CN102025456A - Feedback parameter selection device and feedback parameter selection method - Google Patents

Abstract

The present invention relates to a feedback parameter selection device and a feedback parameter selection method. The feedback parameter selection device is used for a receiver and comprises: an effective carrier to interference and noise power ratio calculation unit for calculating a plurality of effective carrier to interference and noise power ratios respectively corresponding to each combination of a precoding matrix, a modulation coding scheme, and a frequency band that can be selected by the receiver; the screening unit is used for screening the effective carrier interference noise power ratios according to the effective carrier interference noise power ratio threshold values corresponding to the modulation coding schemes; and a feedback parameter selection unit which obtains the largest effective carrier interference noise power ratio in the screened effective carrier interference noise power ratios, and determines the combination of the precoding matrix, the modulation coding scheme and the frequency band corresponding to the largest effective carrier interference noise power ratio as the combination of the precoding matrix, the modulation coding scheme and the frequency band to be fed back.

Description

Feedback parameter selection device and feedback parameter selection method

technical field

The present invention is related to wireless communication, in particular to a wireless receiver using closed-loop Multiple Input Multiple Output (MIMO, Multiple Input Multiple Output) technology.

Background technique

In a wireless communication system, multiple antennas are installed at the transmitting end and the receiving end, which is called multiple-input multiple-output technology. In different ways, MIMO technology can effectively improve the reliability and capacity of wireless communication. Orthogonal Frequency Division Multiplexing (OFDM, Orthogonal Frequency Division Multiplex) can be effectively combined with MIMO technology to form a MIMO-OFDM system by dividing the frequency selective fading channel into independent flat fading channels, and the MIMO-OFDM system is widely used It is used in super 3G and 4G wireless communication systems.

When the channel is known at the sender, system performance can be improved by performing some preprocessing. In MIMO technology, the transmission data is multiplied by a specific matrix according to channel conditions, which can improve link quality and transmission rate. This technology is called precoding technology. Generally, the channel state information needs to be estimated by the receiving end and fed back to the sending end. However, whether it is directly feeding back the channel state or feeding back the calculated precoding matrix, for OFDM multi-carrier and MIMO multi-antenna systems, the amount of feedback is very large and the system cannot bear it. Therefore, a codebook-based feedback method will be used in a practical system. In this way, both the sending end and the receiving end store the same set of precoding matrices, and this set is called a codebook. Then the channel information is estimated at the receiving end, and the best matrix is searched in the codebook according to certain criteria according to the channel information as the precoding matrix, and only the selected precoding matrix index (PMI, Precoding Matrix Index) is fed back. The sending end can be made to complete precoding to effectively reduce the bits of the precoding feedback information.

In the MIMO-OFDM wireless communication system, the channel changes in space, frequency and time, which causes a lot of uncertainty in the communication process. On the one hand, in order to improve the system throughput, high-order modulation with high transmission rate and less redundant error correction codes are used for communication. In this way, the system throughput is indeed greatly improved when the signal-to-noise ratio of the wireless fading channel is ideal. However, when the channel is in deep fading, it cannot guarantee reliable and stable communication. On the other hand, in order to ensure the reliability of communication, low-order modulation with low transmission rate and large redundant error correction codes are used for communication, even when the wireless channel is in deep fading, the reliability of communication can be guaranteed. However, when the channel signal noise When it is relatively high, due to the low transmission rate, the improvement of the throughput of the system is restricted, resulting in waste of resources. Therefore, considering the throughput and reliability of the system comprehensively, the Adaptive Modulation Coding (AMC, Adaptive Modulation Coding) technology is introduced on this basis. Change the modulation and coding methods to obtain the maximum throughput under different channel conditions. In a practical system, the channel information is generally estimated at the receiving end, and then a suitable coding and modulation scheme (MCS, Modulation and Coding Scheme) is selected according to a certain error probability requirement, and the information indicating the corresponding MCS is fed back to the sending end. Implement AMC technology.

One of the characteristics of MIMO-OFDM is the existence of frequency selectivity. In a multi-user scenario, the different environments of users will make some users have better channel conditions on some frequency bands, while other users have poorer channel conditions on the same frequency band. If different frequency selectivity of different users is used for resource scheduling, and the most suitable frequency resources are allocated to users for transmission, the system capacity can be effectively improved. In the MIMO-OFDM system that actually uses frequency selective scheduling, the entire frequency resource can generally be divided into several frequency bands (BAND), and then the channel conditions of users in each frequency band are measured respectively, and the frequency band with the best channel condition is selected to be allocated to users, thereby realizing frequency selective scheduling. Similar to PMI and MCS, the channel information is generally estimated at the receiving end and the frequency band to be selected is measured, and then the best frequency band is selected, and the information indicating the frequency band (such as the serial number) is fed back to the sending end.

That is to say, in the MIMO-OFDM wireless communication system with feedback, PMI, MCS, and BAND all need to be selected at the receiving end and fed back to the sending end.

The following uses the typical MIMO-OFDM system with feedback shown in FIG. 1 to illustrate this problem.

As shown in Figure 1, for a MIMO-OFDM system with the number of transmitting antennas Nt and the number of receiving antennas Nr, in the subcarrier K, the single-layer or multi-layer source data is first encoded and modulated by the modulation unit 101 using the MCS fed back from the receiver Perform coding and modulation, and then enter the space-time coding unit 102, and the space-time coding unit 102 uses the frequency band information fed back by the receiver to form s data streams. After being multiplied by the precoding matrix W _i in the precoding unit 103, the transmitted symbols are formed. Then, the subcarrier allocation and mapping unit 104 schedules the user's data flow to the corresponding subchannel and maps it on the physical subcarrier in a certain way. The formed multi-carrier signal in the frequency domain is processed by IFFT and adding a cyclic prefix at the IFFT unit 105 , and then sent by an antenna via a radio frequency front-end (RF) 106 .

In the receiver, the FFT unit 108 performs FFT on the signal received by the radio frequency front end 107 through the antenna, and the desubcarrier allocation and mapping unit 109 demaps the FFT signal.

Channel estimation is performed at the channel estimation unit 110 . In the feedback parameter selection unit 111 , according to the channel estimation result of the channel estimation performed by the channel estimation unit 110 , the selection of the precoding matrix, the frequency band and the MCS is completed. The selected information indicating the precoding matrix, MCS, frequency band is fed back to the transmitter by the receiver. The space-time detection unit 112 performs data stream separation and equalization according to the estimated real channel and the PMI adopted by the transmitter; the demodulation and encoding unit 113 performs demodulation and channel decoding to restore the transmitted data.

Therefore, in the MIMO-OFDM system with feedback, the performance of the system depends on whether the selection of the precoding matrix, frequency band and MCS at the receiver corresponds to the channel conditions. In the process of studying the present invention, the inventor found that in the traditional method, the precoding matrix, frequency band and MCS are selected in a certain order, and the selection of these three is independent of each other, but actually these three are related to each other Therefore, the precoding matrix, BAND and MCS selected in the prior art are not optimal.

Contents of the invention

The embodiments of the present invention are made in view of the above-mentioned problems of the prior art, to eliminate or alleviate one or more problems of the prior art, and to provide at least one beneficial option.

In order to achieve the object of the present invention, the present invention provides the following aspects.

Aspect 1. A feedback parameter selection device for a receiver, wherein the feedback parameter selection device includes:

An effective carrier-to-interference-to-noise power ratio calculation unit, configured to calculate a plurality of effective carrier-to-interference-to-noise power ratios corresponding to combinations of precoding matrices, modulation and coding schemes and frequency bands that can be selected by the receiver;

The screening unit is configured to screen the plurality of effective carrier-to-interference-to-noise power ratios according to the effective carrier-to-interference-to-noise power ratio threshold value corresponding to each modulation and coding scheme; and

The feedback parameter selection unit obtains the largest effective carrier-to-interference-to-noise power ratio among the screened effective carrier-to-interference-to-noise power ratios, and determines the combination of the precoding matrix, modulation and coding scheme and frequency band corresponding to the largest effective carrier-to-interference-to-noise power ratio is the combination of precoding matrix, modulation and coding scheme and frequency band to be fed back.

Aspect 2. The feedback parameter selection device according to aspect 1, wherein the feedback parameter selection device further includes a modulation and coding scheme threshold unit, and the modulation and coding scheme threshold unit is used to obtain the effective carrier corresponding to each modulation and coding scheme Interference noise power ratio threshold.

Aspect 3. The feedback parameter selection device according to aspect 1, wherein the effective carrier-to-interference-to-noise power ratio calculation unit calculates the effective carrier-to-interference-to-noise power ratio using a method based on symbol mutual information.

Aspect 4. The device for selecting feedback parameters according to aspect 1, wherein the effective carrier-to-interference-to-noise power ratio calculation unit calculates the effective carrier-to-interference-to-noise power ratio using an exponential combination method.

Aspect 5. The feedback parameter selection device according to aspect 1, wherein the effective carrier-to-interference-to-noise power ratio calculation unit combines the calculated effective carrier-to-interference-to-noise power ratio with the corresponding precoding matrix, modulation and coding scheme, and frequency band Correspondingly stored in the data table, the screening unit screens the effective carrier-to-interference-to-noise power ratio by looking up the data table, and the feedback parameter selection unit searches for the largest effective carrier-to-interference noise power ratio by looking up the data table Noise power ratio, and thus determine the combination of precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier-to-interference and noise power ratio.

Aspect 6. A feedback parameter selection method for a receiver, wherein the feedback parameter selection method includes:

An effective carrier-to-interference-to-noise power ratio calculation step, which is used to calculate a plurality of effective carrier-to-interference-to-noise power ratios corresponding to each combination of a precoding matrix, a modulation coding scheme and a frequency band that can be selected by the receiver;

The screening step is to screen the plurality of effective carrier-to-interference noise power ratios according to the effective carrier-to-interference noise power ratio threshold value corresponding to each modulation and coding scheme; and

The feedback parameter selection step is to obtain the maximum effective carrier-to-interference-to-noise power ratio in the screened effective carrier-to-interference-to-noise power ratio, and select the combination of the precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier-to-interference-to-noise power ratio is the combination of precoding matrix, modulation and coding scheme and frequency band to be fed back.

Aspect 7. The feedback parameter selection method according to aspect 6, wherein the feedback parameter selection step further includes a modulation and coding scheme threshold acquisition step, and the modulation and coding scheme threshold acquisition step is used to obtain the corresponding modulation and coding schemes. The effective carrier-to-interference-to-noise power ratio threshold.

Aspect 8. The feedback parameter selection method according to aspect 6, wherein the step of calculating the effective carrier-to-interference-to-noise power ratio adopts an average-based method, a channel capacity-based method, and a symbol-based mutual information-based method to calculate the effective Carrier to Interference to Noise Power Ratio.

Aspect 9. The feedback parameter selection method according to aspect 6, wherein the step of calculating the effective carrier-to-interference-to-noise power ratio adopts an exponential combination method to calculate the effective carrier-to-interference-to-noise power ratio.

Aspect 10. The feedback parameter selection method according to aspect 6, wherein the effective carrier-to-interference-to-noise power ratio calculation step combines the calculated effective carrier-to-interference-to-noise power ratio with the corresponding precoding matrix, modulation and coding scheme and frequency band Correspondingly stored in the data table, the screening step screens the effective carrier-to-interference-to-noise power ratio by looking up the data table, and the feedback parameter selection step searches for the maximum effective carrier-to-interference by looking up the data table Noise power ratio, and thus determine the combination of precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier-to-interference and noise power ratio.

These and further aspects and features of the invention will become more apparent with reference to the following description and drawings. In the description and drawings, specific embodiments of the invention are disclosed in detail, indicating the manner in which the principles of the invention may be employed. It should be understood that the invention is not thereby limited in scope. The invention embraces many changes, modifications and equivalents within the spirit and scope of the appended claims.

Features described and/or illustrated with respect to one embodiment can be used in the same or similar manner in one or more other embodiments, in combination with, or instead of features in other embodiments .

It should be emphasized that the term "comprising/comprising" when used herein refers to the presence of a feature, integer, step or component, but does not exclude the presence or addition of one or more other features, integers, steps or components.

The embodiment of the present invention combines the selection of the three quantities and uses a unified quantity to evaluate, so that the optimal PMI/MCS/frequency band can be selected, which improves the throughput of the system or the reliability of the link to a certain extent .

Further, the embodiment of the present invention only needs to involve a simple comparison operation by searching the form of a three-dimensional table, so that the circuit design of the receiving end is simpler.

Description of drawings

Figure 1 shows a typical MIMO-OFDM system with feedback;

Fig. 2 shows a feedback parameter selection device according to an embodiment of the present invention;

Fig. 3 shows the flowchart of calculating ECINR according to an embodiment of the present invention;

Fig. 4 shows the flowchart of calculating ECINR according to another embodiment of the present invention;

Figure 5 shows an example of an ECINR_BLER graph;

Fig. 6 has provided the schematic flowchart of the processing that the screening unit carries out according to an embodiment of the present invention;

Figure 7 shows a feedback parameter selection method according to an embodiment of the present invention; and

Fig. 8 shows a schematic relationship between CINR and symbol ratio for different modulation schemes.

Detailed ways

The implementation of the present invention will be described in detail below in conjunction with the accompanying drawings.

FIG. 2 shows a feedback parameter selection device according to an embodiment of the present invention, which can be used as the feedback parameter selection unit 111 shown in FIG. 1 . As shown in FIG. 2 , the feedback parameter selection unit according to an embodiment of the present invention includes an ECINR calculation unit 201 , an MCS threshold unit 202 , a screening unit 203 , and a joint search unit 204 .

The ECINR calculation unit 201 calculates a plurality of ECINR (effective carrier to interference and noise power ratio) values corresponding to various combinations of PMI, MCS and BAND according to the frequency domain channel estimated by the receiver through the channel estimation module. Among them, ECINR is used to represent the channel link quality, and its calculation can be realized by using the method of index combination and the method based on symbolic mutual information. In one embodiment, for the method of index consolidation, it can be implemented, for example, by using the following formula (1):

$\mathrm{<span\; class="notranslate">\; ECINR</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&beta;</span>}\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}}\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; CINR</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Where N is the total number of subcarriers included in a frequency band, n is the serial number of the subcarriers in the frequency band, β is a parameter associated with the MCS, and different β is used to calculate the ECINR value for different MCSs. CINR _n is the CINR value corresponding to the nth subcarrier in the frequency band, and different CINR values can be obtained by using different precoding matrices. All methods known to those skilled in the art can be used for CINR value calculation. In this way, in the process of calculating the ECINR, different ECINR values can be obtained according to different BAND, MCS and precoding matrix.

Taking the case of 2 transmitting antennas and 2 receiving antennas as an example, it is assumed that the channel response on the kth subcarrier is as shown in the following formula (2).

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 11</span>}}& {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 12</span>}}\\ {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}& {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}\end{array}\right]<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

表示第k个子载波上第j根发送天线到第i根接收天线的信道响应。在多天线传输方案中，根据信道状况，会分成多种Rank(秩)。Rank表征了单位天线单位时间/子载波上传送的信息符号数，不同的Rank对应的方式不同。例如，Rank-1在多个天线上传输的同样的信息，Rank-2在多个天线上传输不同的信息。in,

Indicates the channel response from the j-th transmit antenna to the i-th receive antenna on the k-th subcarrier. In the multi-antenna transmission scheme, according to channel conditions, it will be divided into multiple Ranks. Rank represents the number of information symbols transmitted per antenna unit time/subcarrier, and different Ranks correspond to different methods. For example, Rank-1 transmits the same information on multiple antennas, while Rank-2 transmits different information on multiple antennas.

则等效信道表达式为：For Rank-1: Let the l-th precoding vector in the codebook be

Then the equivalent channel expression is:

在接收端采用最大比合并，则相应的CINR表达式为：

The maximum ratio combining is adopted at the receiving end, and the corresponding CINR expression is:

Among them, l is the index of the precoding vector in the codebook, k represents the subcarrier number, and δ2 represents the Gaussian white noise power.

则等效信道表达式为：For Rank-2: Let the l-th precoding vector in the codebook be

Then the equivalent channel expression is:

${\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 11</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 11</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 12</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}& {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 11</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 12</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; 12</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}\\ {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 11</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}& {\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 12</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}\end{array}\right]$

则相应的CINR表达式为：

其中[A]_i，j表示矩阵A中第(i，j)个元素。The minimum mean square error (MMSE, Minimum Mean Square Error) detection is used at the receiving end, and the detection matrix is

Then the corresponding CINR expression is:

Where [A] _{i, j} represents the (i, j)th element in matrix A.

For Rank-1: $\mathrm{ECINR}(\mathrm{band},\mathrm{mcs},\mathrm{pmi})=-{\mathrm{\&beta;}}_{\mathrm{mcs}}\ln \left(\frac{1}{N}\underset{\mathrm{no}=\mathrm{band}\left(1\right)}{\overset{\mathrm{band}\left(N\right)}{\mathrm{\&Sigma;}}}{e}^{-\left(\frac{\mathrm{CINR}(\mathrm{pmi},\mathrm{no})}{{\mathrm{\&beta;}}_{\mathrm{mcs}}}\right)}\right)$

For Rank-2: $\mathrm{ECINR}(\mathrm{band},\mathrm{mcs},\mathrm{pmi})=-{\mathrm{\&beta;}}_{\mathrm{mcs}}\ln \left(\frac{1}{2N}\underset{\mathrm{no}=\mathrm{band}\left(1\right)}{\overset{\mathrm{band}\left(N\right)}{\mathrm{\&Sigma;}}}(e^{-\left(\frac{{\mathrm{CINR}}_1(\mathrm{pmi},\mathrm{no})}{{\mathrm{\&beta;}}_{\mathrm{mcs}}}\right)}+e^{-\left(\frac{{\mathrm{CINR}}_2(\mathrm{pmi},\mathrm{no})}{{\mathrm{\&beta;}}_{\mathrm{mcs}}}\right)})\right)$

In this way, by changing the frequency band and MCS by fixing the PMI, multiple ECINRs corresponding to one fixed PMI can be obtained. Then, by changing the PMI, multiple ECINRs corresponding to the changed PMI can be obtained. By repeating this process, multiple sets of ECINRs respectively corresponding to each PMI can be obtained.

FIG. 3 shows a schematic flowchart of an exemplary method for the ECINR calculating unit 201 to calculate multiple ECINRs corresponding to various combinations of PMI, MCS and BAND.

As shown in Figure 3, at first, in step S301, carry out initialization, promptly MCS, PMI and frequency band are all set as the first kind (in this embodiment, make the index value mcs=0 of MCS, PMI and frequency band, pmi= 0 and band=0). Then in step S302, calculate the CINR (pmi, band(n)) of each subcarrier of the current frequency band, and thereby calculate the ECINR of the current frequency band, then in step S303, increase band, promptly specify to the next frequency band, and in step S304 , judging whether the calculations for all frequency bands have been completed for the current PMI and MCS, that is, judging whether band=B, where B is the total number of frequency bands of the channel. If the calculations for all frequency bands have not been completed (step S304, No), return to step S302 to calculate the ECINR for the next frequency band. If have finished computing (step S304, yes) for all frequency bands, then enter step S305, increase mcs, promptly point to next MCS, and judge in step S306 whether computing has been carried out for all MCS, promptly judge whether mcs is equal to M , where M is the total number of MCS species. If it is judged that calculations have not been performed on all MCSs (step S306, No), then return to step S302 to calculate the ECINR for MCSs. If it is judged that the calculations to all MCSs have been completed (step S306, yes), then enter step S307, increase pmi, promptly point to the next PMI, and judge in step S308 whether calculations have been carried out for all PMIs, i.e. judge Is pmi equal to P, where P is the total number of PMI. If it is judged that calculations have not been performed on all PMIs (step S308, No), return to step S302, and repeat the above steps S302-S308 for this PMI. If it is judged that the calculations on all PMIs have been completed (step S308, Yes), all calculated ECINRs are returned, and the processing ends.

The above description is only exemplary, and a plurality of ECINRs corresponding to each combination of PMI, MCS, and frequency band usable by the receiver may be calculated in a different order. Fig. 4 shows a flow chart of calculating ECINR according to another embodiment of the present invention.

As shown in Figure 4, first, in step S401, initialization is performed, that is, the MCS, PMI and frequency band are all set as the first type (in this embodiment, the index values of MCS, precoding matrix and frequency band mcs=0, pmi=0 and band=0). Then in step S402, calculate the CINR (pmi, band(n)) of each subcarrier of the current frequency band, and calculate the ECINR of the current frequency band in step S403, then in step S404, increase mcs, promptly specify to the next MCS, and Step S405, judging whether the calculations for all MCSs have been completed for the current frequency band, that is, judging whether mcs=M, where M is the total number of mcs that the receiver can use. If the calculations for all MCSs have not been completed (step S405, No), return to step S403 to calculate the ECINR of the current frequency band for the next MCS. If have finished computing (step S405, yes) for all MCSs, then enter step S406, increase band, promptly point to next frequency band, and judge in step S407 whether computing has been carried out for all frequency bands, promptly judge whether band is equal to B , where B is the total number of frequency bands of the channel. If it is determined that calculations have not been performed on all frequency bands (step S407, No), return to step S402 to perform CINR calculations for each subcarrier in the next frequency band. If it is judged that the computing to all frequency bands has been completed (step S407, yes), then enter step S408, increase pmi, promptly point to the next PMI, and judge whether computing has been carried out for all PMIs in step S409, promptly judge Is pmi equal to P, where P is the total number of PMI. If it is judged that all PMIs have not been calculated (step S409, No), then return to step S402, and repeat the above steps S402-S409 for this PMI. If it is judged that the calculations on all PMIs have been completed (step S409, Yes), all calculated ECINRs are returned, and the processing ends.

In this way, as shown in formula 3, different ECINR values can be obtained according to different frequency bands, MCS and PMI.

$\mathrm{<span\; class="notranslate">\; ECINR</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; mcs</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; pmi</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}}\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>}{\overset{\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; CINR</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; pmi</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

The calculated result is a three-dimensional table with corresponding ECINR elements. For example, the three-dimensional table can be expressed as:

Table 1

Band Index MCS index PMI index ECINR value Band Index 1 MCS index 1 PMI index 1 value 1 Band Index 1 MCS index 1 PMI index 2 value 2 ... ... Band Index 1 MCS index 2 PMI index 1 Value P+1 ... ... ... Band Index 2 MCS index 1 PMI index 1 Value P×M+1 ... ... ... Band Index N MCS index M PMI index P Value P×M×N

The table can be stored in the storage device of the receiver or in a dedicated register.

The above table is stored as an index, and another table is required to associate the index with the indexed content. In addition, the content of the index can also be directly stored in the table without using an index. For example, you can change the MCS index column to MCS column, and replace MCS index 1 with QPSK 1/2, replace MCS index 2 with QPSK 3/4, and so on.

In addition, the ECINR can be calculated using a method based on symbolic mutual information or the like.

When using the method based on symbol information (Symbol information, SI) to calculate ECINR, it can be based on the following formula (6):

$\mathrm{ECINR}(\mathrm{band},\mathrm{mcs},\mathrm{pmi})=\frac{1}{N}\underset{\mathrm{no}=\mathrm{band}\left(1\right)}{\overset{\mathrm{band}\left(N\right)}{\mathrm{\&Sigma;}}}\mathrm{Si}(\mathrm{pmi},\mathrm{band}\left(\mathrm{no}\right))$ (6)

$<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}}\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>}{\overset{\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; CINR</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; pmi</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; band</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

Among them, γ _mcs is the mapping function from CINR to SI, which varies with the modulation mode. Fig. 8 shows a schematic relationship between CINR and SI for different modulation schemes. Those skilled in the art who have benefited from the description of the previous embodiments of the present invention can conceive a flowchart similar to that of FIG. 3 and FIG. 4 according to Equation 6, so no more detailed description will be made here.

The MCS threshold unit 202 obtains the ECINR threshold corresponding to each MCS, and the MCS threshold unit 202 can select strategies according to different MCSs (such as maximizing throughput, target BLER/BER (block error rate/bit error rate) criterion, considering the target of HARQ BLER/BER criteria), so as to calculate the corresponding ECINR thresholds of different MCS.

The ECINR threshold can be calculated using the formula. For example, when the BLER does not exceed 10%, it can be calculated according to the following formula.

$\mathrm{<span\; class="notranslate">\; Selected</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; mcs</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; mcs</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; MCS</span>}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; BLER</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; ECINR</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; BLER</span>}}_{\mathrm{<span\; class="notranslate">\; mcs</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; ECINR</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; \%</span><span\; class="notranslate">\; )</span>$

Among them, selected_mcs is a specific MCS method, and arg_max is a mathematical expression form, which means to seek the maximum. In the above formula, it specifically means to find the MCS set that satisfies BLER<10%, and make the expression the maximum mcs. R _mcs refers to the symbol rate corresponding to mcs. BLER _mcs (ECINR) refers to the BLER corresponding to mcs, ECINR.

In addition, the ECINR threshold corresponding to the MCS can be determined according to the requirements of the BLER in conjunction with the ECINR_BLER diagram (obtained by pre-simulation).

Figure 5 shows an example of the ECINR_BLER map. As shown in Figure 5, when the BLER is required to be less than 10%, the threshold is about 16 for 64QAM 2/3.

In addition, the ECINR threshold corresponding to each MCS may also be determined in advance according to each criterion, and stored in a memory. In this case, the MCS threshold unit 202 may be a storage unit. Assuming that the system has a total of 8 types of MCS, the following table 2 can be obtained, for example:

Table 2

MCS index MCS ECINR threshold 1 QPSK 1/2 T ₁ 2 QPSK 3/4 T ₂ 3 16QAM 1/2 T ₃ 4 16QAM 3/4 T ₄ 5 64QAM 1/2 T ₅ 6 64QAM 2/3 T ₆ 7 64QAM 3/4 T ₇ 8 64QAM 5/6 T ₈

The meaning of the threshold is that only when the measured ECINR value is greater than the corresponding threshold, the corresponding MCS mode can be used for transmission.

The MCS threshold unit 202 may also be an input unit, through which the threshold values corresponding to each MCS are input.

The screening unit 203 uses the MCS_ECINR threshold table obtained by the MCS threshold unit 202 to screen the three-dimensional ECINR table calculated by the ECINR calculation unit 201 . The screening unit 203 is mainly used to remove unreasonable elements in the ECINR three-dimensional table. According to the threshold table obtained by the MCS threshold unit 202, the corresponding MCS can only be supported if the ECINR value meets a certain requirement. Therefore, records in the three-dimensional table whose ECINR value is insufficient to support the corresponding MCS need to be removed.

Fig. 6 shows a schematic flowchart of the processing performed by the screening unit according to an embodiment of the present invention. First, in step S601, the first record is taken out from the ECINR three-dimensional table, and then in step S602, the ECINR value of the record is compared with the record in the MCS_ECINR threshold table that has the same MCS index as the MCS index in the first record ECINR threshold for comparison. If it is less than the threshold value (step S602, No), then mark and delete the record in step S603, and judge in step S604 whether all the records in the three-dimensional ECINR table have been processed. If all the records in the ECINR three-dimensional table have not been processed (step S604, No), then take out the next record in the ECINR three-dimensional table, and return to step S602, and repeat steps S602-S605 for the next record. On the other hand, if in step S602, it is judged that the currently recorded ECINR value is less than the threshold value, then go directly to step S604. And if it is determined in step S604 that all the records in the ECINR three-dimensional table have been processed, the processing ends.

Although the above screening of ECINR is performed before selecting the maximum ECINR, it can also be performed after the selection of the maximum ECINR. For example, after the maximum ECINR is selected, it is judged whether the maximum ECINR is greater than the ECINR threshold corresponding to the MCS corresponding to the maximum ECINR, and screening is performed.

The joint search unit 204 searches the three-dimensional table screened by the screening unit 203 for the record with the largest ECINR value, and selects the PMI/MCS/frequency band value corresponding to the record as the final PMI/MCS/frequency band value.

Fig. 7 shows a feedback parameter selection method according to an embodiment of the present invention. As shown in FIG. 7 , first, in step S701 , a plurality of ECINRs corresponding to combinations of PMI, MCS, and frequency bands that can be used by the receiver are calculated. Then in step S702, these ECINRs are screened according to the ECINR threshold values corresponding to each MCS, and finally in step S703, the maximum value among the screened ECINRs is obtained, and the combination of PMI, MCS and frequency band corresponding to the maximum value Determined as the feedback parameter combination.

The above description of the embodiments of the present invention is only exemplary, and the purpose is to enable those skilled in the art to have a clear understanding of the implementation of the embodiments of the present invention, and those devices involved in implementing the embodiments of the present invention (such as other components necessary for the operation of the receiver) but are clear to those skilled in the art.

The above devices and methods in the embodiments of the present invention can be implemented by hardware (such as field programmable logic components, etc.), and can also be realized by combining hardware with software (such as a microchip with memory for executing programs, etc.). The present invention relates to such a computer-readable program that, when the program is executed by a logic component, enables the logic component to realize the above-mentioned device or constituent component, or enables the logic component to realize the above-mentioned various methods or steps. The present invention also relates to a storage medium for storing the above program, such as hard disk, magnetic disk, optical disk, DVD, flash memory and the like.

The present invention has been described above in conjunction with specific embodiments, but those skilled in the art should be clear that these descriptions are all exemplary and not limiting the protection scope of the present invention. Those skilled in the art can make various variations and modifications to the present invention according to the spirit and principle of the present invention, and these variations and modifications are also within the scope of the present invention.

Claims (10)

1. A feedback parameter selection device for a receiver, wherein the feedback parameter selection device comprises: An effective carrier-to-interference-to-noise power ratio calculation unit, which is used to calculate a plurality of effective carrier-to-interference-to-noise power ratios corresponding to each combination of a precoding matrix, a modulation coding scheme and a frequency band that can be selected by the receiver; The screening unit is configured to screen the plurality of effective carrier-to-interference-to-noise power ratios according to the effective carrier-to-interference-to-noise power ratio threshold value corresponding to each modulation and coding scheme; and The feedback parameter selection unit obtains the largest effective carrier-to-interference-to-noise power ratio among the screened effective carrier-to-interference-to-noise power ratios, and combines the precoding matrix, modulation and coding scheme, and frequency band corresponding to the largest effective carrier-to-interference-to-noise power ratio It is determined as a combination of a precoding matrix to be fed back, a modulation and coding scheme, and a frequency band. 2. The feedback parameter selection device according to claim 1, wherein the feedback parameter selection device further comprises a modulation and coding scheme threshold unit, and the modulation and coding scheme threshold unit is used to obtain the effective carrier corresponding to each modulation and coding scheme Interference noise power ratio threshold. 3 . The feedback parameter selection device according to claim 1 , wherein the effective carrier-to-interference-to-noise power ratio calculation unit calculates the effective carrier-to-interference-to-noise power ratio by a method based on symbol mutual information. 4 . The feedback parameter selection device according to claim 1 , wherein the effective carrier-to-interference-to-noise power ratio calculation unit adopts an exponential combination method to calculate the effective carrier-to-interference-to-noise power ratio. 5. The feedback parameter selection device according to claim 1, wherein the effective carrier-to-interference-to-noise power ratio calculation unit calculates the effective carrier-to-interference-to-noise power ratio and the combination of the corresponding precoding matrix, modulation and coding scheme and frequency band Correspondingly stored in the data table, the screening unit screens the effective carrier-to-interference-to-noise power ratio by looking up the data table, and the feedback parameter selection unit searches for the largest effective carrier by looking up the data table Interference and noise power ratio, and thus determine the combination of precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier to interference and noise power ratio. 6. A feedback parameter selection method for a receiver, wherein the feedback parameter selection method comprises: An effective carrier-to-interference-to-noise power ratio calculation step, which is used to calculate a plurality of effective carrier-to-interference-to-noise power ratios corresponding to each combination of a precoding matrix, a modulation coding scheme and a frequency band that can be selected by the receiver; The screening step is to screen the plurality of effective carrier-to-interference noise power ratios according to the effective carrier-to-interference noise power ratio threshold value corresponding to each modulation and coding scheme; and The feedback parameter selection step is to obtain the maximum effective carrier-to-interference-to-noise power ratio in the screened effective carrier-to-interference-to-noise power ratio, and the combination of the precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier-to-interference-to-noise power ratio The choice is a combination of precoding matrix, modulation coding scheme and frequency band to be fed back. 7. The feedback parameter selection method according to claim 6, wherein the feedback parameter selection step also includes a modulation and coding scheme threshold acquisition step, and the modulation and coding scheme threshold acquisition step is used to obtain the corresponding modulation and coding scheme The effective carrier-to-interference-to-noise power ratio threshold. 8. The feedback parameter selection method according to claim 6, wherein the step of calculating the effective carrier-to-interference-to-noise power ratio adopts a method based on symbol mutual information to calculate the effective carrier-to-interference-to-noise power ratio. 9. The feedback parameter selection method according to claim 6, characterized in that, the effective carrier-to-interference-to-noise power ratio calculation step adopts an exponential combination method to calculate the effective carrier-to-interference-to-noise power ratio. 10. The feedback parameter selection method according to claim 6, wherein the effective carrier-to-interference-to-noise power ratio calculation step calculates the effective carrier-to-interference-to-noise power ratio and the combination of the corresponding precoding matrix, modulation and coding scheme and frequency band Correspondingly stored in the data table, the screening step screens the effective carrier-to-interference-to-noise power ratio by looking up the data table, and the feedback parameter selection step searches for the maximum effective carrier-to-interference by looking up the data table Noise power ratio, and thus determine the combination of precoding matrix, modulation and coding scheme and frequency band corresponding to the maximum effective carrier-to-interference and noise power ratio.

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