的编码支路数，当支路长度L等于***的编码支路数，此时进行译码的性能最好。
S103、分别计算长度为L的分段数据流各支路的测度，以得到各支路的分段路径测度。换句话说，就是计算步骤S101中的长度为L的分段数据流的每个到达节点对应的ML-1条扩展支路的测度，作为各支路的分段路径测度，包含M个到达节点，M是***的维数，取值为大于或等于2的整数。
S105、比较所述各支路的分段路径测度，以选取最小测度。换句话说，就是比较步骤S103中的每个到达节点的ML-1条支路的分段路径测度，从中选取最小测度作为对应到达节点的最小测度，共计得到M个最小测度，M是***的维数，取值为大于或等于2的整数。S107、将所述最小测度除以L，以得到当前时 刻节点的平均支路测度。换句话说，就是求得每个到达节点对应路径的平均支路测度，包含M个平均支路测度。
S109、将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。传统译码方案中，当前时刻的累加支路测度是通过将当前时刻节点的瞬时支路测度加上前一时刻节点的累加支路测度，而当前时刻节点的瞬时支路测度，即是前一时刻节点到当前时刻节点这一长度为1的支路的测度。因此，可以看到，本申请在计算时，是将平均支路测度来代替瞬时支路测度，从而使得当前节点的累加支路测度的信息，不仅包含了当前节点之前的支路测度信息，还包括了当前节点之后的支路测度的一定信息，这使得当前节点的累加支路测度更具参考性，使得在步骤S300中进行的译码可靠度更高，筛选出的译码路径更准确和可靠。需要说明的是，由于初始时刻节点并不存在前一时刻节点，因此在计算初始时刻节点的累加支路测度时，其就是初始时刻节点的平均支路测度，即初始时刻节点的累加支路测度等于初始时刻节点的平均支路测度。另外，当计算最后若干个时刻节点的累加支路测度，可能其后面不存在足够长度的支路，即后面即使扩展到最后一个时刻节点，其之间的支路的长度也可能小于L-1，此时，有几个解决方式，例如，假设数据帧长度为N，当译码深度到达N-L时，最后L个符号可通过上述选取最小测度对应的路径作为译码输出。
在较优实施例中，步骤S109在将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子，这样，再将与权重因子相乘过后的累加支路测度与前一时刻节点的累加支路测度相加，以得到当前时刻节点的累加支路测度。引入权重因子的目的，是使得距离当前时刻节点越远的节点，其测度对当前时刻节点的测度影响越小。权重因子由***的平坦衰落宽度来决定，在一实施例中，权重因子的取值范围为大于等于0.9且小于等于1。
步骤S300、根据计算得到的累加支路测度进行译码。在一较优的实施例中，步骤S300中的译码规则包括从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展。当然，步骤S300中的译码规则也可以是现有的译码规则，或未来可能出现的译码规则，只要此译码规则需要使用到节点的测度，就可以适用本申请中的改进的节点的累加支路测度。由于本申请对节点的累加支路测度的计算提出了改进，因而无需像传统做法一样遍历所有状态节点及其扩展路径，也可以取得很准确的译码结果，例如，如上所述，每次只选取最小累加支路测度的节点进行扩展，而不是每次都对所有节点和支路进行扩展并计算测度。 具体地，在一实施例中，步骤S109会得到M个累加支路测度，即对应M个到达节点。对这M个累加支路测度进行比较，从中选取测度最小者对应的到达状态节点，按照如上方法对其节点扩展和路径选取。重复以上步骤，从第n步开始只保留前rn条到达节点及其累加支路测度，rn由***容忍的性能损失决定，将具有较大平均支路测度的路径及其测度全部抛弃。
对应地，本申请还公开了一种适用于OvXDM***的译码装置，这种适用于OvXDM***的译码装置尤其适用于OvXDM***，在一实施例中，OvXDM***为OvTDM***、OvFDM***、OvCDM***、OvSDM***或OvHDM***。
请参照图3，本申请的适用于OvXDM***的译码装置包括节点累加支路测度计算模块100和译码模块300，下面具体说明。
节点累加支路测度计算模块100用于计算节点的累加支路测度。在一实施例中，请参照图4，节点累加支路测度计算模块100包括扩展模块101、第一计算模块103、比较模块105、平均支路测度计算模块107和加法模块109，在一较优实施例中，还可以包括权重因子模块111。
扩展模块101用于对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数。在一实施例中，当OvXDM***为OvTDM***或OvFDM***时，支路长度L小于或等于***的重叠复用次数；当OvXDM***为OvCDM***时，支路长度L小于或等于***的编码支路数。
第一计算模块103用于分别计算长度为L的分段数据流各条支路的测度，以得到各支路的分段路径测度。
比较模块105用于比较所述各支路的分段路径测度，以选取最小测度。
平均支路测度计算模块107用于将上述最小测度除以L，以得到当前时刻节点的平均支路测度。
加法模块109用于将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。
权重因子模块111用于在加法模109块将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子。权重因子由***的平坦衰落宽度来决定，在一实施例中，权重因子的取值范围为大于等于0.9且小于等于1。引入权重因子的目的，是使得距离当前时刻节点越节点，其测度对当前时刻节点的测度影响越小。
译码模块300用于根据计算得到的累加支路测度进行译码。在一实施例中，译码模块300包括最小累加支路测度扩展模块，最小累加支路测度扩展模块用于从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展。
本申请还公开了一种OvXDM***，其包括本申请的应用分段路径测度的译码装置，在一实施例中，本申请公开的OvXDM***为OvTDM***、OvFDM***、OvCDM***、OvSDM***或OvHDM***。
下面再通过若干实施例对本申请进行进一步地说明。
实施例一
本实施例不妨以OvFDM***为例进行说明。
如图5所示，为现有技术中OvFDM***发送端，其首先将频域信号按照一定的规律进行编码，然后将频域信号转换为时域信号即进行傅氏反变换，之后才将信号发送出去。具体地，先根据设计参数生成一个初始包络波形；然后根据重叠复用次数将上述初始包络波形在频域上按预定的频谱间隔进行移位，得到各子载波包络波形；再将输入数据序列与各自对应的子载波包络波形相乘，得到各子载波的调制包络波形；再将各子载波的调制包络波形在频域上进行叠加，得到频域上的复调制包络波形，最后将上述频域上的复调制包络波形变换为时域上的复调制包络波形以发送，其中频谱间隔为子载波频谱间隔△B，其中子载波频谱间隔△B＝B/K，B为所述初始包络波形的带宽，K为重叠复用次数。如图6所示，为上述过程中将各子载波的调制包络波形在频域上进行叠加反映到符号编码上的叠加过程示意图。如图7所示，为现有技术中OvFDM***接收端，其通过天线收到的信号是时域的信号，如果要对接收信号译码，首先需要将时域信号转换为频域信号，即进行傅氏变换之后才能处理。具体地，先对接收信号在时间域形成符号同步；然后对各个符号时间区间的接收信号进行取样、量化，使它变成接收数字信号序列；将时域信号转换为频域信号，再对该频率域信号以频谱间隔△B分段，形成实际接收信号分段频谱；再形成接收信号频谱与发送的数据符号序列之间的一一对应关系，最后根据此种一一对应的关系，检测数据符号序列。具体译码过程可参见图8、图9和图10，图8为重叠复用次数K＝3时的***输入-输出关系的码树图，图9为对应图8中的节点的状态转移图，图10为重叠复用次数K＝3时的***对应的格状(Trellis)图，节点的支路扩展过程可从***对应的格状图中清楚地看出。需要说明的是，OvFDM***中的傅氏反变换和傅氏变换都涉及采样点数的设置，两者的采样点数应保持一致，且取值为2n，n为正整数。
因为OvFDM***所用的重叠复用调制编码方法，使得OvFDM***的***符号间本身就具有相互关联的特性，但传统译码方法并未充分利用好这一点，本申请对现有技术中OvFDM***的改进之一在于，改进了***译码过程中节点的累加支路测度计算方法，将平均支路测度来代替瞬时支路测度，从而使得当前节点的累加支路测度的信息，不仅包含了当前节点之前的支路测度信息，还包括了当前节点之后的支路测度的一定信息，这使得当前节点的累加支路测度更具参考性，使得筛选出的译码路径更准确和可靠。
另外，传统的OvFDM***的译码规则一般采用维特比(Viterbi)译码，对于OvFDM***，由于译码过程中，需要对格状图中每个节点进行扩展，因此节点数决定了译码的复杂度，而对于重叠次数为K和调制维度为M的***(M是大于等于2的整数)，其对应的格状图中稳定状态的节点数为MK-1，因此译码复杂度会随着重叠次数K而指数增加。而在OvFDM***中，***的频谱效率为2K/符号，因此重叠次数K越大频谱效率越高。因此，一方面出于提高频谱效率的要求使得重叠次数K越大越好，另一方面出于降低译码复杂度的要求使得重叠次数K越小越好，特别地，当重叠次数K增加到一定值，例如K大于8后，译码复杂度急剧增加，现有的译码方法难以满足实时译码的要求，频谱效率与译码复杂度、译码效率形成了一对矛盾需求。针对此问题，本实施例中在计算累加支路测度时，令支路长度L等于重叠复用次数K，就可以达到与复杂的维特比算法一样的效果。另外，本申请采用的译码规则，也不需要像维特比算法一样遍历所有状态节点及其扩展路径，只需要从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展，因此可以大幅度降低译码复杂度，并提高译码效率，其译码复杂度并不会像传统译码方案一样随着重叠复用次数K的增加而急剧增加，解决了频谱效率与译码复杂度、译码效率这一对矛盾需求。
下面具体说明。
假设***接收端收到的符号数据流为：y0,y1,…,yL-1,yL,…,yN，***发送端发送的符号数据为：u0,u1,…,uL-1,uL,…,uN，其中L为分段路径长度，即上述的扩展支路长度，N为帧数据长度，重叠复用次数为K，L小于或等于K，当L＝K时就是最优算法，其性能与viterbi算法完全一致。以二元输入数据{+1，-1}为例，即M＝2。在***对应的格状图中节点转移时，每个节点将向其后的两个节点转移，其中转移的上节点表示新输入数据+1时的到达节点，下节点表示新输入数据-1时的到达节点，我们将根据节点在格状图中的位置将他们分别称之为原点，第一节点，第二节点等等。相邻节点之间的连线就是支路，支路相连成完整折线的就是最终译码路径。
(1)计算扩展的长度为L的各支路的测度
公式为：
Figure PCTCN2017091961-appb-000003
其中L为分段路径长度，L≤K。当K很大时，L在可容忍计算复杂度前提下越大越好。因为OvFDM***符号间本身就具有相互关联的特性，通过本申请的应用分段路径测度的译码方法，强化了测度之间的参考性，使得筛选出的译码路径可靠度更高。
从格状图的节点i出发长度为L的分段数据流为ui,ui+1,…,ui+L，i表示帧符号序列索引，从ui到ui+1有两个到达节点，分为上节点ui＝+1和下节点ui＝-1，ui+1到ui+L共计有2L-1种理想序列排序，即ui＝+1的上节点分段数据流ui,ui+1,…,ui+L共计有2L-1种理想序列排序，ui＝-1的下节点分段数据流ui,ui+1,…,ui+L也有2L-1种理想序列排序。
分别计算接收符号数据流yi,yi+1,…,yi+L与上节点的2L-1种序列的分段路径测度
Figure PCTCN2017091961-appb-000004
和与下节点的2L-1种分段路径测度
Figure PCTCN2017091961-appb-000005
(2)计算平均支路测度
平均支路测度公式：
Figure PCTCN2017091961-appb-000006
对(1)中求得的2L-1种长度为L的支路比较得出最小测度对应的路径，上下节点对应的最小测度的索引j分别为min+、min-，再对其求平均，即得到平均支路测度，上节点的平均支路测度为
Figure PCTCN2017091961-appb-000007
下节点的平均支路测度为
Figure PCTCN2017091961-appb-000008
(3)计算累加支路测度
累加支路测度公式：
Figure PCTCN2017091961-appb-000009
α表示权重因子，取值为小数α∈[0.9,1]，由***平坦衰落宽度决定。含义为随着译码深度的增加，距离当前节点越远的节点其测度影响越小。
Figure PCTCN2017091961-appb-000010
表示当前节点的累加支路测度。
Figure PCTCN2017091961-appb-000011
表示当前节点的平均支路测度。
Figure PCTCN2017091961-appb-000012
表示当前节点之前的前一节点的累加支路测度。
由(2)得到ui的上下节点平均支路测度，将ui-1的累加支路测度乘上相应的权重因子，分别与上下节点的平均支路测度相加，分别得到ui＝+1的累加支路测度和ui＝-1的累加支路测度。
当i＝0时，即为原点，也就是初始时刻的节点，此时仅存在平均支路测度，不存在前一节点的累加测度，在计算时，在数学上可以直接令原点的平均支路测度为原点的累加支路测度。
(4)译码规则
由(3)得到ui的上、下节点的累加支路测度，对其进行大小比较，选取测度较小的节点对其进行节点扩展，同样是从当前节点选取长度为L的分段数据流，按照(1)～(3)的方式对其进行节点测度选取和扩展，每扩展一次增加一个到达节点。
在一实施例中，可以在扩展到某一节点后只保留前rn条到达节点及其累加支路测度，rn由***容忍的性能损失决定，将具有较大平均支路测度的路径及其测度全部抛弃。
在一实施例中，当信噪比很高时，一旦某分段路径的测度远小于其它分段路径时，可以直接从该分段路径向前扩展，使译码复杂度进一步大幅度降低。
(5)判决输出
对其余的数据帧符号按照(1)～(4)的方式进行筛选和扩展，如此进行直至数据帧结束，将具有最小平均支路测度到达节点的路径判决输出，此路径即为最终的译码结果。
上述过程，以二维OvFDM***为例，其采用矩形复用窗H＝{1 1 1 1 1}，需要说明的是，本申请的应用分段路径测度的译码方法，也可以适用于各种复用窗函数调制的OvFDM***。不妨令重叠重数K＝5，因此***对应的格状图完全展开后有2K-1＝16个节点，本案例中选取分段路径长度L＝3，rn＝4。发送码序列为xi＝{+1,-1,-1,+1,-1,+1+1,-1,+1,-1}，经过OvFDM***波形复用后，得到接收序列为yi＝{+1,0,-1,0,-1,-1,+1,+1,+1,+1}。按照本实施例的应用分段路径测度的译码方法对接收到的序列yi进行译码，其译码路径请参照图11，最终得到了正确的译码结果。
实施例二
本实施例不妨以OvTDM***为例进行说明。
如图12所示，为现有技术中OvTDM***发送端，先根据设计参数生成一个时域内的初始包络波形；然后根据重叠复用次数将上述初始包络波形在时域上按预定的时间间隔进行移位，得到各个时刻的偏移包络波形；再将输入数据序列与各个时刻的偏移包络波形相乘，得到各个时刻的调制包络波形；再将各个时刻的调制包络波形在时域上进行叠加，得到时域上的复调制包络波形以发送，其中时间间隔为△t，△t＝T/K，T为所述初始包络波形的时域宽度，K为重叠复用次数。如图13所示，为上述过程中将各个时刻的调制包络波形在时域上进行叠加反映到符号编码上的叠加过程示意图。如图14所示，为现有技术中 OvTDM***接收端，其对每一帧内的接收信号形成接收数字信号序列，再对形成的接收数字信号序列实施检测，以得到所述帧长内的调制在全部符号上的调制数据的判决，具体地，先对接收信号进行同步，包括载波同步、帧同步、符号时间同步等，再根据取样定理，对每一帧内的接收信号进行数字化处理，接着对接收到的波形按照波形发送时间间隔切割，之后按照一定的译码算法对切割后的波形进行译码。具体译码过程中参见图15、图16和图17，图15为重叠复用次数K＝3时的***输入-输出关系的码树图，图16为对应图15中的节点的状态转移图，图17为重叠复用次数K＝3时的***对应的格状(Trellis)图，节点的支路扩展过程可从***对应的格状图中清楚地看出。
因为OvTDM***所用的重叠复用调制编码方法，使得OvTDM***的***符号间本身就具有相互关联的特性，但传统译码方法并未充分利用好这一点，本申请对现有技术中OvTDM***的改进之一在于，改进了***译码过程中节点的累加支路测度计算方法，将平均支路测度来代替瞬时支路测度，从而使得当前节点的累加支路测度的信息，不仅包含了当前节点之前的支路测度信息，还包括了当前节点之后的支路测度的一定信息，这使得当前节点的累加支路测度更具参考性，使得筛选出的译码路径更准确和可靠。
另外，传统的OvTDM***的译码规则一般采用维特比(Viterbi)译码，对于OvTDM***，由于译码过程中，需要对格状图中每个节点进行扩展，因此节点数决定了译码的复杂度，而对于重叠次数为K和调制维度为M的***(M是大于等于2的整数)，其对应的格状图中稳定状态的节点数为MK-1，因此译码复杂度会随着重叠次数K而指数增加。而在OvTDM***中，***的频谱效率为2K/符号，因此重叠次数K越大频谱效率越高。因此，一方面出于提高频谱效率的要求使得重叠次数K越大越好，另一方面出于降低译码复杂度的要求使得重叠次数K越小越好，特别地，当重叠次数K增加到一定值，例如K大于8后，译码复杂度急剧增加，现有的译码方法难以满足实时译码的要求，频谱效率与译码复杂度、译码效率形成了一对矛盾需求。针对此问题，本实施例中在计算累加支路测度时，令支路长度L等于重叠复用次数K，就可以达到与复杂的维特比算法一样的效果。另外，本申请采用的译码规则，也不需要像维特比算法一样遍历所有状态节点及其扩展路径，只需要从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展，因此可以大幅度降低译码复杂度，并提高译码效率，其译码复杂度并不会像传统译码方案一样随着重叠复用次数K的增加而急剧增加，解决了频谱效率与译码复杂度、译码效率这一对矛盾需求。
下面具体说明。
假设***接收端收到的符号数据流为：y0,y1,…,yL-1,yL,…,yN，***发送端发送的符号数据为：u0,u1,…,uL-1,uL,…,uN，其中L为分段路径长度，即上述的扩展支路长度，N为帧数据长度，重叠复用次数为K，L小于或等于K，当L＝K时就是最优算法，其性能与viterbi算法完全一致。以二元输入数据{+1，-1}为例，在***对应的格状图中节点转移时，每个节点将向其后的两个节点转移，其中转移的上节点表示新输入数据+1时的到达节点，下节点表示新输入数据-1时的到达节点，我们将根据节点在格状图中的位置将他们分别称之为原点，第一节点，第二节点等等。相邻节点之间的连线就是支路，支路相连成完整折线的就是最终译码路径。
(1)计算扩展的长度为L的各支路的测度
公式为：
Figure PCTCN2017091961-appb-000013
其中L为分段路径长度，L≤K。当K很大时，L在可容忍计算复杂度前提下越大越好。因为OvTDM***符号间本身就具有相互关联的特性，通过本申请的应用分段路径测度的译码方法，强化了测度之间的参考性，使得筛选出的译码路径可靠度更高。
从格状图的节点i出发长度为L的分段数据流为ui,ui+1,…,ui+L，i表示帧符号序列索引，从ui到ui+1有两个到达节点，分为上节点ui＝+1和下节点ui＝-1，ui+1到ui+L共计有2L-1种理想序列排序，即ui＝+1的上节点分段数据流ui,ui+1,…,ui+L共计有2L-1种理想序列排序，ui＝-1的下节点分段数据流ui,ui+1,…,ui+L也有2L-1种理想序列排序。
分别计算接收符号数据流yi,yi+1,…,yi+L与上节点的2L-1种序列的分段路径测度
Figure PCTCN2017091961-appb-000014
和与下节点的2L-1种分段路径测度
Figure PCTCN2017091961-appb-000015
(2)计算平均支路测度
平均支路测度公式：
Figure PCTCN2017091961-appb-000016
对(1)中求得的2L-1种长度为L的支路比较得出最小测度对应的路径，上下节点对应的最小测度的索引j分别为min+、min-，再对其求平均，即得到平均支路测度，上节点的平均支路测度为
Figure PCTCN2017091961-appb-000017
下节点的平均支路测度为
Figure PCTCN2017091961-appb-000018
(3)计算累加支路测度
累加支路测度公式：
Figure PCTCN2017091961-appb-000019
α表示权重因子，取值为小数α∈[0.9,1]，由***平坦衰落宽度决定。含义为随着译码深度的增加，距离当前节点越远的节点其测度影响越小。
Figure PCTCN2017091961-appb-000020
表示当前节点的累加支路测度。
Figure PCTCN2017091961-appb-000021
表示当前节点的平均支路测度。
Figure PCTCN2017091961-appb-000022
表示当前节点之前的前一节点的累加支路测度。
由(2)得到ui的上下节点平均支路测度，将ui-1的累加支路测度乘上相应的权重因子，分别与上下节点的平均支路测度相加，分别得到ui＝+1的累加支路测度和ui＝-1的累加支路测度。
当i＝0时，即为原点，也就是初时时刻的节点，此时仅存在平均支路测度，不存在前一节点的累加测度，在计算时，在数学上可以直接令原点的平均支路测度为原点的累加支路测度。
(4)译码规则
由(3)得到ui的上、下节点的累加支路测度，对其进行大小比较，选取测度较小的节点对其进行节点扩展，同样是从当前节点选取长度为L的分段数据流，按照(1)～(3)的方式对其进行节点测度选取和扩展，每扩展一次增加一个到达节点。
在一实施例中，可以在扩展到某一节点后只保留前rn条到达节点及其累加支路测度，rn由***容忍的性能损失决定，将具有较大平均支路测度的路径及其测度全部抛弃。
在一实施例中，当信噪比很高时，一旦某分段路径的测度远小于其它分段路径时，可以直接从该分段路径向前扩展，使译码复杂度进一步大幅度降低。
(5)判决输出
对其余的数据帧符号按照(1)～(4)的方式进行筛选和扩展，如此进行直至数据帧结束，将具有最小平均支路测度到达节点的路径判决输出，此路径即为最终的译码结果。
上述过程，以二维OvFDM***为例，其采用矩形复用窗H＝{1 1 1 1 1}，需要说明的是，本申请的应用分段路径测度的译码方法，也可以适用于各种复用窗函数调制的OvFDM***。不妨令重叠重数K＝5，因此***对应的格状图完全展开后有2K-1＝16个节点，本案例中选取分段路径长度L＝3，rn＝4。发送码序列为xi＝{+1,-1,-1,+1,-1,+1+1,-1,+1,-1}，经过OvFDM***波形复用后，得到接收序列为yi＝{+1,0,-1,0,-1,-1,+1,+1,+1,+1}。按照本实施例的应用分段路径测度的译码方法对接收到的序列yi进行译码，其译码路径请参照图18，最终得到了正确的译码结果。
实施例三
本实施例不妨以OvCDM***为例进行说明
OvCDM***的重叠码分复用的核心是重叠和复用，目的是提高通信***的频谱效率。OvCDM***将卷积编码系数推广到复数域的广义卷积编码模型，通过符号重叠产生约束关系，主要参数包括编码支路数K’路和编码约束长度L’，其***结构图如图19所示，对应的编码器结构如附图20所示。OvCDM***的关键是编码矩阵，即卷积扩展系数，要求其满足线性关系，此时输入序列与输出序列一一对应，因此理论上可以无误码的解码，一般通过计算机搜索所有测度较大的矩阵作为编码矩阵，其编码矩阵排列如附图21所示。
先给出传统OvCDM***的编码过程。
(1)将待发送数据经过串并转换成为K’路子数据流，第i路上的数据流记为ui＝ui,0ui,1ui,2…。比如K’＝2时，u0＝u0,0u0,1u0,2…，u1＝u1,0u1,1u1,2…。
(2)将每一路数据送入一个移位寄存器进行加权叠加，第i路的加权系数为bi＝bi,0bi,1bi,2…，其为一复向量。
(3)把各路信号相加输出，得到最终OvCDM编码器的输出为c＝c0c1c2…，
Figure PCTCN2017091961-appb-000023
OvCDM的码率为
Figure PCTCN2017091961-appb-000024
其中n为子数据流长度。当n很长时，由移位寄存器拖尾所带来的码率损失可以忽略不计，于是有rOVCDM≈k。
传统的二元域卷积编码模型码率一般小于1，会导致频谱效率损失。而OvCDM的复数域的卷积编码码率等于1，单路的卷积编码扩展不会导致频谱效率损失，还会增加额外的编码增益。
接收端收到信号后，先对信号进行同步、信道估计、数字化处理，再对处理后的数据进行快速译码。译码算法的核心是通过计算接收信号与理想状态的测度，采用路径存储器和测度判决出最佳的译码路径，得到最终的检测序列，序列检测过程框图如附图22所示。
因为OvCDM***所用的调制编码方法，使得OvCDM***的***符号间本身就具有相互关联的特性，但传统译码方法并未充分利用好这一点，本申请对现有技术中OvCDM***的改进之一在于，改进了***译码过程中节点的累加支路测度计算方法，将平均支路测度来代替瞬时支路测度，从而使得当前节点的累加支路测度的信息，不仅包含了当前节点之前的支路测度信息，还包括了当前节点之后的支路测度的一定信息，这使得当前节点的累加支路测度更具参考性，使得筛选出的译码路径更准确和可靠。
另外，传统的OvCDM***的译码规则一般采用维特比(Viterbi)译码，对于一个编码支路数为K’的M维调制OvCDM***，其对应的格状图中稳定状态的节点数为MK’-1，因此译码复杂度会随着编码去路数K’而指数增加。而在OvCDM***中，需要尽可能大的编码支路数K’，以使得频谱效率越高，但是同时译码复杂度会随K’的增加而急剧增加，因此频谱效率与译码复杂度、译码效率形成了一对矛盾需求。针对此问题，本实施例中在计算累加支路测度时，令支路长度L等于编码支路数K’，就可以达到与复杂的维特比算法一样的效果。另外，本申请采用的译码规则，也不需要像维特比算法一样遍历所有状态节点及其扩展路径，只需要从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展，因此可以大幅度降低译码复杂度，并提高译码效率，其译码复杂度并不会像传统译码方案一样随着编码支路数K’的增加而急剧增加，解决了频谱效率与译码复杂度、译码效率这一对矛盾需求。
下面具体说明。
(1)计算扩展的长度为L的各支路的测度
公式为：
Figure PCTCN2017091961-appb-000025
其中L为分段路径长度，L≤L’。当L’很大时，L在可容忍计算复杂度前提下越大越好。因为OvCDM***符号间本身就具有相互关联的特性，通过本申请的应用分段路径测度的译码方法，强化了测度之间的参考性，使得筛选出的译码路径可靠度更高。
从格状图的节点i出发长度为L的分段数据流为ui,ui+1,…,ui+L，i表示帧符号序列索引，分别计算接收符号数据流yi,yi+1,…,yi+L与分段数据流之间的测度，以得到各支路的分段路径测度。
(2)计算平均支路测度
平均支路测度公式：
Figure PCTCN2017091961-appb-000026
对(1)中求得的各支路的分段路径测度比较得出最小测度对应的路径，再对其求平均，即得到平均支路测度。
(3)计算累加支路测度
累加支路测度公式：
Figure PCTCN2017091961-appb-000027
α表示权重因子，取值为小数α∈[0.9,1]，由***平坦衰落宽度决定。含义为随着译码深度的增加，距离当前节点越远的节点其测度影响越小。
Figure PCTCN2017091961-appb-000028
表示当前节点的累加支路测度。
Figure PCTCN2017091961-appb-000029
表示当前节点的平均支路测度。
Figure PCTCN2017091961-appb-000030
表示当前节点之前的前一节点的累加支路测度。
由(2)得到ui的各到达节点的平均支路测度，将ui-1的累加支路测度乘上相应的权重因子，分别与各到达节点的平均支路测度相加，得到各到达节点当前时刻的累加支路测度。
当i＝0时，即为原点，也就是初始时刻的节点，此时仅存在平均支路测度，不存在前一节点的累加测度，在计算时，在数学上可以直接令原点的平均支路测度为原点的累加支路测度。
(4)译码规则
由(3)得到ui的各到达节点当前时刻的累加支路测度，对其进行大小比较，选取测度较小的节点对其进行节点扩展，同样是从当前节点选取长度为L的分段数据流，按照(1)～(3)的方式对其进行节点测度选取和扩展，每扩展一次增加一个到达节点。
在一实施例中，可以在扩展到某一节点后只保留前rn条到达节点及其累加支路测度，rn由***容忍的性能损失决定，将具有较大平均支路测度的路径及其测度全部抛弃。
在一实施例中，当信噪比很高时，一旦某分段路径的测度远小于其它分段路径时，可以直接从该分段路径向前扩展，使译码复杂度进一步大幅度降低。
(5)判决输出
对其余的数据帧符号按照(1)～(4)的方式进行筛选和扩展，如此进行直至数据帧结束，将具有最小平均支路测度到达节点的路径判决输出，此路径即为最终的译码结果。
上述过程，以输入数据流为u＝{+1,-1,-1,-1,-1,+1,-1,+1,+1,-1,+1,-1,-1,-1,-1,+1}，K’＝2，L’＝2，L＝2，rn＝4，编码矩阵
Figure PCTCN2017091961-appb-000031
的OvCDM为例，这些参数设计下对应的OvCDM***的格状图如图23所示。
(1)编码
首先对于K’＝2，将输入数据流u转换为两路，对应为：
u1＝{+1,-1,-1,-1,+1,+1,-1,-1}
u2＝{-1,-1,+1,+1,-1,-1,-1,+1}
每一路的卷积系数表示为：b0＝[1 j],b1＝[j 1]，参照附图20编码结构和附图23的格状图，其编码输出为c＝{1-j,-2,-2,0,2-2j,0,-2,-2}。
(2)译码
经过信号同步、信道估计、数字化处理后，接收端得到信号序列，为方便说明，假定为理想状态，此时接收信号序列为c＝{1-j,-2,-2,0,2-2j,0,-2,-2}，按 照上述中的应用分段路径测度的译码方法，对接收到的序列进行译码，其译码路径如附图24所示，最终得到正确的译码结果。
本申请公开的适用于OvXDM***的译码方法、装置及OvXDM***，在译码过程中对***对应的格状图中访问节点进行筛选，通过改进累加支路测度计算方法，并结合权重因子，来共同筛选较优路径，并对累加支路测度最小的节点进行扩展，筛选出最佳译码路径，在重叠复用次数或编码支路数较大的OvXDM***译码过程中应用本申请，会降低***设计复杂度和计算量，使***具有较低误码率，同时性能提到提升。
以上内容是结合具体的实施方式对本申请所作的进一步详细说明，不能认定本申请的具体实施只局限于这些说明。对于本申请所属技术领域的普通技术人员来说，在不脱离本申请发明构思的前提下，还可以做出若干简单推演或替换。

Claims (13)

  1. 一种适用于OvXDM***的译码方法，其特征在于，包括以下步骤：
    计算节点的累加支路测度；
    根据计算得到的累加支路测度进行译码；
    其中，任意一节点的累加支路测度通过以下步骤计算：
    对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数；分别计算长度为L的分段数据流各条支路的测度，以得到各支路的分段路径测度；
    比较所述各支路的分段路径测度，以选取最小测度；
    将所述最小测度除以L，以得到当前时刻节点的平均支路测度；
    将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。
  2. 如权利要求1所述的适用于OvXDM***的译码方法，其特征在于，将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子。
  3. 如权利要求2所述的适用于OvXDM***的译码方法，其特征在于，所述权重因子的取值范围为大于等于0.9且小于等于1。
  4. 如权利要求1至3中任一项所述的适用于OvXDM***的译码方法，其特征在于，所述OvXDM***为OvTDM***、OvFDM***、OvCDM***、OvSDM***或OvHDM***。
  5. 如权利要求4所述的适用于OvXDM***的译码方法，其特征在于，当所述OvXDM***为OvTDM***或OvFDM***时，支路长度L小于或等于***的重叠复用次数；当所述OvXDM***为OvCDM***时，支路长度L小于或等于***的编码支路数。
  6. 如权利要求1所述的适用于OvXDM***的译码方法，其特征在于，所述根据计算得到的累加支路测度进行译码，包括：从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展。
  7. 一种适用于OvXDM***的译码装置，其特征在于，包括：
    节点累加支路测度计算模块，用于计算节点的累加支路测度；
    译码模块，用于根据计算得到的累加支路测度进行译码；
    其中，节点累加支路测度计算模块包括：
    扩展模块，用于对前一时刻节点向后扩展L个节点，以得到长度为L的分段数据流的全部支路，其中L为大于1的整数；
    第一计算模块，用于分别计算长度为L的分段数据流各条支路的测度，以得到各支路的分段路径测度；
    比较模块，用于比较所述各支路的分段路径测度，以选取最小测度；
    平均支路测度计算模块，用于将所述最小测度除以L，以得到当前时刻节点的平均支路测度；
    加法模块，用于将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度，以得到当前时刻节点的累加支路测度。
  8. 如权利要求7所述的适用于OvXDM***的译码装置，其特征在于，还包括权重因子模块，用于在加法模块将当前时刻节点的平均支路测度加上前一时刻节点的累加支路测度时，先将前一时刻节点的累加支路测度乘以一权重因子。
  9. 如权利要求8所述的适用于OvXDM***的译码装置，其特征在于，所述权重因子模块中的权重因子的取值范围为大于等于0.9且小于等于1。
  10. 如权利要求7至9中任一项所述的适用于OvXDM***的译码装置，其特征在于，当所述OvXDM***为OvTDM***或OvFDM***时，支路长度L小于或等于***的重叠复用次数；当所述OvXDM***为OvCDM***时，支路长度L小于或等于***的编码支路数。
  11. 如权利要求7所述的适用于OvXDM***的译码装置，其特征在于，所述译码模块包括最小累加支路测度扩展模块，用于从初始时刻的节点开始，每次都选取最小累加支路测度的节点进行扩展。
  12. 一种OvXDM***，其特征在于，包括权利要求7至11中任一项所述的的译码装置。
  13. 如权利12所述的OvXDM***，其特征在于，所述OvXDM***为OvTDM***、OvFDM***、OvCDM***、OvSDM***或OvHDM***。
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101262232A (zh) * 2008-04-28 2008-09-10 山东大学 一种针对重叠编码复用的译码算法
CN101997553A (zh) * 2009-08-13 2011-03-30 中兴通讯股份有限公司 一种卷积码译码方法及装置
US20110075649A1 (en) * 2009-09-13 2011-03-31 Research Institute Of Tsinghua University In Shenzhen Method and system of frequency division multiplexing
CN103427850A (zh) * 2012-05-24 2013-12-04 中兴通讯股份有限公司 多模维特比解码装置及其解码方法

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5905742A (en) * 1995-12-27 1999-05-18 Ericsson Inc. Method and apparauts for symbol decoding
EP1356652B1 (en) * 2001-01-16 2006-06-28 Koninklijke Philips Electronics N.V. Bit interleaved coded modulation (BICM) mapping
US7773699B2 (en) * 2001-10-17 2010-08-10 Nortel Networks Limited Method and apparatus for channel quality measurements
US8265175B2 (en) * 2007-06-05 2012-09-11 Constellation Designs, Inc. Methods and apparatuses for signaling with geometric constellations
CN101471689B (zh) * 2007-12-29 2013-03-20 ***通信集团公司 在通信***中传送数据的方法、通信装置及通信***
CN101471746B (zh) * 2007-12-29 2012-06-27 ***通信集团公司 宽带无线传输的方法、装置及一种传输***
US20110103236A1 (en) * 2009-09-13 2011-05-05 Research Institute Of Tsinghua University In Shenzhen Transmission method of code division multiplexing and multiple access
US20110141918A1 (en) * 2009-09-13 2011-06-16 Research Institute Of Tsinghua University In Shenzhen Time division multiplexing method and system
EP3149893A4 (en) * 2014-05-29 2018-03-07 Causam Energy, Inc. System, method, and data packets for messaging for electric power grid elements over a secure internet protocol network
CN105281785B (zh) * 2015-10-22 2018-08-31 东南大学 一种列表连续消除极化码译码方法、装置
CN105406877B (zh) * 2015-11-26 2018-11-06 天津大学 一种短码长循环码的译码方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101262232A (zh) * 2008-04-28 2008-09-10 山东大学 一种针对重叠编码复用的译码算法
CN101997553A (zh) * 2009-08-13 2011-03-30 中兴通讯股份有限公司 一种卷积码译码方法及装置
US20110075649A1 (en) * 2009-09-13 2011-03-31 Research Institute Of Tsinghua University In Shenzhen Method and system of frequency division multiplexing
CN103427850A (zh) * 2012-05-24 2013-12-04 中兴通讯股份有限公司 多模维特比解码装置及其解码方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3490176A4 *

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