WO2017049633A1

WO2017049633A1 - Method, apparatus and receiver for computing signal-to-interference-and-noise ratio

Info

Publication number: WO2017049633A1
Application number: PCT/CN2015/090829
Authority: WO
Inventors: 原近宏; 赵越; 黄涛; 程型清
Original assignee: 华为技术有限公司
Priority date: 2015-09-25
Filing date: 2015-09-25
Publication date: 2017-03-30
Also published as: CN107534530A; CN107534530B

Abstract

Provided are a method, apparatus and receiver for computing a signal-to-interference-and-noise ratio. The method comprises: performing a median acquisition operation on N first output symbol variances at each SNR to obtain a median variance transfer function; determining third output symbol variances in combination with a broadband SINR of a data flow where a symbol is located; and computing the SINR of a single subcarrier at a next iteration based on the third output symbol variances. The method of the present invention improves the accuracy for computing an SINR of a single subcarrier.

Description

Method, device and receiver for calculating signal to noise ratio

Technical field

The present invention relates to communication technologies, and in particular, to a method, an apparatus, and a receiver for calculating a signal to interference and noise ratio.

Background technique

Minimum Mean Square Error Successive Interference Cancellation (MMSE-SIC) receiver is a commonly used advanced receiver technology in Single User Multi-input Multi-output (Single User Multi-input Multi-output) The MMSE-SIC receiver will use the MMSE-SIC receiver to feed back the adapted Modulation and Coding Scheme (MCS) to the base station, that is, the User Equipment (UE) will use the MMSE-SIC receiver. Calculating a valid signal to interference and noise ratio SINR (the effective SINR is the SINR of a single subcarrier when the MMSE-SIC receiver decodes in the last iteration), thereby transmitting an MCS adapted to the SINR to the base station according to the SINR Then, the base station can recalculate the channel quality indicator (CQI) according to the SINR, and then send a signal to the user equipment (User Equipment, UE for short) according to the recalculated CQI.

In general, the iterative decoding process of the MMSE-SIC receiver is as follows: the base station transmits a data stream, and the data stream passes through the transmitting antenna to reach the MMSE-SIC receiver, but the MMSE-SIC receiver cannot know the specific data stream transmitted by the transmitting end. Content, the MMSE-SIC receiver only performs multiple iterative decoding by receiving the received data stream (the data stream may include at least one symbol), and determines the pair according to the identifier in the symbol obtained after each iteration decoding. Whether the symbols in each data stream are decoded correctly, when all the symbols in a data stream are decoded correctly, the MMSE-SIC receiver knows the specific content of the data stream. Since the SINR of the MMSE-SIC receiver during the last iteration decoding is related to the SINR during the previous iterative decoding process, the MMSE-SIC calculates the current iterative decoding process during each iterative decoding process. SINR.

In the prior art, the MMSE-SIC receiver calculates the SINR for each iteration decoding using the average variance transfer function, and the acquisition of the average variance transfer function requires the system to preset a simulation number. N and multiple SNRs (in a Gaussian white noise environment, the value of SNR on a single subcarrier is equal to the value of SINR on a single subcarrier). At a given SNR, the MMSE-SIC receiver needs to obtain the output symbol variance of the decoder in each simulation, and then average the N N output symbol variances obtained from the obtained N simulations, respectively. The average output symbol variance at SNR, which in turn yields an average variance transfer function.

However, in the prior art, the MMSE-SIC calculates the SINR accuracy on each subcarrier in each iterative process by the average variance transfer function.

Summary of the invention

The method, device and receiver for calculating the signal to interference and noise ratio provided by the embodiments of the present invention aim to solve the technical problem that the accuracy of the SINR on each subcarrier calculated by the prior art using the average variance transfer function is not high.

In a first aspect, the present invention provides a method for calculating a signal to interference and noise ratio, the method being applicable to a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the MMSE-SIC The receiver includes a decoder, and after the MMSE-SIC receiver performs the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the estimated symbols of the symbols; the method includes:

Obtaining N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs;

Performing a median operation on the N first output symbol variances at each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer function includes each of the SNRs and each of the described a mapping relationship between the second output symbol variances corresponding to the estimated symbols in the SNR; the taking the median operation comprises: respectively sorting the N first output symbol variances, and according to the preset policy and after the sorting At least one first output symbol variance of an intermediate position in the N first output symbol variances determines the second output symbol variance;

Performing a determining operation, the determining operation comprising: an average signal to interference and noise ratio SINR and a median variance transfer function when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers according to the obtained Determining a third output symbol variance of the decoder at the average SINR;

Calculating, according to the third output symbol variance, the decoder in the next iterative decoding process The SINR of the data stream in which the symbol is located on a single subcarrier, and returns to perform the determining operation until the symbol is successfully decoded or the number of iterative decodings reaches a preset number of times.

With reference to the first aspect, in a first possible implementation manner of the first aspect, the symbol corresponds to a constellation point that is sent by the transmitting end according to the to-be-transmitted bit; and the obtaining the N-th simulation operation after each of the SNRs And obtaining the N first output symbol variances corresponding to the estimated symbols, specifically:

Performing N simulation operations for each of the SNRs to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs; wherein the simulation operations include:

Obtaining an expected value of a square of a modulus of the symbol at each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol;

Obtaining a first output corresponding to the estimated symbol at each of the SNRs according to an expected value of a square of a modulus of the symbol at each of the SNRs and an expected value of a square of a modulus of the estimated symbol at each of the SNRs Symbol variance.

With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the selecting, according to the power of the constellation point, the constellation point, the symbol is used as the symbol The probability of performing the transmission, obtaining the expected value of the square of the modulus of the symbol under each of the SNRs, specifically including:

According to the formula

Determining a square of a modulus of the symbol at each of the SNRs, wherein the P _k is a power of the constellation point at time _t, and the Pr(x _t,i =S _k ) is a selection constellation of the transmitting end Point S _{k is} the probability of transmitting the symbol, the x _t,i is the symbol sent by the transmitting end t, the k is an index of the constellation point, and the M is a constellation point representation The number of bits of the bit, the M being a positive integer greater than or equal to 1;

According to the formula

Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the Nc is a number of subcarriers, and each time t corresponds to one subcarrier.

In conjunction with the second possible implementation of the first aspect, in a third possible implementation of the first aspect, the expected value of the square of the modulus according to the symbol and the estimated symbol for each of the SNRs The expected value of the square of the modulus, obtaining the first corresponding to the estimated symbol under each of the SNRs Output symbol variance, including:

According to the formula

Determining an expected value of a square of a modulus of the estimated symbol at each of the SNRs; wherein

For the estimated symbol;

According to the formula

Obtaining a first output symbol variance corresponding to the estimated symbol at each of the SNRs.

With reference to the first aspect to any one of the third possible implementation manners of the first aspect, in the fourth possible implementation manner of the first aspect, the taking the median operation includes:

Performing size sorting on the N first output symbol variances respectively;

If N is an odd number, determining a first output symbol variance at an intermediate position among the sorted N first output symbol variances as the second output symbol variance;

If N is an even number, the average of the adjacent two first output symbol variances at intermediate positions in the sorted N first output symbol variances is determined as the second output symbol variance.

In a second aspect, the present invention provides a signal to interference and noise ratio calculation apparatus, the apparatus being applicable to a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the MMSE-SIC The receiver includes a decoder, after the MMSE-SIC receiver performs the last iterative decoding on the symbols in the data stream transmitted by the transmitting end, the decoder outputs the estimated symbols of the symbols; the apparatus includes:

a symbol variance obtaining module, configured to acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs;

a median variance transfer function obtaining module, configured to perform a median operation on the N first output symbol variances in each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer function includes a mapping relationship between each of the SNRs and a second output symbol variance corresponding to the estimated symbol in each of the SNRs; the taking a median operation comprises: respectively sorting the N first output symbol variances And determining, according to the preset policy and the at least one first output symbol variance of the intermediate position in the sorted N first output symbol variances, the second output symbol variance;

a determining module, configured to perform a determining operation, where the determining operation comprises: an average signal to interference and noise ratio SINR when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers, and the middle a value variance transfer function that determines the number of the decoder at the average SINR Three output symbol variance;

a calculation module, configured to calculate, according to the third output symbol variance, an SINR of the data stream in which the symbol is located on a single subcarrier in the next iterative decoding process, and return to perform the determining operation until The decoding of the symbol is successful or the number of iterative decoding reaches a preset number of times.

With reference to the second aspect, in a first possible implementation manner of the second aspect, the symbol corresponds to a constellation point that is sent by the sending end according to the to-be-transmitted bit, and the symbol variance acquiring module is specifically configured to be used in each Performing N simulation operations at SNR to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs; wherein the simulation operation includes: selecting according to power of the constellation points and the transmitting end Obtaining a probability that the constellation point is transmitted as the symbol, obtaining an expected value of a square of a modulus of the symbol at each of the SNRs, and according to an expected value of each square of the modulus of the symbol at each of the SNRs and each And an expected value of a square of a modulus of the estimated symbol under the SNR, and acquiring a first output symbol variance corresponding to the estimated symbol in each of the SNRs.

With reference to the first possible implementation manner of the second aspect, in a second possible implementation manner of the second aspect, the symbol variance acquisition module is specifically configured to select, according to a power of the constellation point, and the sending end The probability that the constellation point is transmitted as the symbol, and the expected value of the square of the modulus of the symbol in each of the SNRs is obtained, which specifically includes:

The symbol variance acquisition module is specifically used according to a formula

Determining the square of the modulus of the symbol at each of the SNRs, and according to the formula

Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the _Pk is a power of the constellation point at time _t, and the Pr( _{xt, i} = _Sk ) is the transmitting end Selecting a constellation point _Sk as a probability of transmitting the symbol, the x _t,i being the symbol sent by the transmitting end t, the k being an index of the constellation point, and the M being a constellation The number of bits of the bit represented by the dot, the M being a positive integer greater than or equal to 1, the Nc being the number of subcarriers, and each time t corresponding to one subcarrier.

With reference to the second possible implementation manner of the second aspect, in a third possible implementation manner of the second aspect, the symbol variance acquisition module is specifically configured to be used according to a period of a square of a modulus of the symbol Obtaining a desired value of the square of the modulus of the estimated symbol under each of the SNRs, and acquiring a first output symbol variance corresponding to the estimated symbol in each of the SNRs, specifically:

Determining an expected value of a square of a modulus of the estimated symbol at each of the SNRs, and according to a formula

Obtaining a first output symbol variance corresponding to the estimated symbol under each of the SNRs; wherein

Is the estimated symbol.

With reference to any one of the second aspect to the third possible implementation manner of the second aspect, in the fourth possible implementation manner of the second aspect, the taking the median operation includes:

Performing size sorting on the N first output symbol variances respectively;

In a third aspect, the present invention provides a receiver, which is a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the receiver including a decoder, After the receiver performs the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the estimated symbols of the symbols; the receiver further includes:

a processor, configured to acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs, and for the N first outputs in each of the SNRs The symbol variance performs a median operation to obtain a median variance transfer function; wherein the median variance transfer function includes between each of the SNRs and a second output symbol variance corresponding to the estimated symbol at each of the SNRs Mapping the relationship; the taking the median operation comprises: respectively sorting the N first output symbol variances, and according to the preset strategy and at least one of the intermediate positions in the sorted N first output symbol variances The first output symbol variance determines the second output symbol variance;

The processor is further configured to perform a determining operation, where the determining operation comprises: an average signal to interference and noise ratio SINR when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers according to the acquired The median variance transfer function determines a third output symbol variance of the decoder at the average SINR, and calculates the decoder according to the third output symbol variance The SINR of the data stream in which the symbol is located in the sub-iterative decoding process on a single subcarrier, and returns to perform the determining operation until the decoding of the symbol is successful or the number of iterative decoding reaches a preset number of times.

With reference to the third aspect, in a first possible implementation manner of the third aspect, the symbol corresponds to a constellation point that the transmitting end maps according to the to-be-transmitted bit, and the processor is configured to obtain each of the SNRs The N first output symbol variances corresponding to the estimated symbols obtained after the N simulation operations include:

The processor is specifically configured to perform N simulation operations for each of the SNRs to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs, where the simulation operations include: Obtaining an expected value of a square of a modulus of the symbol at each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol, and according to each of the SNRs The expected value of the square of the modulus of the symbol and the expected value of the square of the modulus of the estimated symbol for each of the SNRs are obtained, and a first output symbol variance corresponding to the estimated symbol at each of the SNRs is obtained.

With reference to the first possible implementation manner of the third aspect, in a second possible implementation manner of the third aspect, the processor is configured to select, according to a power of the constellation point, and the sending end The probability that the constellation point is transmitted as the symbol, and the expected value of the square of the modulus of the symbol in each of the SNRs is obtained, which specifically includes:

The processor is specifically configured according to a formula

Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the _Pk is a power of the constellation point at time _t, and the Pr( _{xt, i} = _Sk ) is the transmitting end Selecting a constellation point _Sk as a probability of transmitting the symbol, the x _t,i being the symbol sent by the transmitting end t, the k being an index of the constellation point, and the M being a constellation The number of bits of the bit represented by the dot, the M being a positive integer greater than or equal to 1; the Nc being the number of subcarriers, and each time t corresponding to one subcarrier.

In conjunction with the second possible implementation of the third aspect, in a third possible implementation of the third aspect, the processor is specifically configured to use an expected value of each of the squares of the symbols and each The expected value of the square of the modulus of the estimated symbol in the SNR, and the first output symbol variance corresponding to the estimated symbol in each of the SNRs is obtained, which specifically includes:

The processor is specifically configured according to a formula

Is the estimated symbol.

With reference to any one of the third aspect to the third possible implementation manner of the third aspect, in the fourth possible implementation manner of the third aspect, the taking the median operation includes:

Performing size sorting on the N first output symbol variances respectively;

The method, device and receiver for calculating the signal to interference and noise ratio provided by the embodiment of the present invention obtain the N first output symbol variances corresponding to the estimated symbols under each SNR, and the N of each of the SNRs The first output symbol variance performs a median operation to obtain a median variance transfer function, thereby shifting the average SINR and the median variance when the symbol is transmitted on all subcarriers in the current iterative decoding process. a function of determining a third output symbol variance of the decoder at the average SINR, and further calculating, according to the third output symbol variance, that the symbol is in a single subcarrier during a next iterative decoding process SINR on. The method provided by the embodiment of the invention improves the accuracy of the MMSE-SIC receiver in calculating the SINR of the symbol on a single subcarrier in each iterative decoding process, and improves the input and output variance fitting of the decoder. The accuracy of the function.

DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief description of the drawings used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description Are some embodiments of the invention, to those of ordinary skill in the art In other words, other drawings can be obtained from these drawings without any creative work.

1 is a schematic flowchart of Embodiment 1 of a method for calculating a signal to interference and noise ratio according to the present invention;

2 is a schematic flowchart diagram of Embodiment 2 of a method for calculating a signal to interference and noise ratio according to the present invention;

3 is a schematic flowchart of Embodiment 3 of a method for calculating a signal to interference and noise ratio according to the present invention;

4 is a schematic structural diagram of Embodiment 1 of a device for calculating a signal to interference and noise ratio according to the present invention;

FIG. 5 is a schematic structural diagram of Embodiment 1 of a receiver provided by the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. It is a partial embodiment of the invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

The method according to the embodiment of the present invention may be applied to an MMSE-SIC receiver, where the MMSE-SIC receiver includes a decoder, and may further include a log likelihood ratio module, a signal reconstruction module, and the like. The MMSE-SIC receiver can be located inside the UE. The UE involved in the embodiment of the present invention may be a wireless terminal, which may be a device that provides voice and/or data connectivity to a user, a handheld device with a wireless connection function, or other processing device connected to a wireless modem. The wireless terminal can communicate with one or more core networks via a radio access network (e.g., RAN, Radio Access Network). The wireless terminal can be a mobile terminal, such as a mobile telephone (or "cellular" telephone) and a computer with a mobile terminal that exchanges language and/or data with the wireless access network. A wireless terminal may also be called a system, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, an access point, or an access point. Remote Terminal, Access Terminal, User Terminal, User Agent, User Device, or User Equipment.

The transmitting end involved in the embodiment of the present invention may be a base station. The base station (e.g., access point) can refer to a device in the access network that communicates with the wireless terminal over one or more sectors over the air interface. The base station can be used to convert the received air frame and the IP packet into each other as a wireless terminal. A router between the endpoint and the rest of the access network, wherein the remainder of the access network may include an Internet Protocol (IP) network. The base station can also coordinate attribute management of the air interface. For example, the base station may be a base station (BTS, Base Transceiver Station) in GSM or CDMA, or may be a base station (NodeB) in WCDMA, or may be an evolved base station in LTE (NodeB or eNB or e-NodeB, evolutional Node B), this application is not limited.

Generally, the transmitting end has a bit to be transmitted, and after being modulated by the constellation of the transmitting end, the bits are mapped into constellation points, and then the mapped constellation points are respectively transmitted through the transmitting antenna in the form of data streams. The transmitting end may send multiple data streams on multiple subcarriers, and each data stream may include at least one symbol. For example, suppose that data stream 1 includes two bound symbols of 1# and 2#, and data stream 2 includes two bound symbols of 3# and 4#, but at the time of transmission, 1# transmitted on subcarrier 1 at time t And the 3# symbol, the 2# and 4# symbols transmitted on subcarrier 2 at the next moment. However, when the receiver receives these symbols, the 1# and 2# symbols are still included in the data stream 1, and the 3# and 4# symbols are still included in the data stream 2.

When the MMSE-SIC receiver at the receiving end receives these data streams and iteratively decodes each symbol in each data stream, the decoder outputs the estimated symbols corresponding to each symbol (because the receiving end is receiving the transmitting end) After the transmitted data stream, if the specific content of the symbol in the data stream is unknown, the data stream needs to be decoded to obtain an estimated symbol. Thus, there is an error between the estimated symbol and the symbol actually transmitted by the transmitting end.

In the prior art, in order to obtain the effective SINR of each subcarrier at each time t (the SINR is the SINR of the MMSE-SIC receiver on the single subcarrier when decoding the last iteration of the received symbol), it needs to be acquired. Average variance transfer function. The specific process is as follows:

The system pre-configures the MMSE-SIC receiver with at least one Signal Noise Ratio (SNR) and N times of simulation times, and then the MMSE-SIC receiver obtains the MMSE-SIC in each simulation at a given SNR. The receiver obtains the variance of the output symbol of the decoder, and then averages the N output symbol variances obtained by the obtained N simulations respectively to obtain the average output symbol variance under the SNR, and finally obtains the median variance shift pair under the SNR. According to the above method, the median variance transfer pair under each SNR is obtained, and then the average variance transfer function is obtained according to the obtained N median variance transfer pairs. In order to better understand the process, continue to use the above examples as an example:

The sender sends a string of random 0s and 1 bits, and maps the bits through the constellation into symbols (symbol 1, symbol 2, symbol 3, and symbol 4, respectively), plus Gaussian white noise (Gaussian white noise according to The current SNR and the square of the modulus of the symbol are calculated) and finally sent to the receiving end (MMSE-SI receiver) through the transmitting antenna. The MMSE-SIC receiver receives the signal through the receiving antenna, and then maps the received signal into soft bit information through a certain mapping relationship, and then uses the soft bit information as the input of the decoder. After the decoding process, the decoder outputs the signal. New soft bit information, and then these new soft bit information are respectively reconstructed into estimated symbols symbol_estimate (1#', 2#', 3#', 4#' respectively), and then according to the traditional covariance calculation formula The output symbol variance of the symbols. According to this process, assuming that the system is configured with two SNRs for the MMSE-SIC receiver, namely SNR1 and SNR2, and the number of simulations is 500, the MMSE-SIC receiver obtains 500 output symbols for each symbol under SNR1. variance. Then, the MMSE-SIC receiver averages the 500 output symbol variances of each symbol to obtain the average output symbol variance corresponding to each symbol, and then obtains four median variance shift pairs, thereby obtaining the SNR1 and The median variance of each symbol shifts the mapping relationship between pairs. Similarly, for SNR2, the MMSE-SIC receiver performs the same process, and obtains the mapping relationship between the SNR2 and the median variance transfer pair of each symbol under SNR2. Finally, based on the above two mapping relationships, the average variance transfer function is obtained.

In this way, the MMSE-SIC receiver can determine the SINR of each subcarrier during the last iteration decoding according to the average variance transfer function, as follows:

Step 1: The MMSE-SIC receiver performs the first iterative decoding according to Equation 1:

Calculate each subcarrier on each sub-time t

Where k is the number of iterative decodings and P is the average power of the constellation points.

Is the physical parameter used by the MMSE-SIC receiver when receiving (in the first iteration decoding,

Is an initial value, in the subsequent iterative decoding process,

It is calculated by calculation), h _i is the value of the i-th column of the channel matrix H at the current time t. It should be noted that several symbols are transmitted on one subcarrier, which is obtained here.

For the sake of clearer description of how to obtain the SINR of each subcarrier in the last iterative decoding process, the SINR of one subcarrier is taken as an example. The SINR of other subcarriers can refer to the subcarrier. The SINR acquisition process is to be obtained.

Step 2: The MMSE-SIC receiver corresponds to each symbol on the subcarrier

The mapping is divided into mutual information MI _t,i .

Step 3: Then according to Equation 2:

Get average mutual information.

Fourth step: The average mutual information is then mapped again to an average SINR, where the average SINR is the wideband SINR of the symbols on the subcarriers transmitted on all subcarriers.

Step 5: After obtaining the average SINR, the decoder is replaced by an average variance transfer function, and the average output symbol variance corresponding to the average SINR is obtained according to the average variance transfer function, and the average output symbol variance is used as the output of the decoder. Symbol variance

The sixth step: the MMSE-SIC receiver corrects the obtained output symbol variance, and determines the required time for the second iteration decoding according to the modified output symbol variance.

Then returning to the first step and then according to the above formula 1, the SINR on the subcarrier at the time of the second iterative decoding can be obtained. Repeating the first step to the sixth step above, and finally obtaining the SINR of the subcarrier on the last iteration of the MMSE-SIC receiver.

In summary, after the above process, the prior art obtains the SINR on each subcarrier at the time t, the last iteration of the MMSE-SIC receiver. However, in the prior art, the average output symbol variance is used as the actual output symbol variance of the decoder in the fifth step, which is different from the output symbol variance actually calculated by the MMSE-SIC during each iteration decoding. Not very sexual. Therefore, the accuracy of the SINR on each subcarrier calculated by the prior art using the average variance transfer function is not high.

Therefore, the method for calculating the signal to interference and noise ratio provided by the embodiment of the present invention aims to solve the technical problem that the accuracy of the SINR on each subcarrier calculated by the prior art using the average variance transfer function is not high.

The technical solutions of the present invention and the technical solutions of the present invention are described in detail below with reference to specific embodiments. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in some embodiments.

FIG. 1 is a schematic flowchart diagram of Embodiment 1 of a method for calculating a signal to interference and noise ratio according to the present invention. This embodiment relates to a specific process of calculating the SINR of each subcarrier by using a median variance transfer function. The executor of the method is an MMSE-SIC receiver, and after the MMSE-SIC receiver performs the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the bit information reconstructed from the symbol. Estimated symbol. As shown in Figure 1, the method includes:

S101: Acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each SNR.

Specifically, the system pre-configures at least one SNR for the MMSE-SIC receiver, so that the MMSE-SIC receiver can obtain the estimated symbol of the decoder output corresponding to the first output symbol at each SNR and in each simulation. variance. In the embodiment of the present invention, the number of simulations is N times per SNR, so the MMSE-SIC receiver obtains N first output symbol variances under each SNR.

It should be noted that the process of obtaining the variance of the first output symbol in each simulation may be performed by using the prior art, and may be obtained by other methods, which is not limited by the embodiment of the present invention. In addition, the symbol of the data stream sent by the sending end may be one or more, and each data stream may include one symbol or multiple symbols. One symbol corresponds to one estimated symbol, and one estimated symbol corresponds to a first output symbol variance in one simulation.

S102: Perform a median operation on the N first output symbol variances in each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer function includes each of the SNR and each a mapping relationship between the second output symbol variances corresponding to the estimated symbols in the SNR; the taking the median operation comprises: respectively sorting the N first output symbol variances, and according to a preset policy and located The at least one first output symbol variance of the intermediate positions in the sorted N first output symbol variances determines the second output symbol variance.

Specifically, in order to better illustrate the specific execution process of this step, the following describes the N first output symbol variances under one SNR (assumed to be SNR1) as an example:

The MMSEISIC receiver sorts the N first output symbol variances under the SNR1 obtained above, and the ordering can be sorted according to the magnitude of the variance. Optionally, the first output symbol variances may be arranged in descending order, and the first output symbol variances may be arranged in ascending order. After sorting, the MMSE-SIC receiver obtains the N first output symbol variances after sorting.

Thereafter, the MMSE-SIC receiver determines the second output symbol variance according to a preset policy and at least one first output symbol variance of the intermediate position in the sorted N first output symbol variances, optionally, may be The first output symbol variance of the intermediate position in the sorted N first output symbol variances is used as the second output symbol variance of the decoder, and may also be located in the sorted N first output symbol variances The arithmetic mean of the two or even more first output symbol variances at the intermediate position is taken as the second output symbol variance of the decoder. This gives the decoding under SNR1. The second output symbol variance of the device, that is, the median variance shift pair corresponding to SNR1 is obtained.

Using the same method as described above, the MMSE-SIC receiver obtains the second output symbol variance of the estimated symbol at each SNR, thereby obtaining a median variance shift pair of the estimated symbols corresponding to each SNR. Of course, when there are multiple symbols in the data stream, each estimated symbol corresponds to a median variance shift pair, so that each SNR corresponds to multiple median variance shift pairs. Furthermore, the MMSE-SIC receiver obtains a median variance transfer function according to the median variance transfer pair corresponding to each SNR and each SNR, and the median variance transfer function includes each SNR and each SNR. A mapping relationship between the second output symbol variances of the estimated symbols.

In order to better illustrate the process, a simple example is given below: It is assumed that the data stream sent by the sender is two, namely data stream 1 and data stream 2, and data stream 1 includes 1# and 2# symbols. Data stream 2 includes 3# and 4# symbols. Suppose the system is configured with two SNRs for the MMSE-SIC receiver, SNR1 and SNR2, respectively, and the number of simulations is 500. The MMSE-SIC receiver is at SNR1. In one simulation, the first output symbol variance of the estimated symbol 1 corresponding to the 1# symbol, the first output symbol variance of the estimated symbol 2 corresponding to the 2# symbol, and the first output symbol variance of the estimated symbol 3 corresponding to the 3# symbol are respectively obtained. The first output symbol variance of the estimated symbol 4 corresponding to the 4# symbol. Then the process is performed 500 times, so that the first output symbol variance corresponding to 500 estimated symbols 1 , the first output symbol variance corresponding to 500 estimated symbols 2, and the first output symbol variance corresponding to 500 estimated symbols 3 are obtained. 500 estimated symbols 4 corresponding to the first output symbol variance. Then, the MMSE-SIC receiver performs a median operation on the corresponding first output symbol variance corresponding to the 500 estimated symbols 1, and obtains a second output symbol variance corresponding to the estimated symbol 1, and then obtains the SNR1, and the estimated symbol 1 corresponds to The median variance is shifted to 1. In the same way, the MMSE-SIC receiver obtains the second output symbol variance corresponding to the estimated symbol 2 in the SNR1, the second output symbol variance corresponding to the estimated symbol 3 in the SNR1, and the corresponding symbol 4 in the SNR1. The output symbol variance is further obtained, and the median variance transfer pair of the estimated symbol 2 under the SNR1 is obtained, the median variance transfer pair 3 of the estimated symbol 3 under the SNR1, and the median variance transfer pair 4 of the estimated symbol 4 under the SNR1 are obtained. That is to say, under SNR1, there are four median variance transfer pairs. Similarly, under SNR2, there are also four median variance transfer pairs. Finally, the MMSE-SIC receiver determines the median variance transfer function based on the mapping relationship between the SNR1 and the four median variance transfer pairs at SNR1 and the mapping relationship between the SNR2 and the four median variance transfer pairs at SNR2.

S103: Perform a determining operation, where the determining operation comprises: determining, according to the average SINR and the median variance transfer function when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers, The third output symbol variance of the decoder at the average SINR.

Specifically, after the MMSE-SIC receiver determines the median variance transfer function, the MMSE-SIC receiver obtains an average SINR when the symbol is transmitted on all subcarriers in the current iterative decoding process, and the average SINR of the symbol The specific acquisition process can refer to the prior art, and details are not described herein again. After the MMSE-SIC receiver obtains the average SINR of the symbol in the current iterative decoding process, according to each SNR in the median variance transfer function and the second output symbol corresponding to the estimated symbol under each of the SNRs The mapping relationship between the variances determines a third output symbol variance corresponding to the average SINR, and the third output symbol variance is the output symbol variance of the decoder during the decoding of the iteration. It should be noted that when there are multiple symbols on the subcarriers, the corresponding estimated symbols are multiple, and the third average symbol variance corresponding to the determined average SINR is also multiple. Moreover, in the Gaussian white noise environment, the above average SINR has the same value as the SNR.

S104: Calculate, according to the third output symbol variance, an SINR of the data stream where the symbol is located in a single subcarrier in the next iterative decoding process, and return to perform the determining operation until the The symbol decoding succeeds or the number of iterative decoding reaches a preset number of times.

Specifically, after the MMSE-SIC receiver obtains the output symbol variance (ie, the third output symbol variance) of the decoder during the iterative decoding process, the MMSE-SIC receiver corrects the third output symbol variance. Calculating, according to the modified third output symbol variance, the SINR of the symbol on a single subcarrier in the next iterative decoding process, and returning to perform the determining operation until the symbol is decoded The number of successful or iterative decoding reaches the preset number of times. In this way, the MMSE-SIC receiver can obtain the SINR of the symbol on a single subcarrier when the last iteration is decoded. For the description of this step, refer to the description of the prior art, and details are not described herein again.

In the prior art, the SINR of the symbol on the single subcarrier when the MMSE-SIC receiver determines the last iteration decoding adopts an average variance transfer function, and the average output symbol variance is used as the actual output symbol of the decoder. The variance, which is different from the variance of the output symbols actually calculated by the MMSE-SIC at each iteration decoding, is not high, so the accuracy of SINR on each subcarrier calculated by the average variance transfer function in the prior art is used. Not high; however, the median variance transfer function is used in the embodiment of the present invention, and the third output symbol variance obtained according to the median variance transfer function is close to the actual output symbol of the decoder in the current iterative decoding process. Poor, since the variance of the third output symbol is less than the actual output symbol variance of the decoder during the current iterative decoding process, therefore, each iterative decoding process calculated according to the median variance transfer function The accuracy of the SINR of a symbol on a single subcarrier is relatively high. Therefore, the method provided by the embodiment of the present invention improves the accuracy of the MMSE-SIC receiver in calculating the SINR of the symbol on a single subcarrier in each iterative decoding process.

The calculation method of the signal to interference and noise ratio provided by the embodiment of the present invention, by obtaining the N first output symbol variances corresponding to the estimated symbols under each SNR, and for the N first output symbols in each of the SNRs The variance performs a median operation to obtain a median variance transfer function, thereby determining the average SINR and the median variance transfer function when the symbol is transmitted on all subcarriers in the current iterative decoding process. a third output symbol variance of the coder at the average SINR, and then calculating an SINR of the symbol on a single subcarrier in the next iterative decoding process by the decoder according to the third output symbol variance. The method provided by the embodiment of the invention improves the accuracy of the MMSE-SIC receiver in calculating the SINR of the symbol on a single subcarrier in each iterative decoding process, and improves the input and output variance fitting of the decoder. The accuracy of the function.

Further, based on the foregoing embodiment, referring to the second embodiment shown in FIG. 2, the embodiment relates to the specific process of taking the median operation. As shown in FIG. 2, the above median operation specifically includes:

S201: Perform size ordering on the N first output symbol variances.

Optionally, the N first output symbol variances may be arranged in descending order, and the N first output symbol variances may be arranged in order from small to large. After sorting, the MMSE-SIC receiver obtains the sorted N first output symbol variances after sorting.

S202: If N is an odd number, determine a first output symbol variance of an intermediate position in the sorted N first output symbol variances as the second output symbol variance.

S203: If N is an even number, determine an average value of adjacent two first output symbol variances at intermediate positions among the sorted N first output symbol variances as the second output symbol variance.

FIG. 3 is a schematic flowchart diagram of Embodiment 3 of a method for calculating a dry noise ratio according to the present invention. The present embodiment relates to a specific process of calculating a first output symbol variance of an estimated symbol corresponding to a symbol of the data stream. The symbol in the foregoing data stream corresponds to the constellation point that the transmitting end maps according to the to-be-transmitted bit. On the basis of the foregoing Embodiment 1, the S101 may specifically include: performing N in each of the SNRs. The sub-simulation operation obtains N first output symbol variances corresponding to the estimated symbols at each of the SNRs. For each simulation operation, refer to the method steps shown in FIG. 3, which specifically includes:

S301: Obtain an expected value of a square of a modulus of the symbol under each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol.

Specifically, as described in the foregoing embodiment, in each simulation process under each SNR, one estimated symbol corresponds to a first output symbol variance, and in the N simulation process, the estimated symbol corresponds to N firsts. An output symbol variance. The following is an introduction to each simulation operation of the MMSE-SIC receiver at each given SNR:

The MMSE receiver obtains the expected value of the square of the modulus of the symbol at each SNR according to the power of the constellation point corresponding to the symbol in the data stream sent by the transmitting end and the probability that the transmitting end selects the constellation point as the symbol. It should be noted that in a noiseless environment, one symbol corresponds to one constellation point.

Alternatively, the MMSE-SIC receiver can be based first on Equation 3:

Determining the square of the modulus of the symbol at each of the SNRs, and then according to Equation 4:

Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the _Pk is a power of the constellation point at time _t, and the Pr( _{xt, i} = _Sk ) is the transmitting end Selecting a constellation point S _k as a probability of transmitting the symbol, the x _t,i being the symbol actually sent by the transmitting end t, the k being an index of the constellation point, and the M being a The number of bits of the bit represented by the constellation point, the M being a positive integer greater than or equal to 1, the Nc being the number of subcarriers, and each time t corresponding to one subcarrier.

Optionally, the MMSE-SIC receiver can obtain the square of the modulus of the symbol according to any variant of Equation 3, for example, multiplying A by the original formula 3, and then dividing by A, or, based on the formula 3. Adding a B to it and then subtracting a B, as long as the square of the modulus of the symbol obtained by the MMSE-SIC receiver according to the modified formula 3 is equal to the square of the modulus of the symbol obtained according to Equation 3. Just fine.

Optionally, the MMSE-SIC receiver can also obtain the expected value of the square of the modulus of the symbol according to any variant of Equation 4, for example, multiplying A by the original formula 4, and then dividing by A, or Adding a B to the formula 4, and then subtracting a B, as long as the expected value of the square of the modulus of the symbol obtained by the MMSE-SIC receiver according to the modified formula 4 is the same as that obtained according to the formula 4. The expected value of the square of the modulus of the symbol is equal.

S302: Acquire, according to an expected value of a square of a modulus of the symbol under each of the SNRs and an expected value of a square of a modulus of the estimated symbol under each of the SNRs, to obtain a corresponding number corresponding to the estimated symbol in each of the SNRs. An output symbol variance.

Specifically, the MMSE-SIC receiver can use Equation 5:

For the estimated symbol; optionally, the MMSE-SIC receiver may also obtain an expected value of the square of the modulus of the estimated symbol under each of the SNRs according to any variant of Equation 5, for example, multiplying by the original formula 5 A, then divide by A, or add a B to the formula 5, and then subtract a B, as long as the MMSE-SIC receiver obtains the square of the modulus of the symbol according to the modified formula 5. The expected value is equal to the expected value of the square of the modulus of the symbol obtained according to Equation 5.

After the MMSE-SIC receiver determines the expected value of the square of the modulus of the above symbol at each of the SNRs and the expected value of the square of the modulus of the estimated symbol, it can be according to Equation 6:

In summary, after the MMSE-SIC receiver performs N simulation operations at each SNR, the N first output symbol variances of the estimated symbols at each SNR can be obtained.

A method for calculating a signal to interference and noise ratio according to an embodiment of the present invention obtains a square of a modulus of the symbol at each SNR by selecting a power of a constellation point at the transmitting end and a probability that the transmitting end selects the constellation point as the symbol to transmit. The expected value, and the first output symbol variance corresponding to the estimated symbol at each SNR is obtained according to an expected value of the square of the modulus of the symbol at each SNR and an expected value of the square of the modulus of the estimated symbol corresponding to the symbol at each SNR. That is, the method provided by the present invention uses the soft power of the constellation point to replace the flatness of the constellation point in the prior art when calculating the first output symbol variance of the estimated symbol. Average power, which can be applied to high-order modulated symbols and short codes, and the calculated first symbol variance of the estimated symbols is relatively accurate; on the other hand, the estimated symbols are obtained for each SNR obtained by the present embodiment. N first output symbol variances, the determined median variance transfer function is more accurate, and then the decoder calculated according to the median variance transfer function in the next iterative decoding process, the symbols are on a single subcarrier The SINR is more accurate.

A person skilled in the art can understand that all or part of the steps of implementing the above method embodiments may be completed by using hardware related to the program instructions. The foregoing program may be stored in a computer readable storage medium, and the program is executed when executed. The foregoing steps include the steps of the foregoing method embodiments; and the foregoing storage medium includes: a medium that can store program codes, such as a ROM, a RAM, a magnetic disk, or an optical disk.

FIG. 4 is a schematic structural diagram of Embodiment 1 of a device for calculating a signal to interference and noise ratio according to the present invention. The apparatus is adapted for an MMSE-SIC receiver configured with at least one SNR, the MMSE-SIC receiver including a decoder that performs a last iterative translation of symbols in a data stream transmitted by a transmitting end After the code, the decoder outputs an estimated symbol of the symbol; as shown in FIG. 4, the apparatus includes: a symbol variance acquisition module 10, a median variance transfer function acquisition module 11, a determination module 12, and a calculation module 13.

Specifically, the symbol variance obtaining module 10 is configured to obtain N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs;

The median variance transfer function obtaining module 11 is configured to perform a median operation on the N first output symbol variances in each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer The function includes a mapping relationship between each of the SNRs and a second output symbol variance corresponding to the estimated symbols in each of the SNRs; the taking a median operation includes: respectively, respectively, the N first output symbol variances Performing sorting, and determining the second output symbol variance according to a preset policy and at least one first output symbol variance of an intermediate position in the sorted N first output symbol variances;

The determining module 12 is configured to perform a determining operation, where the determining operation includes: an average SINR and a median variance when the data stream in which the symbol is located is transmitted on all subcarriers according to the obtained current iterative decoding process. a transfer function determining a third output symbol variance of the decoder at the average SINR;

The calculating module 13 is configured to calculate, according to the third output symbol variance, an SINR of the data stream in which the symbol is located in a single subcarrier in the next iterative decoding process, and return The determining operation is performed until the symbol is successfully decoded or the number of iterative decodings reaches a preset number of times.

The device for calculating a signal to interference and noise ratio according to the embodiment of the present invention may perform the foregoing method embodiments, and the implementation principle and technical effects are similar, and details are not described herein again.

Further, the symbol corresponds to a constellation point mapped by the transmitting end according to the to-be-transmitted bit, and the symbol variance obtaining module 10 is specifically configured to perform N simulation operations under each of the SNRs to obtain each of the SNRs. The N first output symbol variances corresponding to the estimated symbols; wherein the simulation operation comprises: obtaining, according to a power of the constellation point, a probability that the transmitting end selects the constellation point as the symbol to transmit The expected value of the square of the modulus of the symbol at the SNR, and the expected value of the square of the modulus of the symbol for each of the SNRs and the expected value of the square of the modulus of the estimated symbol for each of the SNRs. Obtaining a first output symbol variance corresponding to the estimated symbol at each of the SNRs.

Further, the symbol variance obtaining module 10 is specifically configured to obtain, according to the power of the constellation point and the probability that the transmitting end selects the constellation point as the symbol, to obtain the SNR The expected value of the square of the modulus of the symbol, specifically including:

The symbol variance obtaining module 10 is specifically configured according to a formula

Further, the symbol variance obtaining module 10 is specifically configured to obtain, according to an expected value of a square of a modulus of the symbol and an expected value of a square of a modulus of the estimated symbol under each of the SNRs, each of the SNRs is obtained. The first output symbol variance corresponding to the estimated symbol includes:

Is the estimated symbol.

Further, the taking the median operation specifically includes:

Performing size sorting on the N first output symbol variances respectively;

FIG. 5 is a schematic structural diagram of Embodiment 1 of a receiver provided by the present invention. The receiver is a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the receiver comprising a decoder 20, the receiver in a data stream transmitted by the transmitting end After the symbol is subjected to the last iterative decoding, the decoder 20 outputs the estimated symbol of the symbol; the receiver further includes:

The processor 21 is configured to acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs, and the N firsts in each of the SNRs The output symbol variance performs a median operation to obtain a median variance transfer function; wherein the median variance transfer function includes a variance of a second output symbol for each of the SNR and the estimated symbol for each of the SNRs The mapping operation includes: sorting the N first output symbol variances separately, and according to the preset policy and at least an intermediate position among the sorted N first output symbol variances A first output symbol variance determines the second output symbol variance;

The processor 21 is further configured to perform a determining operation, where the determining operation includes: an average SINR when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers, and the middle a value variance transfer function determining a third output symbol variance of the decoder 20 at the average SINR, and calculating, according to the third output symbol variance, the decoder 20 in the next iterative decoding process The SINR of the data stream where the symbol is located on a single subcarrier and returns to execution The determining operation until the decoding of the symbol is successful or the number of iterative decoding reaches a preset number of times.

The receiver provided by the embodiment of the present invention may perform the foregoing method embodiments, and the implementation principles and technical effects thereof are similar, and details are not described herein again.

Further, the symbol corresponds to a constellation point mapped by the transmitting end according to the to-be-transmitted bit; the processor 21 is configured to acquire N corresponding to the estimated symbol obtained after performing N simulation operations in each of the SNRs. The first output symbol variance includes:

The processor 21 is configured to perform N simulation operations at each of the SNRs to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs, where the simulation operation includes Obtaining an expected value of a square of a modulus of the symbol at each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol, and according to each The expected value of the square of the modulus of the symbol at SNR and the expected value of the square of the modulus of the estimated symbol at each of the SNRs, the first output symbol variance corresponding to the estimated symbol at each of the SNRs is obtained.

Further, the processor 21 is specifically configured to obtain, according to the power of the constellation point, a probability that the transmitting end selects the constellation point as the symbol, and obtain the symbol of each symbol at the SNR. The expected value of the square of the modulus, including:

The processor 21 is specifically configured according to a formula

Further, the processor 21 is specifically configured to acquire, according to an expected value of a square of a modulus of the symbol and an expected value of a square of a modulus of the estimated symbol under each of the SNRs, Estimating the first output symbol variance corresponding to the symbol, specifically including:

The processor 21 is specifically configured according to a formula

Is the estimated symbol.

Further, the taking the median operation specifically includes:

Performing size sorting on the N first output symbol variances respectively;

Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the foregoing embodiments may be modified, or some or all of the technical features may be equivalently replaced; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present invention. range.

Claims

A method for calculating a signal to interference and noise ratio, characterized in that the method is applicable to a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the MMSE-SIC receiver comprising a decoder, after the MMSE-SIC receiver performs the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the estimated symbols of the symbols; the method includes:

Obtaining N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs;

Performing a median operation on the N first output symbol variances at each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer function includes each of the SNRs and each of the described a mapping relationship between the second output symbol variances corresponding to the estimated symbols in the SNR; the taking the median operation comprises: respectively sorting the N first output symbol variances, and according to the preset policy and after the sorting At least one first output symbol variance of an intermediate position in the N first output symbol variances determines the second output symbol variance;

Performing a determining operation, the determining operation comprising: an average signal to interference and noise ratio SINR and a median variance transfer function when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers according to the obtained Determining a third output symbol variance of the decoder at the average SINR;

Calculating, according to the third output symbol variance, an SINR of the data stream where the symbol is located on a single subcarrier in the next iterative decoding process, and returning to perform the determining operation until the symbol is decoded The number of successful or iterative decoding reaches the preset number of times.
The method according to claim 1, wherein the symbol corresponds to a constellation point mapped by the transmitting end according to the to-be-transmitted bit; and the obtaining the estimated symbol obtained after performing N simulation operations under each of the SNRs Corresponding N first output symbol variances, specifically including:

Performing N simulation operations for each of the SNRs to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs; wherein the simulation operations include:

Obtaining an expected value of a square of a modulus of the symbol at each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol;

Obtaining, according to an expected value of a square of a modulus of the symbol under each of the SNRs and an expected value of a square of a modulus of the estimated symbol under each of the SNRs, obtaining an estimated symbol corresponding to each of the SNRs The first output symbol variance.
The method according to claim 2, wherein the probability of transmitting according to the power of the constellation point and the transmitting end selecting the constellation point as the symbol is obtained according to each of the SNRs. The expected value of the square of the modulus of the symbol, specifically including:

According to the formula
Determining a square of a modulus of the symbol at each of the SNRs, wherein the P k is a power of the constellation point at time t, and the Pr(x t,i =S k ) is a selection constellation of the transmitting end Point S k is the probability of transmitting the symbol, the x t,i is the symbol sent by the transmitting end t, the k is an index of the constellation point, and the M is a constellation point representation The number of bits of the bit, the M being a positive integer greater than or equal to 1;

According to the formula
Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the Nc is a number of subcarriers, and each time t corresponds to one subcarrier.
The method according to claim 3, wherein said each of said SNRs is obtained according to an expected value of a square of a modulus of said symbol and an expected value of a square of a modulus of said estimated symbol at each said SNR The first output symbol variance corresponding to the estimated symbol includes:

According to the formula
Determining an expected value of a square of a modulus of the estimated symbol at each of the SNRs; wherein
For the estimated symbol;

According to the formula
Obtaining a first output symbol variance corresponding to the estimated symbol at each of the SNRs.
The method according to any one of claims 1 to 4, wherein the taking the median operation comprises:

Performing size sorting on the N first output symbol variances respectively;

If N is an odd number, determining a first output symbol variance at an intermediate position among the sorted N first output symbol variances as the second output symbol variance;

If N is an even number, the average of the adjacent two first output symbol variances at intermediate positions in the sorted N first output symbol variances is determined as the second output symbol variance.
A computing device for signal to interference and noise ratio, characterized in that the device is suitable for a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the MMSE-SIC receiver comprising a decoder, after the MMSE-SIC receiver performs the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the estimated symbols of the symbols; the device includes:

a symbol variance obtaining module, configured to acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs;

a median variance transfer function obtaining module, configured to perform a median operation on the N first output symbol variances in each of the SNRs to obtain a median variance transfer function; wherein the median variance transfer function includes a mapping relationship between each of the SNRs and a second output symbol variance corresponding to the estimated symbol in each of the SNRs; the taking a median operation comprises: respectively sorting the N first output symbol variances And determining, according to the preset policy and the at least one first output symbol variance of the intermediate position in the sorted N first output symbol variances, the second output symbol variance;

a determining module, configured to perform a determining operation, where the determining operation comprises: an average signal to interference and noise ratio SINR when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers, and the middle a value variance transfer function determining a third output symbol variance of the decoder at the average SINR;

a calculation module, configured to calculate, according to the third output symbol variance, an SINR of the data stream in which the symbol is located on a single subcarrier in the next iterative decoding process, and return to perform the determining operation until The decoding of the symbol is successful or the number of iterative decoding reaches a preset number of times.
The device according to claim 6, wherein the symbol corresponds to a constellation point mapped by the transmitting end according to the to-be-transmitted bit, and the symbol variance obtaining module is specifically configured to perform N simulations under each of the SNRs. Manipulating, obtaining N first output symbol variances corresponding to the estimated symbols in each of the SNRs, wherein the simulating operation comprises: selecting the constellation points as the location according to the power of the constellation points and the transmitting end Deriving the probability of the symbol being transmitted, obtaining an expected value of the square of the modulus of the symbol at each of the SNRs, and according to the expected value of the square of the modulus of the symbol at each of the SNRs and each of the SNRs An expected value of the square of the modulus of the symbol is estimated, and a first output symbol variance corresponding to the estimated symbol at each of the SNRs is obtained.
The apparatus according to claim 7, wherein the symbol variance acquisition module is configured to obtain, according to a power of the constellation point and a probability that the transmitting end selects the constellation point as the symbol to transmit The expected value of the square of the modulus of the symbol under each of the SNRs specifically includes:

The symbol variance acquisition module is specifically used according to a formula
Determining the square of the modulus of the symbol at each of the SNRs, and according to the formula
Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the Pk is a power of the constellation point at time t, and the Pr( xt, i = Sk ) is the transmitting end Selecting a constellation point Sk as a probability of transmitting the symbol, the x t,i being the symbol sent by the transmitting end t, the k being an index of the constellation point, and the M being a constellation The number of bits of the bit represented by the dot, the M being a positive integer greater than or equal to 1, the Nc being the number of subcarriers, and each time t corresponding to one subcarrier.
The apparatus according to claim 8, wherein said symbol variance acquisition module is specifically configured to use an expected value of a square of a modulus of said symbol and an expected value of a square of a modulus of said estimated symbol for each said SNR Obtaining a first output symbol variance corresponding to the estimated symbol in each of the SNRs, specifically:

The symbol variance acquisition module is specifically used according to a formula
Determining an expected value of a square of a modulus of the estimated symbol at each of the SNRs, and according to a formula
Obtaining a first output symbol variance corresponding to the estimated symbol under each of the SNRs; wherein
Is the estimated symbol.
The device according to any one of claims 6-9, wherein the taking the median operation comprises:

Performing size sorting on the N first output symbol variances respectively;

If N is an odd number, it will be in the middle of the sorted N first output symbol variances. The first output symbol variance is determined as the second output symbol variance;

If N is an even number, the average of the adjacent two first output symbol variances at intermediate positions in the sorted N first output symbol variances is determined as the second output symbol variance.
A receiver, characterized in that the receiver is a minimum mean square error serial interference cancellation MMSE-SIC receiver configured with at least one signal to noise ratio SNR, the receiver comprising a decoder, the receiver After performing the last iterative decoding on the symbols in the data stream sent by the transmitting end, the decoder outputs the estimated symbols of the symbols; the receiver further includes:

a processor, configured to acquire N first output symbol variances corresponding to the estimated symbols obtained after performing N simulation operations in each of the SNRs, and for the N first outputs in each of the SNRs The symbol variance performs a median operation to obtain a median variance transfer function; wherein the median variance transfer function includes between each of the SNRs and a second output symbol variance corresponding to the estimated symbol at each of the SNRs Mapping the relationship; the taking the median operation comprises: respectively sorting the N first output symbol variances, and according to the preset strategy and at least one of the intermediate positions in the sorted N first output symbol variances The first output symbol variance determines the second output symbol variance;

The processor is further configured to perform a determining operation, where the determining operation comprises: an average signal to interference and noise ratio SINR when the data stream in which the symbol is located in the current iterative decoding process is transmitted on all subcarriers according to the acquired The median variance transfer function determines a third output symbol variance of the decoder at the average SINR, and calculates the decoder in the next iterative decoding process according to the third output symbol variance The SINR of the data stream in which the symbol is located on a single subcarrier, and returns to perform the determining operation until the symbol is successfully decoded or the number of iterative decodings reaches a preset number of times.
The receiver according to claim 11, wherein the symbol corresponds to a constellation point mapped by the transmitting end according to the to-be-transmitted bit; and the processor is configured to acquire N times of simulation operations after each of the SNRs And obtaining the N first output symbol variances corresponding to the estimated symbols, specifically:

The processor is specifically configured to perform N simulation operations for each of the SNRs to obtain N first output symbol variances corresponding to the estimated symbols in each of the SNRs, where the simulation operations include: Obtaining an expected value of a square of a modulus of the symbol at each of the SNRs according to a power of the constellation point and a probability that the transmitting end selects the constellation point to transmit as the symbol, and according to each of the SNRs The expected value of the square of the modulus of the symbol below and the estimate for each of the SNRs The expected value of the square of the modulo of the symbol obtains the first output symbol variance corresponding to the estimated symbol at each of the SNRs.
The receiver according to claim 12, wherein the processor is configured to obtain, according to a power of the constellation point, a probability that the transmitting end selects the constellation point as the symbol to transmit, The expected value of the square of the modulus of the symbol under the SNR includes:

The processor is specifically configured according to a formula
Determining the square of the modulus of the symbol at each of the SNRs, and according to the formula
Determining an expected value of a square of a modulus of the symbol at each of the SNRs; wherein the Pk is a power of the constellation point at time t, and the Pr( xt, i = Sk ) is the transmitting end Selecting a constellation point Sk as a probability of transmitting the symbol, the x t,i being the symbol sent by the transmitting end t, the k being an index of the constellation point, and the M being a constellation The number of bits of the bit represented by the dot, the M being a positive integer greater than or equal to 1; the Nc being the number of subcarriers, and each time t corresponding to one subcarrier.
The receiver according to claim 13, wherein said processor is specifically configured to: according to an expected value of a square of a modulus of said symbol and an expected value of a square of a modulus of said estimated symbol at said said SNR, Obtaining a first output symbol variance corresponding to the estimated symbol in each of the SNRs, specifically:

The processor is specifically configured according to a formula
Determining an expected value of a square of a modulus of the estimated symbol at each of the SNRs, and according to a formula
Obtaining a first output symbol variance corresponding to the estimated symbol under each of the SNRs; wherein
Is the estimated symbol.
The receiver according to any one of claims 11 to 14, wherein the median operation comprises:

Performing size sorting on the N first output symbol variances respectively;

If N is an odd number, it will be in the middle of the sorted N first output symbol variances. The first output symbol variance is determined as the second output symbol variance;

If N is an even number, the average of the adjacent two first output symbol variances at intermediate positions in the sorted N first output symbol variances is determined as the second output symbol variance.