WO2012159473A1

WO2012159473A1 - Method and device for combining and receiving multiple paths of data of the same source

Info

Publication number: WO2012159473A1
Application number: PCT/CN2012/071622
Authority: WO
Inventors: 姚珂; 王文焕
Original assignee: 中兴通讯股份有限公司
Priority date: 2011-05-25
Filing date: 2012-02-24
Publication date: 2012-11-29
Also published as: CN102801489B; CN102801489A

Abstract

Disclosed are a method and device for combining and receiving multiple paths of data of the same source. The method comprises: adding the creditability of each path of data of the same source when sending multiple paths of data of the same source, or acquiring the creditability of each path of data of the same source when receiving multiple paths of data of the same source; and combining the multiple paths of data of the same source according to the creditability of each path. Through the technical solution provided by the embodiment of the present invention, the creditability of data is considered when the multiple paths of data of the same source are combined, and different pieces of received information are weighted during the combination through the creditability, thereby further improving the reliability of information decoding.

Description

Method and device for combining multiple channels of homologous data

The present invention relates to the field of communications, and in particular, to a method and apparatus for multiplexed reception of multiple homogeneous data. Background technique

CoMP (Coordinated Multipoint Transmission/Reception) is one of the key technologies of LTE-Advanced. The CoMP is mainly for the case where the UE (User Equipment) in the cell edge zone is seriously interfered by the situation, and multiple cells cooperate to perform multipoint data transmission/reception on the interfered UE, or through coordination and scheduling between multiple cells. In order to eliminate inter-cell interference, improve signal quality, improve user and system data throughput, and thereby improve system spectrum utilization.

A collaboration set is an important concept in collaboration technology and refers to a collection of multiple base stations or cells participating in communication with a UE. The CoMP technology is divided into two types: uplink CoMP and downlink CoMP according to the link direction: the downlink CoMP refers to multiple cooperations, and the regional joints transmit data for users, and the uplink CoMP refers to multiple cooperative cells jointly receive data of UEs. The set of cells participating in the collaboration in the uplink and downlink are all collaborative sets.

Uplink CoMP mainly adopts joint processing between coordinated cells, and combines UE uplink data received by multiple points to improve the receiving correct rate. The joint processing of the uplink data requires interaction data between the coordinated cells, that is, in the uplink cooperation process, the UE sends data to the base station in the cooperation set, and when the base station independently decodes incorrectly, a cooperation process may be initiated, and the base station interacts through the X2 interface. The received data, after receiving the data of other base stations in the cooperation set, the base station performs joint decoding together with the data received by the local end. The general combined reception and joint decoding are only in the serving base station and area.

The data exchanged through the X2 interface can be of different processing levels. Usually the interactive data can be divided into 4 levels, from IQ samples (orthogonal two-way sampled data), soft bit (bit) information, CB. (Code Block, TB (Transport Block), the cost is reduced in turn, right

The pressure of the X2 interface is also different. The cooperative base station selects a data packet of the most suitable level according to the capability of the X2 interface and sends it to the serving base station, and the serving base station performs the combining and parsing according to the level of the received data packets of all the cooperative base stations. For the above 4-level data, only the TB and CB levels have CRC check bits, and the receiving end can obtain the detection result according to this, and the detected data can be completely trusted, and if the information detected by the TB and CB levels is incorrect, or the interaction is Soft bit information and IQ samples level information, the data can only be partially trusted.

Since the channels between different base stations and UEs are different, the quality of UE data received by each base station is also different. The sample data of different base stations should show different degrees of trust in joint decoding. For example, data received from a cell with good channel quality is more reliable than data received from a cell with poor channel quality. There is currently no mechanism to reflect this difference.

Similarly, many other technologies in communication systems, such as macrodiversity techniques, retransmission techniques, also have the same-origin data merge process in the above-mentioned collaboration. At present, equal gain combining is usually adopted, which does not reflect the credibility of different paths and reduces the reliability of information decoding. Summary of the invention

The main purpose of the embodiments of the present invention is to provide a method and apparatus for combining and receiving multi-channel homologous data, so as to improve the reliability of information decoding of homologous data combining.

The embodiment of the invention provides a method for combining and receiving multi-channel homologous data, which comprises: adding the credibility of each homologous data when transmitting multi-channel homologous data, or acquiring the multi-channel homologous data when acquiring the multi-channel homologous data Describe the credibility of multi-channel homologous data;

The multi-channel homologous data is combined according to the credibility of the multi-channel homologous data.

Preferably, the credibility of each of the homologous data is separately added when transmitting the multi-channel homologous data, or the credibility of the multi-channel homologous data is obtained when receiving the multi-channel homologous data Previously, it also included:

The credibility of the multi-channel homologous data is determined by a real-time calculation method or a look-up table method. Preferably, the calculating the credibility of the multi-channel homologous data by using a real-time calculation method or a look-up table method includes:

The credibility is determined according to the network environment configuration, the channel quality measured in real time, the decoding result, and the channel quality of the long-term statistics, and the average bit error rate.

Preferably, the obtaining the credibility of the multi-channel homologous data when receiving the multi-channel homologous data comprises:

Extracting a first initial credibility carried by the multi-channel homologous data;

Giving a second initial credibility to the multi-channel homologous data;

And integrating the first initial credibility and the second initial credibility according to a preset rule to obtain a final credibility of the multi-channel homologous data.

Preferably, the combining the multi-channel homologous data according to the credibility of the multi-channel homologous data comprises: determining the credibility of the multi-channel homologous data;

When there is a homogenous data that is completely trusted, and the local corresponding data is not completely trusted, the homologous data is used to replace the local corresponding data;

When each of the homologous data is partially trusted, the credibility of the multi-channel homologous data is used as a weighting weight, and the multi-channel homologous data is weighted or combined.

The embodiment of the invention further provides a device for combining and receiving multi-channel homologous data, comprising: a credibility determining module, configured to separately add credibility of each homologous data when transmitting multi-channel homologous data, or Acquiring the credibility of the multi-channel homologous data when receiving the multi-channel homologous data; and combining modules for combining the multi-channel homologous data according to the credibility of the multi-channel homologous data.

Preferably, the device further includes:

And a calculation module, configured to determine the credibility of the multi-channel homologous data by using a real-time calculation method or a look-up table method.

Preferably, the credibility determining module is specifically configured to perform real-time measurement according to a network environment. The channel quality, the decoding result, and the channel quality of the long-term statistics, and the average bit error rate determine the credibility.

Preferably, the credibility determining module comprises:

An extracting unit, configured to extract a first initial credibility carried by the multi-channel homologous data; an assigning unit, configured to respectively assign a second initial credibility to the multi-channel homologous data; The first initial credibility and the second initial credibility are integrated according to a preset rule to obtain a final credibility of the multi-channel homologous data.

Preferably, the merging module comprises:

a determining unit, configured to determine a credibility of the multi-channel homologous data;

a first replacement unit, configured to replace the local corresponding data with the homologous data when the existing homologous data is completely trusted, and the locally corresponding data is not completely trusted;

a second replacing unit, configured to: when each of the homologous data is partially trusted, use the credibility of the multi-channel homologous data as a weighting weight, and perform weighted combining or selecting the multi-channel homologous data merge.

A method and device for merging and receiving multi-channel homologous data according to an embodiment of the present invention, and proposing to consider the credibility of data when merging and merging homologous data, and embodying different received information at the time of merging through credibility Weighting can further improve the reliability of information decoding. DRAWINGS

1 is a schematic flowchart of a method for combining and receiving multi-channel homologous data according to an embodiment of the present invention; FIG. 2 is a schematic diagram of a system architecture of macro-diversity combining in a method for combining and receiving multi-channel homologous data according to the present invention;

3 is a schematic diagram of a system architecture for retransmission combining in an embodiment of a method for merging and receiving multiple channels of homologous data according to the present invention;

4 is a schematic structural diagram of a system for uplink cooperative merging in an embodiment of a method for merging and receiving multi-channel homologous data according to an embodiment of the present invention; FIG. 5 is a schematic flowchart of the method for obtaining the credibility of the homologous data by the receiving end according to an embodiment of the method for combining and receiving multi-channel homologous data according to the present invention;

6 is a schematic flow chart of a merge in a method for merging and receiving multi-channel homologous data according to an embodiment of the present invention;

FIG. 7 is a schematic flowchart of still another embodiment of a method for merging and receiving multiple channels of homologous data according to the present invention; FIG. 8 is a schematic structural diagram of an apparatus for merging and receiving multiple channels of homologous data according to an embodiment of the present invention; Schematic diagram of a credibility determining module in an embodiment of a device for receiving and receiving homologous data;

10 is a schematic structural diagram of a credibility determining module according to an embodiment of a multi-channel homologous data combining and receiving apparatus according to the present invention;

FIG. 11 is still another schematic structural diagram of a credibility determining module according to an embodiment of a multi-channel homologous data combining and receiving apparatus according to the present invention;

12 is another schematic structural diagram of a credibility determining module according to an embodiment of a multi-channel homologous data combining and receiving apparatus according to the present invention;

13 is a schematic structural diagram of a merging module in an embodiment of a device for merging and receiving multi-channel homologous data according to the present invention;

FIG. 14 is a schematic structural diagram of still another embodiment of a device for merging and receiving multi-channel homologous data according to the present invention. detailed description

The implementation, functional features and advantages of the objects of the present invention will be further described in conjunction with the embodiments herein. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to FIG. 1, an embodiment of a method for merging and receiving multi-channel homologous data according to the present invention includes: Step S10: adding credibility of each homologous data when transmitting multi-channel homologous data, or receiving multiple channels Obtaining the credibility of the multi-channel homologous data when the data is homologous; Step S11: Combine the multi-channel homologous data according to the credibility of the multi-channel homologous data. This embodiment is applicable to the following application scenarios: multiple sending ends, one receiving end, and the receiving end performs data combining on multiple homologous data sent by multiple sending ends. Here, the transmitting end refers to the source point of the data packet when the same data packet is transmitted through different transmission channels. Different transmission channels are distinguished by different working modes, including transmission at different times, transmission in different frequency bands, and different Transmission at the transmitting end, transmission at different multi-antenna ports, transmission in different code channels. The receiving end refers to the end point of the data packet when the same data packet is sent through different transmission channels.

Embodiments of the present invention typically illustrate the method of the present invention by macro-diversity combining, re-sending combining, and uplink combining, respectively.

(1) The general macro-division set includes the following processes: 1. The distribution of the original data packet causes the transmitting end to have the same data; 2. The different points send the data packet, and the multiple transmitting ends send the original data packet at different locations. The space gain can be obtained. 3. The receiving end combines the sample data of different points, and the diversity gain improves the accuracy of data unpacking. details as follows:

Taking the three base station scenarios shown in FIG. 2 as an example: eNB1 is a serving base station of UE1, and eNB2 and eNB3 participate in macro diversity transmission of UE1.

In the first step, the eNB1 distributes the data packet and the related control information to the macro diversity base stations eNB2 and eNB3. In the second step, the eNB1, the eNB2, and the eNB3 send the data packet to the UE1 according to the control information, and carry the reliability of the data packet when transmitting.

It is assumed that the factors determining the reliability are as follows: channel quality (X) measured in real time, channel quality (y) of long-term statistics, distance (z) between eNB1, eNB2, eNB3 and UE1.

For example, the calculation result is that eNB1 evaluates the credibility of a data packet to 0.8, eNB2 evaluates the credibility of the same data packet to 0.6, and eNB3 evaluates the credibility of the same data packet to 0.3.

In the third step, after receiving the data packets sent by the eNB1, the eNB2, and the eNB3 and the credibility thereof, the UE1 combines the data according to the credibility.

One method of merging is to weight the data and add it directly. Taking the credibility of this embodiment as an example, The normalized weighting value of each sample is calculated first: the normalized weighting value of eNB1 is 0.8/(0.8+0.6+0.3)=0.4706, and the normalized weighting value of eNB2 is 0.6/(0.8+0.6+0.3)=0.3529 The normalized weighting value of eNB3 is 0.3/(0.8+0.6+0.3)=0.1765; then each sample is multiplied by the corresponding normalized weighting value, and then the multiple weighted samples are added into one sample, and finally The final result is obtained by the analytical process specified by the agreement.

(2) Retransmission means that the transmitting end resends the data packet when it knows that the receiving end receives the data packet abnormality, and the retransmitted data packet may be the original data packet (such as CC (Chase Combining) in HARQ technology). It can also be the relevant coding package of the original data packet (such as IR (Incremental Redundancy) in HARQ technology). The receiving end combines the newly received data packet with the original data packet to improve the decoding success rate.

The retransmitted data packet and the original data packet may be scheduled at the same frequency location, or may be scheduled at different frequency locations. The transmitting end needs to evaluate the sending position of the data packet when scheduling the data packet, based on long-term and real-time channel measurement information. Therefore, the sender can also give the credibility of the corresponding location of the current data packet. As shown in the retransmission process shown in Figure 3, an example is given in which each transmitted data packet is independently scheduled. Each time the sender is scheduled, the allocated resource location may not be the most reliable, so there is credibility. The difference.

For example: The result of the calculation is that the confidence of the first transmitted packet is evaluated as 0.5, the confidence of the second transmitted packet is evaluated as 0.6, and the reliability of the third transmitted packet is evaluated as 0.8.

During the data transmission process, each sender must evaluate the credibility of the data packet to be sent according to the above method. If the first unpacking is correct, no retransmission is required, otherwise it needs to be retransmitted one or more times.

In the case of retransmission, the receiving end receives multiple samples, and according to the credibility, different weighted combining processing can be performed on the different ones. The specific merging method can adopt the macro-diversity and the method adopted.

(3) Uplink cooperation includes the following processes: 1. Multiple base stations receive data through air interfaces. Obtaining samples of different paths, the link is unreliable, and each base station may have independent decoding capability; 2. Collecting and decoding to a base station, the link is an X2 interface, which is basically reliable. Therefore, step one will introduce differences in the credibility of different points.

Taking the three base station cooperation scenario shown in FIG. 4 as an example: eNB1 is a serving base station of UE1, eNB2 and eNB3 are cooperative base stations of UE1, and the cooperation set is a set of eNB1, eNB2, and eNB3.

In the uplink cooperation process, the serving base station shares all the information of UE1 in the cooperation set, and UE1 sends the uplink data, and the base stations in the cooperation set can receive and perform independent decoding. When the serving base station decodes correctly, no backhaul transmission is required regardless of the resolution of the cooperative base station. When the serving base station decodes the error and the cooperative base station has the correct decoding, the correct base station decodes the fully trusted data sample to the serving base station through the backhaul. After the serving base station receives the fully trusted data sample, the data is used by the serving base station. The sample replaces the local peer-level sample and completes the parsing process. When the serving base station decodes the error and the cooperative base station also decodes the error, the cooperative base station transmits the partially trusted data sample to the serving base station through the backhaul through negotiation, and attaches the credibility of the data sample.

In this embodiment, the base station in each cooperation set tests the channel quality of UE1 and the distance from UE1, and evaluates the reliability of the data packet in combination with the receiving capability of the base station itself. This credibility should reflect long-term and short-term changes in the network environment. For example, if the credibility value ranges from 0 to 1, the trustworthiness of eNB 1 for a data packet is evaluated as 0.8, the trust degree of eNB2 for the same data packet is evaluated as 0.6, and the trust degree of eNB3 for the same data packet is evaluated as 0.3. .

After receiving the data samples of the cooperative base station and the corresponding credibility, the serving base station assigns different weight values to the data samples according to the credibility. Based on the level of the data sample, the same level of data is processed along with the received data samples. For example: If the data sample is at the soft bit level, the serving base station weights and combines the local soft bit information with other sample data. One way to combine is to weight the data and add them directly. Taking the credibility of this embodiment as an example, the weighting value is first calculated: the weighting value of eNB1 is 0.8/(0.8+0.6+0.3)=0.4706, and the weighting value of eNB2 is 0.6/(0.8+0.6+0.3)=0.3529, the weighting value of eNB3 is 0.3/(0.8+0.6+0.3)=0.1765; then each data sample is multiplied by its own weighting value, and then multiple weighted samples are compared. Add a sample and then parse the process as specified by the protocol until the TB is solved. If the data sample is other levels of information, it can also be weighted and merged as described above, and then decoded to solve the TB.

It should be noted that the method proposed in this embodiment is not limited to the weighted combining method, and may be another improved method, and may also adopt a selective combining method, which is not described herein again.

In the uplink cooperation process, the serving base station shares part of the information of the UE1 in the cooperation set, for example, only long-term information and no real-time information, when the UE1 sends the uplink data, the base station in the cooperation set can receive, and only the serving base station can be independent. Decoding, the cooperative base station cannot decode, but the cooperative base station can measure the channel or evaluate the credibility of the data packet in other ways if the channel cannot be measured. In this scenario, when the serving base station decodes correctly, the cooperative base station does not need to transmit data. Otherwise, the cooperative base station needs to send the received original packet with the respective credibility to the serving base station. A plurality of original packet sample data are weighted by the serving base station, combined into one sample, and then parsed according to the protocol until the TB is solved.

In this embodiment, in order to improve the effect of combining and receiving multiple homologous data, when collecting multiple samples, the credibility of the collected samples is attached, so that different weights are reflected in different quality samples in the merge process, so that the reliable data pairs are predicted. Merge decoding contributes even more. This way of differentiating different data samples is more reasonable and more accurate than dealing with data indiscriminately.

Referring to FIG. 5, in an embodiment, step S10 is specifically:

Step S101: Extract a first initial credibility carried by the multi-channel homologous data.

Step S102: Give a second initial credibility to the multi-channel homologous data respectively;

Step S103: Synthesize the first initial credibility and the second initial credibility according to a preset rule to obtain a final credibility of the multi-channel homologous data.

The measurement and statistics of the credibility can be performed at the transmitting end or at the receiving end. When the credibility is determined by the sender, each time the homologous data is sent, it can be carried in a certain field of the homologous data. Add a new field or modify the current field) credibility. When the credibility is determined at the receiving end, the receiving end can give credibility to the homologous data of different transmitting ends each time the data packet is received. There is also a case where the transmitting end writes the first initial credibility when transmitting the homologous data, and the receiving end respectively gives each of the homologous data of the multi-channel homologous data a second initial credibility when receiving, and then The receiving end combines the first initial credibility and the second initial credibility according to a preset rule to obtain the final credibility of each of the homologous data.

Referring to FIG. 6, in the above embodiment, step S11 may include:

Step S11: determining a credibility of the multi-channel homologous data;

Step S112: When there is one way that the homologous data is completely trusted, and the local corresponding data is not completely trusted, the local homologous data is used to replace the local corresponding data;

Step S113: When each of the homologous data is partially trusted, the credibility of the multi-channel homologous data is used as a weighting weight, and the multi-channel homologous data is weighted or combined.

Referring to FIG. 7, another embodiment of the method for merging and receiving multi-channel homology data according to the present invention is provided. In the above embodiment, before performing step S10, the method further includes:

Step S9: Determine the credibility of the multi-channel homologous data by using a real-time calculation method or a look-up table method. The method of determining the credibility may be a real-time calculation method or a table look-up method.

Real-time calculation: Determine the calculation formula of credibility and correct it according to experience. All base stations adopt the same metric.

Assume that the credibility = f(x, y, z) , where f( ) is a function. The specific f(x, y, z) may be a*x+b*y+c*z, where a, b, and c are the weights of the factors.

Lookup method: As with the principle of real-time calculation, the input variables are still x, y, z, and the output variables are credible. The only difference is that the input and output variables are quantized data.

Step S9 can be further:

The credibility is determined according to the network environment configuration, the channel quality measured in real time, the decoding result, and the channel quality of the long-term statistics, and the average bit error rate. The network environment configuration includes distance information, reception and/or transmission capability information, wherein the reception transmission capability includes the number of antennas, antenna sensitivity, and the like.

Real-time channel quality, decoding results, etc. are real-time measurement results;

Long-term average channel quality, average bit error rate, etc. are long-term statistical results.

Referring to FIG. 8, an embodiment of the apparatus for merging and receiving multi-channel homologous data according to the present invention includes: a credibility determining module 10, configured to separately add credibility of each homologous data when transmitting multi-channel homologous data Or obtaining the credibility of the multi-channel homologous data when receiving the multi-channel homologous data; the merging module 20 is configured to merge the multi-channel homologous data according to the credibility of the multi-channel homologous data.

This embodiment is applicable to the following application scenarios: multiple sending ends, one receiving end, and the receiving end performs data combining on multiple homologous data sent by multiple sending ends. Here, the transmitting end refers to the source point of the data packet when the same data packet is transmitted through different transmission channels. Different transmission channels are distinguished by different working modes, including transmission at different times, transmission in different frequency bands, and different Transmission at the transmitting end, transmission at different multi-antenna ports, transmission in different code channels. The receiving end refers to the end point of the data packet when the same data packet is sent through different transmission channels.

The embodiments of the present invention typically illustrate the solution of the present invention by macro diversity combining, retransmission combining, and uplink combining.

In the first step, the eNB1 distributes the data packet and the related control information to the macro diversity base stations eNB2 and eNB3; in the second step, the eNB1, the eNB2, and the eNB3 send the data packet to the UE1 according to the control information, when sending The credibility of carrying the data packet.

In the third step, after the UE1 receives the data packets sent by the eNB1, the eNB2, and the eNB3 and the credibility thereof, the merging module 20 performs the merging process on the data according to the credibility.

One method of merging is to weight the data and add it directly. Taking the credibility of this embodiment as an example, the normalized weighting value of each sample is first calculated: the normalized weighting value of eNB1 is 0.8/(0.8+0.6+0.3)=0.4706, and the normalized weight value of eNB2 is 0.6/(0.8+0.6+0.3)=0.3529, the normalized weighting value of eNB3 is 0.3/(0.8+0.6+0.3)=0.1765; then each sample is multiplied by the corresponding normalized weighting value, and then The multiple weighted samples are added together to form a sample, and finally the final result is obtained according to the parsing process specified by the protocol.

(2) Retransmission means that the transmitting end resends the data packet when it knows that the receiving end receives the data packet abnormality, and the retransmitted data packet may be the original data packet (such as CC in HARQ technology), or may be the original data packet. Correlation coding package (such as IR in HARQ technology). The receiving end combines the newly received data packet with the original data packet to improve the decoding success rate.

The retransmitted data packet and the original data packet may be scheduled at the same frequency location, or may be scheduled at different frequency locations. The transmitting end needs to evaluate the sending position of the data packet when scheduling the data packet, based on long-term and real-time channel measurement information. Therefore, the credibility determining module 10 of the transmitting end can also give the credibility of the corresponding location of the current data packet. As shown in the retransmission process shown in Figure 3, an example is given in which each transmitted data packet is independently scheduled. Each time the sender is scheduled, the allocated resource location may not be the most reliable, so there is credibility. The difference.

For example: The result of the calculation is that the confidence of the first transmitted packet is evaluated as 0.5, the confidence of the second transmitted packet is evaluated as 0.6, and the reliability of the third transmitted packet is evaluated as 0.8. During the data transmission process, each sender must evaluate the credibility of the data packet to be sent according to the above method. If the first unpacking is correct, no retransmission is required, otherwise it needs to be retransmitted one or more times.

In the case of retransmission, the receiving end receives a plurality of samples, and the merging module 20 may perform different weighted combining processing on different samples according to the reliability. The specific merging method can adopt the macro-diversity and the method adopted.

(3) Uplink cooperation includes the following processes: 1. Multiple base stations receive data through air interfaces to obtain samples of different paths, the link is unreliable, and each base station may have independent decoding capability; 2. Collecting to a base station for merging Decoding, the link is an X2 interface and is basically reliable. So step one will introduce differences in the credibility of the different points.

In the uplink cooperation process, the serving base station shares all the information of UE1 in the cooperation set, and UE1 sends the uplink data, and the base stations in the cooperation set can receive and perform independent decoding. When the serving base station decodes correctly, no backhaul transmission is required regardless of the resolution result of the cooperative base station. When the serving base station decodes the error and the cooperative base station has the correct decoding, the correct base station decodes the fully trusted data sample to the serving base station through the backhaul. After the serving base station receives the fully trusted data sample, the data is used by the serving base station. The sample replaces the local peer-level sample and completes the parsing process. When the serving base station decodes the error and the cooperative base station also decodes the error, the cooperative base station transmits the partially trusted data sample to the serving base station through the backhaul through negotiation, and the credibility determination module 10 appends the credibility of the data sample.

In this embodiment, the base station in each cooperation set tests the channel quality of UE1 and the distance from UE1, and evaluates the reliability of the data packet in combination with the receiving capability of the base station itself. This credibility should reflect long-term and short-term changes in the network environment. For example, if the credibility value ranges from 0 to 1, the trustworthiness of eNB 1 for a data packet is evaluated as 0.8, and the trustworthiness of eNB2 for the same data packet is evaluated as 0.6. The trustworthiness of eNB3 for the same data packet is evaluated as 0.3.

After the serving base station receives the data samples of the cooperative base station and the corresponding credibility, the merging module 20 assigns different weight values to the data samples according to the credibility. Based on the level of the data sample, the same level of local data is processed along with the received data samples. For example: If the data samples are at the soft bit level, the serving base station weights and combines the local soft bit information with other sample data. One method of combining is to weight the data and add them directly. Taking the credibility of this embodiment as an example, the weighting value is first calculated: the weighting value of eNB1 is 0.8/(0.8+0.6+0.3)=0.4706, and the weighting value of eNB2 is 0.6/(0.8+0.6+0.3)=0.3529. The weighting value of eNB3 is 0.3/(0.8+0.6+0.3)=0.1765; then each data sample is multiplied by its own weighting value, then multiple weighted samples are added into one sample, and then the parsing process according to the protocol is specified. Until the TB is solved. If the data sample is other levels of information, it can also be weighted and merged as described above, and then decoded to resolve the TB.

It should be noted that the solution proposed in this embodiment is not limited to the weighted combining method, and may be another improved method, and may also adopt a selective combining method, which is not described herein again.

In this embodiment, in order to improve the effect of combining and receiving multiple homologous data, when collecting multiple samples, the credibility of the collected samples is attached, so that different weights are reflected in different quality samples in the merge process, so that the reliable data pairs are predicted. Merge decoding contributes even more. This way of differentiating different data samples is more reasonable and more accurate than processing data indiscriminately. Referring to FIG. 9, in an embodiment, the credibility determining module 10 includes:

The extracting unit 11 is configured to extract a first initial credibility carried by the multi-channel homologous data; and the assigning unit 12 is configured to respectively assign a second initial credibility to the multi-channel homologous data; the synthesizing unit 13 And combining the first initial credibility and the second initial credibility according to a preset rule to obtain a final credibility of the multi-channel homologous data.

As shown in Figure 10, Figure 11, and Figure 12, the measurement and statistics of the credibility can be performed at the transmitting end or at the receiving end. When the credibility is determined by the sender, each time the homologous data is sent, the credibility can be carried in a field of the same source data (adding a new field or modifying the current field). Credibility When the receiving end determines, the receiving end can give credibility to the homologous data of different transmitting ends each time the data packet is received. There is also a case where the transmitting end writes the first initial credibility when transmitting the homologous data, and the receiving end respectively gives each of the homologous data of the multi-channel homologous data a second initial credibility when receiving, and then The receiving end combines the first initial credibility and the second initial credibility according to a preset rule to obtain the final credibility of each of the homologous data.

Referring to FIG. 13, in the above embodiment, the merging module 20 includes:

The determining unit 21 is configured to determine the credibility of the multi-channel homologous data;

The first replacing unit 22 is configured to replace the local corresponding data with the homologous data when the existing homologous data is completely trusted, and the locally corresponding data is not completely trusted;

a second replacing unit 23, configured to: when each of the homologous data is partially trusted, use the credibility of the multi-channel homologous data as a weighting weight, and perform weighted combining on the multi-channel homologous data or Choose to merge.

Referring to FIG. 14, another embodiment of the apparatus for merging and receiving multiple channels of the same data in the present invention is provided. In the foregoing embodiment, the method further includes:

The calculating module 30 is configured to determine the reliability of the multi-channel homologous data by using a real-time calculation method or a look-up table method.

The calculation module 30 can determine the credibility by using a real-time calculation method or a look-up table method. Real-time calculation: Determine the calculation formula of credibility, and correct it according to experience. All base stations adopt the same metric.

In the above embodiment, the credibility determining module 10 is specifically configured to determine the credibility according to the network environment configuration, the channel quality measured in real time, the decoding result, and the long-term statistical channel quality and the average bit error rate.

The network environment configuration includes distance information, reception and/or transmission capability information, wherein the reception transmission capability includes the number of antennas, antenna sensitivity, and the like.

The above description is only the preferred embodiment of the present invention, and is not intended to limit the scope of the invention, and the equivalent structure or equivalent flow transformation made by the specification and the drawings of the present invention may be directly or indirectly applied to other related The technical field is equally included in the scope of patent protection of the present invention.

Claims

Claim

A method for merging and receiving multi-channel homologous data, comprising: adding a credibility of each homologous data when transmitting multi-channel homologous data, or acquiring when acquiring multi-channel homologous data The credibility of the multi-channel homologous data;

2. The method according to claim 1, wherein the credibility of each of the homologous data is separately added when transmitting the multi-channel homologous data, or when receiving the multi-channel homologous data Before the credibility of the multi-channel homologous data, the method further includes:

The credibility of the multi-channel homologous data is determined by a real-time calculation method or a look-up table method.

3. The method according to claim 2, wherein the calculating the credibility of the multi-channel homologous data by using a real-time calculation method or a look-up table method comprises:

The method according to any one of claims 1 to 3, wherein the obtaining the credibility of the multi-channel homologous data when receiving the multi-channel homologous data comprises:

Giving a second initial credibility to the multi-channel homologous data;

The method according to any one of claims 1 to 3, wherein the combining the multi-channel homologous data according to the credibility of the multi-channel homologous data comprises:

Determining the credibility of the multi-channel homologous data;

When each homologous data is partially trusted, the credibility of the multi-channel homologous data is made For weighting the weights, the multi-channel homologous data is weighted or combined.

A device for combining and receiving multi-channel homologous data, comprising: a credibility determining module, configured to separately add credibility of each homologous data when transmitting multi-channel homologous data, or Acquiring the credibility of the multi-channel homologous data when receiving the multi-channel homologous data; and combining modules for combining the multi-channel homologous data according to the credibility of the multi-channel homologous data.

7. The apparatus according to claim 6, further comprising: a calculating module, configured to determine the credibility of the multi-channel homologous data by using a real-time calculation method or a look-up table method.

The apparatus according to claim 6, wherein the credibility determining module is specifically configured to determine, according to a network environment configuration, a channel quality measured in real time, a decoding result, and a long-term statistical channel quality and an average bit error rate. The credibility.

The device according to any one of claims 6 to 8, wherein the credibility determining module comprises:

The apparatus according to any one of claims 6 to 8, wherein the merging module comprises: