CN102025456A - Feedback parameter selecting device and feedback parameter selecting method - Google Patents
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Abstract
The invention relates to a feedback parameter selecting device and a feedback parameter selecting method. The feedback parameter selecting device is used for a receiver, and comprises an effective carrier wave interference noise power ratio calculating unit for calculating a plurality of effective carrier wave interference noise power ratios corresponding to the combinations of pre-coding matrixes, modulation coding schemes and frequency bands which can be selected by the receiver, a screening unit for screening the plurality of effective carrier wave interference noise power ratios according to the threshold values of the effective carrier wave interference noise power ratios corresponding to the modulation coding schemes, and a feedback parameter selecting unit for acquiring the maximal effective carrier wave interference noise power ratio among the screened effective carrier wave interference noise power ratios, and determining the combination of the pre-coding matrix, the modulation coding scheme and the frequency band corresponding to the maximal effective carrier wave interference noise power ratio as the combination to be fed back of the pre-coding matrix, the modulation coding scheme and the frequency band.
Description
Technical Field
The present invention relates to wireless communications, and more particularly, to a wireless receiver using a closed-loop Multiple Input Multiple Output (MIMO) technique.
Background
In a wireless communication system, a transmitting end and a receiving end are provided with a plurality of antennas, which is called a multiple-input multiple-output technique. With different modes, the MIMO technology can effectively improve the reliability and capacity of wireless communication. Orthogonal Frequency Division Multiplexing (OFDM) can be effectively combined with MIMO technology by dividing a Frequency selective fading channel into independent flat fading channels to form a MIMO-OFDM system, which is widely used in super 3G and 4G wireless communication systems.
In the case where the channel is known at the transmitting end, the system performance can be improved by performing some pre-processing. In the MIMO technique, the link quality and the transmission rate can be improved by multiplying the transmission data by a specific matrix according to the channel condition, and this technique is called a precoding technique. Generally, the channel state information needs to be estimated and fed back to the transmitting end by the receiving end. However, no matter the channel state is fed back directly or the calculated precoding matrix is fed back, the feedback quantity is very large for the OFDM multi-carrier and MIMO multi-antenna systems, and the systems cannot bear the feedback quantity. Therefore, a codebook-based feedback method is adopted in a practical system. In this way, the same set of precoding matrices is stored at both the transmitting end and the receiving end, and this set is called a codebook. Then, channel information is estimated at a receiving end, an optimal Matrix is searched in a codebook according to certain criteria according to the channel information to serve as a Precoding Matrix, and the transmitting end can complete Precoding only by feeding back a selected Precoding Matrix Index (PMI) so as to effectively reduce Precoding feedback information bits.
In the MIMO-OFDM wireless communication system, a channel changes in three dimensions of space, frequency and time, so that a great deal of uncertainty exists in the communication process. On one hand, in order to improve the system throughput, high-order modulation with higher transmission rate and less redundant error correcting codes are adopted for communication, so that the system throughput is really improved greatly when the signal-to-noise ratio of a wireless fading channel is ideal, but when the channel is in deep fading, the reliable and stable communication cannot be guaranteed. On the other hand, in order to ensure the reliability of communication, low-order modulation with a low transmission rate and a large redundant error correction code are adopted for communication, even if the reliability of communication can be ensured when a wireless channel is in deep fading, when the signal-to-noise ratio of the channel is high, the improvement of the throughput of the system is restricted due to the low transmission rate, and therefore resource waste is caused. Therefore, the throughput and reliability of the system are comprehensively considered, and an Adaptive Modulation Coding (AMC) technology is introduced on the basis, and the basic principle is to keep the transmission power of the transmitting end unchanged, and adaptively change the Modulation and Coding mode according to the state information of the channel, so as to obtain the maximum throughput under different channel states. In a practical system, channel information is generally estimated at a receiving end, and then a suitable Coding and Modulation Scheme (MCS) is selected according to a certain error probability requirement, and information indicating the corresponding MCS is fed back to a transmitting end to implement the AMC technology.
One of the characteristics of MIMO-OFDM is the presence of frequency selectivity. In a multi-user scenario, the different environments of the users may make some users have better channel conditions in some frequency bands, while other users have worse channel conditions in the same frequency bands. If resource scheduling is performed by using different frequency selectivities of different users, and the most suitable frequency resource is allocated to the users for transmission, the system capacity can be effectively improved. In the MIMO-OFDM system actually adopting frequency selective scheduling, generally, the entire frequency resource may be divided into several frequency BANDs (BANDs), then the channel conditions of the users on the respective frequency BANDs are measured, and the frequency BAND with the best channel condition is selected to be allocated to the users, thereby implementing frequency selective scheduling. Similar to PMI and MCS, channel information is generally estimated at the receiving end and measured for a band to be selected, and then the best band is selected, and information (e.g., sequence number) indicating the band is fed back to the transmitting end.
That is, 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 transmitting end.
This problem is illustrated below with a typical MIMO-OFDM system with feedback as shown in fig. 1.
As shown in fig. 1, for a MIMO-OFDM system with Nt transmit antennas and Nr receive antennas, single-layer or multi-layer source data is first coded and modulated by MCS fed back from the receiver via coding modulation section 101 at subcarrier K, and then enters space-time coding section 102, and space-time coding section 102 forms s data streams using band information fed back from the receiver. A precoding matrix W is passed through in precoding section 103iThe multiplication results in the formation of transmitted symbols. Then, the data streams of the users are scheduled to corresponding sub-channels in the sub-carrier allocation mapping unit 104 and mapped on the physical sub-carriers according to a certain manner. Formed frequency domain multi-carrier signalThe numbers are IFFT-processed and cyclic prefix added at IFFT unit 105, and then transmitted by antennas via radio frequency front end (RF) 106.
At the receiver, the FFT unit 108 performs FFT on the signal received from the radio frequency front end 107 through the antenna, and the FFT-ed signal is demapped by the demapping unit 109.
Channel estimation is performed at the channel estimation unit 110. In the feedback parameter selection unit 111, the selection of the precoding matrix, the frequency band, and the MCS is completed based on the channel estimation result of the channel estimation performed at the channel estimation unit 110. The selected information indicating precoding matrix, MCS, frequency band is fed back by the receiver to the transmitter. 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 coding unit 113 performs demodulation and channel decoding to recover transmission data.
Therefore, in MIMO-OFDM system with feedback, the performance of the system depends on whether the selection of precoding matrix, band and MCS by the receiver corresponds to the channel conditions. In the course of studying the present invention, the inventor found that in the conventional practice, the precoding matrix, the frequency BAND, and the MCS are selected in a certain order, and the selection of the precoding matrix, the frequency BAND, and the MCS is independent from each other, but actually the three are related to each other, so that the precoding matrix, the BAND, and the MCS selected in the prior art are not optimized.
Disclosure of Invention
Embodiments of the present invention have been made keeping in mind the above problems occurring in the prior art, and are intended to obviate or mitigate one or more of the problems of the prior art, and to provide at least one advantageous alternative.
In order to achieve the object of the present invention, the present invention provides the following aspects.
an effective carrier interference noise power ratio calculation unit for calculating a plurality of effective carrier interference noise power ratios respectively corresponding to each combination of a precoding matrix, a modulation coding scheme and a frequency band which can be selected by a 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
and a feedback parameter selection unit which acquires the maximum 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 maximum 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.
an effective carrier to interference plus noise power ratio calculation step of calculating a plurality of effective carrier to interference plus 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 a receiver;
a screening step, wherein the effective carrier interference noise power ratios are screened according to the effective carrier interference noise power ratio threshold values corresponding to the modulation coding schemes; and
and a feedback parameter selection step of acquiring the maximum effective carrier to interference and noise power ratio among the screened effective carrier to interference and noise power ratios, and selecting the combination of the precoding matrix, the modulation coding scheme and the frequency band corresponding to the maximum effective carrier to interference and noise power ratio as the combination of the precoding matrix, the modulation coding scheme and the frequency band to be fed back.
Aspect 7 and the method for selecting feedback parameters according to aspect 6 are characterized in that the step of selecting feedback parameters further includes a step of obtaining a modulation and coding scheme threshold, and the step of obtaining the modulation and coding scheme threshold is used for obtaining an effective carrier to interference plus noise power ratio threshold corresponding to each modulation and coding scheme.
Aspect 9 is the feedback parameter selection method according to aspect 6, wherein the effective carrier-to-interference-and-noise power ratio calculation step calculates the effective carrier-to-interference-and-noise power ratio by using an exponential combining method.
These and further aspects and features of the present invention will become more apparent with reference to the following description and the accompanying drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of the manner in which the principles of the invention may be employed. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended. The invention includes many variations, modifications and equivalents within the spirit and scope of the appended claims.
Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments, in combination with or instead of the features of the other embodiments.
It should be emphasized that the term "comprises/comprising" when used herein, is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps or components.
The embodiment of the invention combines the selection of three quantities and adopts uniform quantity to evaluate, thereby selecting the optimized PMI/MCS/frequency band and improving 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 the three-dimensional table, thereby making the circuit design of the receiving end simpler.
Drawings
FIG. 1 illustrates a typical MIMO-OFDM system with feedback;
FIG. 2 illustrates a feedback parameter selection apparatus according to an embodiment of the present invention;
FIG. 3 illustrates a flow chart for calculating ECINR in accordance with an embodiment of the present invention;
FIG. 4 illustrates a flow chart for calculating ECINR according to another embodiment of the present invention;
fig. 5 shows an example of an ECINR _ BLER map;
FIG. 6 presents a schematic flow diagram of a process performed by a screening unit according to an embodiment of the present invention;
FIG. 7 illustrates a feedback parameter selection method according to an embodiment of the present invention; and
fig. 8 shows an exemplary CINR versus symbol ratio for different modulation schemes.
Detailed Description
The following detailed description of the embodiments of the invention refers to the accompanying drawings.
Fig. 2 shows a feedback parameter selection apparatus according to an embodiment of the present invention, which may 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 filtering 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, respectively, from the frequency domain channel estimated by the receiver through the channel estimation module. Where ECINR is used to characterize the channel link quality, its calculation can be implemented by using an exponential combining method and a symbol mutual information-based method, etc. In one embodiment, for the method of index combining, it can be implemented, for example, by using the following formula (1):
where N is the total number of subcarriers contained in a band, N is the number of subcarriers within the band, β is a parameter associated with the MCS, and different β values are used for calculating ECINR values for different MCSs. CINRnThe CINR value corresponding to the nth subcarrier in the frequency band, and different CINR values can be obtained by adopting different precoding matrices. The CINR value calculation can be performed using all methods known to those skilled in the art. Thus, in the process of calculating ECINR, different ECINR values can be obtained according to different BAND, MCS and precoding matrixes.
Taking the case of 2 transmit antennas and 2 receive antennas as an example, it is assumed that the channel response on the k-th subcarrier is as shown in the following equation (2).
Wherein,
indicating the channel response from the jth transmit antenna to the ith receive antenna on the kth subcarrier. In the multi-antenna transmission scheme, a plurality of ranks are classified according to channel conditions. The Rank represents the number of information symbols transmitted on unit antenna unit time/subcarrier, and different Rank corresponding modes are different. For example, Rank-1 transmits the same information over multiple antennas, and Rank-2 transmits different information over multiple antennas.
For Rank-1: let the first precoding vector in the codebook be
The equivalent channel expression is:
where l is the index of the precoding vector in the codebook, k denotes the subcarrier number, and δ 2 denotes the gaussian white noise power.
For Rank-2: let the first precoding vector in the codebook be
The equivalent channel expression is:
minimum Mean Square Error (MMSE) detection is adopted at a receiving end, and a detection matrix is
The corresponding CINR expression is:
wherein [ A ] is]i，jRepresentation matrixThe (i, j) th element in A.
For Rank-1: <math><mrow><mi>ECINR</mi><mrow><mo>(</mo><mi>band</mi><mo>,</mo><mi>mcs</mi><mo>,</mo><mi>pmi</mi><mo>)</mo></mrow><mo>=</mo><mo>-</mo><msub><mi>β</mi><mi>mcs</mi></msub><mi>ln</mi><mrow><mo>(</mo><mfrac><mn>1</mn><mi>N</mi></mfrac><munderover><mi>Σ</mi><mrow><mi>n</mi><mo>=</mo><mi>band</mi><mrow><mo>(</mo><mn>1</mn><mo>)</mo></mrow></mrow><mrow><mi>band</mi><mrow><mo>(</mo><mi>N</mi><mo>)</mo></mrow></mrow></munderover><msup><mi>e</mi><mrow><mo>-</mo><mrow><mo>(</mo><mfrac><mrow><mi>CINR</mi><mrow><mo>(</mo><mi>pmi</mi><mo>,</mo><mi>n</mi><mo>)</mo></mrow></mrow><msub><mi>β</mi><mi>mcs</mi></msub></mfrac><mo>)</mo></mrow></mrow></msup><mo>)</mo></mrow></mrow></math>
for Rank-2: <math><mrow><mi>ECINR</mi><mrow><mo>(</mo><mi>band</mi><mo>,</mo><mi>mcs</mi><mo>,</mo><mi>pmi</mi><mo>)</mo></mrow><mo>=</mo><mo>-</mo><msub><mi>β</mi><mi>mcs</mi></msub><mi>ln</mi><mrow><mo>(</mo><mfrac><mn>1</mn><mrow><mn>2</mn><mi>N</mi></mrow></mfrac><munderover><mi>Σ</mi><mrow><mi>n</mi><mo>=</mo><mi>band</mi><mrow><mo>(</mo><mn>1</mn><mo>)</mo></mrow></mrow><mrow><mi>band</mi><mrow><mo>(</mo><mi>N</mi><mo>)</mo></mrow></mrow></munderover><mrow><mo>(</mo><msup><mi>e</mi><mrow><mo>-</mo><mrow><mo>(</mo><mfrac><mrow><msub><mi>CINR</mi><mn>1</mn></msub><mrow><mo>(</mo><mi>pmi</mi><mo>,</mo><mi>n</mi><mo>)</mo></mrow></mrow><msub><mi>β</mi><mi>mcs</mi></msub></mfrac><mo>)</mo></mrow></mrow></msup><mo>+</mo><msup><mi>e</mi><mrow><mo>-</mo><mrow><mo>(</mo><mfrac><mrow><msub><mi>CINR</mi><mn>2</mn></msub><mrow><mo>(</mo><mi>pmi</mi><mo>,</mo><mi>n</mi><mo>)</mo></mrow></mrow><msub><mi>β</mi><mi>mcs</mi></msub></mfrac><mo>)</mo></mrow></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>
by thus fixing the PMI and changing the band and MCS, a plurality of ECINR corresponding to one fixed PMI can be obtained. Then, the PMI is changed to obtain a plurality of ECINR corresponding to the changed PMI, and by repeating such a process, a plurality of sets of ECINR corresponding to the PMIs can be obtained.
Fig. 3 shows a schematic flow diagram of an exemplary method for the ECINR calculation unit 201 to calculate a plurality of ECINRs corresponding to various combinations of PMI, MCS, and BAND, respectively.
As shown in fig. 3, first, in step S301, initialization is performed such that MCS, PMI, and band are all set to the first type (in the present embodiment, MCS, PMI, and band index MCS is set to 0, PMI is set to 0, and band is set to 0). Then in step S302, CINR (PMI, band (n)) of each subcarrier of the current band is calculated, and thereby ECINR of the current band is calculated, and then in step S303, the band is added, i.e., designated to the next band, and in step S304, it is determined whether the operation for all bands has been completed for the current PMI and MCS, i.e., it is determined whether the band is B, which is the total number of bands of the channel. If the operation for all the bands has not been completed (no at step S304), the process returns to step S302, and ECINR for the next band is calculated. If the operations for all the bands have been completed (step S304, YES), the process proceeds to step S305, MCS is incremented, i.e., the next MCS is pointed to, and it is determined in step S306 whether the operations have been performed for all the MCSs, i.e., whether MCS is equal to M, where M is the total number of MCS categories. If it is determined that all the MCSs have not been calculated (no in step S306), the process returns to step S302 to calculate ECINR for the MCSs. If it is determined that the operations on all the MCSs have been completed (step S306, yes), the process proceeds to step S307, where PMI is incremented, i.e., pointed to the next PMI, and it is determined in step S308 whether operations have been performed on all the PMIs, i.e., whether PMI is equal to P, where P is the total number of PMIs. If it is determined that all PMIs have not been operated (no at step S308), the process returns to step S302, and the above steps S302 to S308 are repeated for the PMIs. If it is judged that the operations on all the PMIs have been completed (yes at step S308), all the ECINR calculated are returned, and the processing is ended.
The above description is merely exemplary, and a plurality of ECINRs corresponding to respective combinations of PMI, MCS, and frequency band that can be used by the receiver can be calculated in different orders. FIG. 4 shows a flow chart for calculating ECINR according to another embodiment of the present invention.
As shown in fig. 4, first, in step S401, initialization is performed such that MCS, PMI, and band are all set to the first type (in the present embodiment, MCS, precoding matrix, and band index values MCS, PMI, and band are set to 0). Then in step S402, CINR (pmi, band (n)) of each subcarrier of the current band is calculated, and in step S403, ECINR of the current band is calculated, and then in step S404, MCS is incremented, i.e., assigned to the next MCS, and in step S405, it is determined whether the operation for all MCSs has been completed for the current band, i.e., it is determined whether MCS equals M, where M is the total number of MCS that can be used by the receiver. If the operation for all MCSs has not been completed (step S405, NO), the process returns to step S403, and ECINR of the current band for the next MCS is calculated. If the operation for all MCSs has been completed (step S405, yes), step S406 is entered, the band is increased, i.e. directed to the next band, and it is determined in step S407 whether the operation has been performed for all bands, i.e. whether the band is equal to B, where B is the total number of bands of the channel. If it is determined that the calculation has not been performed for all the frequency bands (no in step S407), the process returns to step S402, and CINR calculation for each subcarrier of the next frequency band is performed. If it is determined that the operations for all the frequency bands have been completed (step S407, yes), the process proceeds to step S408, where PMI is incremented, i.e., pointed to the next PMI, and it is determined in step S409 whether operations have been performed for all the PMIs, i.e., whether PMI is equal to P, where P is the total number of PMIs. If it is determined that all PMIs have not been operated (no at step S409), the process returns to step S402, and the above steps S402 to S409 are repeated for the PMIs. If it is judged that the operations on all the PMIs have been completed (yes at step S409), all the ECINR calculated are returned, and the processing is ended.
Thus, as shown in equation 3, different ECINR values can be obtained according to different frequency bands, MCSs and PMIs.
The result of the calculation is a three-dimensional table with the corresponding ECINR as an element. For example, the three-dimensional table may appear as:
TABLE 1
| Band index | MCS index | PMI indexing | ECINR |
| Band index | |||
| 1 | |
|
|
| |
|
|
|
| ... | ... | ||
| |
|
|
Value P +1 |
| ... | ... | ... | |
| |
|
|
Value P M +1 |
| ... | ... | ... | |
| Band indexN | MCS index M | PMI index P | Value P M N |
The table may be stored in the storage means of the receiver or in a dedicated register.
The above table is stored in an indexed manner, and an additional table is required to associate the index with the indexed content. In addition, the contents of the index may be directly stored in the table without using the index. For example, the MCS index column may be changed to MCS column, MCS index 1 replaced with QPSK 1/2, MCS index 2 replaced with QPSK 3/4, and so on.
In addition, ECINR can be calculated using a method based on mutual symbol information or the like.
When the ECINR is calculated using a Symbol Information (SI) based method, the ECINR may be calculated based on the following formula (6):
wherein gamma ismcsIs a mapping function of CINR to SI, which varies with the modulation scheme. Fig. 8 shows an exemplary relationship of CINR to SI for different modulation schemes. A flow chart similar to that of fig. 3 and 4 can be conceived by those skilled in the art who have the benefit of the description of the previous embodiment of the present invention according to equation 6, and thus will not be described in more detail herein.
The MCS threshold unit 202 obtains the ECINR thresholds corresponding to the MCSs, and the MCS threshold unit 202 may calculate the ECINR thresholds corresponding to the different MCSs according to different MCS selection policies (e.g., a maximum throughput, a target BLER/BER (block error rate/bit error rate) criterion, and a target BLER/BER criterion considering HARQ).
The ECINR threshold may be calculated using a formula. For example, when BLER does not exceed 10%, the calculation can be performed according to the following equation.
Where selected _ MCS is the specific MCS mode and arg _ max isThe mathematical expression form indicates the maximization, and specifically indicates that the BLER < 10% is found in the MCS set in the above formula, and the expression is maximized in MCS. RmcsRefers to the symbol rate corresponding to mcs. BLERmcs(ECINR) refers to BLER corresponding to ECINR for mcs.
In addition, the ECINR _ BLER diagram (obtained by pre-simulation) can be matched, and the ECINR threshold value corresponding to the corresponding MCS is determined according to the BLER requirement.
Fig. 5 shows an example of an ECINR _ BLER map. As shown in fig. 5, when the BLER is required to be less than 10%, the threshold value is about 16 for 64QAM 2/3.
Further, the ECINR thresholds corresponding to the MCSs may be determined in advance based on the criteria and stored in the memory. In this case, the MCS threshold unit 202 may be a storage unit. Assuming that the system has 8 MCS in total, for example, the following table 2 can be obtained:
TABLE 2
| MCS index | | ECINR threshold | |
| 1 | |
|
|
| 2 | |
|
|
| 3 | |
|
|
| 4 | |
|
|
| 5 | |
|
|
| 6 | |
T6 | |
| 7 | |
|
|
| 8 | |
T8 |
The threshold means that only if the measured ECINR value is greater than the corresponding threshold, the corresponding MCS may be used for transmission.
The MCS threshold unit 202 may also be an input unit, and the threshold value corresponding to each MCS is input through the input unit.
The screening unit 203 screens the ECINR three-dimensional table calculated by the ECINR calculating unit 201 by using the MCS _ ECINR threshold table obtained by the MCS threshold unit 202. The screening unit 203 is mainly used for removing unreasonable elements in the ECINR three-dimensional table. According to the threshold table obtained by the MCS threshold unit 202, the corresponding MCS can be supported only when the ECINR value meets a certain requirement, and therefore, the record that the ECINR value in the three-dimensional table is not enough to support the corresponding MCS needs to be removed.
Fig. 6 presents a schematic flow chart of the processing performed by the screening unit according to an embodiment of the invention. First, in step S601, a first record is taken out of the ECINR three-dimensional table, and then in step S602, the ECINR value of the record is compared with the ECINR threshold of the record having the same MCS index as that in the first record in the MCS _ ECINR threshold table. If the value is less than the threshold value (step S602, no), the deletion of the record is marked in step S603, and it is determined whether all records in the ECINR three-dimensional table have been processed in step S604. If all records in the ECINR three-dimensional table have not been processed (step S604, NO), the next record of the ECINR three-dimensional table is taken out, the step S602 is returned, and the steps S602-S605 are repeated for the next record. On the other hand, if in step S602, it is determined that the currently recorded ECINR value is less than the threshold value, the process directly proceeds to step S604. And if it is judged in step S604 that all the records in the ECINR three-dimensional table have been processed, the process is ended.
Although the screening of ECINRs above is performed before the maximum ECINR is selected, it may be performed after the maximum ECINR is selected. For example, after the largest ECINR is selected, it is determined whether the largest ECINR is larger than the ECINR threshold corresponding to the MCS corresponding to the largest ECINR, and the screening is performed.
The joint search unit 204 searches for the record with the largest ECINR value in the three-dimensional table filtered by the filtering unit 203, and selects the PMI/MCS/band value corresponding to the record as the final PMI/MCS/band value.
Fig. 7 illustrates 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 ECINR corresponding to each combination of PMI, MCS, and frequency band that can be used by the receiver are calculated. Then, in step S702, the ECINR is filtered based on the ECINR threshold values corresponding to the MCSs, and finally, in step S703, the maximum value among the filtered ECINR is obtained, and the combination of the PMI, the MCS, and the frequency band corresponding to the maximum value is determined as the parameter combination to be fed back.
The above description of embodiments of the invention is intended to be exemplary only, and is intended to enable those skilled in the art to make clear the implementation of the embodiments of the invention, and other components which are necessary for the operation of the apparatus (e.g., a receiver) involved in implementing the embodiments of the invention, but which are obvious to those skilled in the art, are not described herein.
The above devices and methods according to the embodiments of the present invention may be implemented by hardware (for example, field programmable logic device, etc.), or may be implemented by hardware in combination with software (for example, microchip with memory for executing programs, etc.). The present invention relates to a computer-readable program which, when executed by a logic section, enables the logic section to realize the above-described apparatus or constituent section, or to realize the above-described various methods or steps. The present invention also relates to a storage medium such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, or the like, for storing the above program.
While the invention has been described with reference to specific embodiments, it will be apparent to those skilled in the art that these descriptions are illustrative and not intended to limit the scope of the invention. Various modifications and alterations of this invention will become apparent to those skilled in the art based upon the spirit and principles of this invention, and such modifications and alterations are also within the scope of this invention.
Claims (10)
1. A feedback parameter selection apparatus for a receiver, wherein the feedback parameter selection apparatus 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
and a feedback parameter selection unit which acquires the maximum 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 maximum 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.
2. The feedback parameter selection apparatus according to claim 1, further comprising a modulation and coding scheme threshold unit, where the modulation and coding scheme threshold unit is configured to obtain an effective carrier-to-interference-and-noise power ratio threshold value corresponding to each modulation and coding scheme.
3. The feedback parameter selection device of claim 1, wherein the effective carrier-to-interference-and-noise power ratio calculation unit calculates the effective carrier-to-interference-and-noise power ratio by a method based on mutual symbol information.
4. The feedback parameter selection device of claim 1, wherein the effective carrier-to-interference-and-noise power ratio calculation unit calculates the effective carrier-to-interference-and-noise power ratio by using an exponential combining method.
5. The feedback parameter selection apparatus according to claim 1, wherein the effective carrier-to-interference-and-noise power ratio calculation unit stores the calculated effective carrier-to-interference-and-noise power ratio in a data table in correspondence with a combination of a corresponding precoding matrix, modulation coding scheme, and frequency band, the screening unit screens the effective carrier-to-interference-and-noise power ratio by looking up the data table, and the feedback parameter selection unit finds a maximum effective carrier-to-interference-and-noise power ratio by looking up the data table, and thereby determines a combination of a precoding matrix, a modulation coding scheme, and a 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 plus noise power ratio calculation step of calculating a plurality of effective carrier to interference plus 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 a receiver;
a screening step, wherein the effective carrier interference noise power ratios are screened according to the effective carrier interference noise power ratio threshold values corresponding to the modulation coding schemes; and
and a feedback parameter selection step of acquiring the maximum effective carrier interference noise power ratio among the screened effective carrier interference noise power ratios, and selecting the combination of the precoding matrix, the modulation coding scheme and the frequency band corresponding to the maximum 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.
7. The feedback parameter selection method according to claim 6, wherein the feedback parameter selection step further includes a modulation coding scheme threshold obtaining step, and the modulation coding scheme threshold obtaining step is configured to obtain an effective carrier-to-interference-and-noise power ratio threshold corresponding to each modulation coding scheme.
8. The feedback parameter selection method of claim 6, wherein the effective carrier-to-interference-and-noise power ratio calculating step calculates the effective carrier-to-interference-and-noise power ratio by using a method based on mutual symbol information.
9. The feedback parameter selection method of claim 6, wherein the effective carrier-to-interference-and-noise power ratio calculating step calculates the effective carrier-to-interference-and-noise power ratio by using an exponential combining method.
10. The feedback parameter selection method according to claim 6, wherein the effective carrier-to-interference-and-noise power ratio calculation step stores the calculated effective carrier-to-interference-and-noise power ratio in a data table in correspondence with a combination of a corresponding precoding matrix, modulation coding scheme, and frequency band, the screening step screens the effective carrier-to-interference-and-noise power ratio by looking up the data table, and the feedback parameter selection step finds a maximum effective carrier-to-interference-and-noise power ratio by looking up the data table, and thereby determines a combination of a precoding matrix, a modulation coding scheme, and a frequency band corresponding to the maximum effective carrier-to-interference-and-noise power ratio.
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