KR101139221B1 - Method apparatus of controling cqi for adaptive modulation and coding in ofdma - Google Patents

Abstract

The present invention provides a CQI control method and apparatus for adaptive modulation and coding in an OFDMA system.

The present invention improves the capacity and fairness of the OFDMA system by variably adjusting the size of the subcarrier group rather than the resource allocation for the existing fixed subcarrier group. In addition, it is possible to use uplink radio resources more efficiently, and it is possible to expect better performance than conventional methods with uplink overhead similar to or less than that of existing systems.

Description

TECHNICAL APPARATUS OF CONTROLING CQI FOR ADAPTIVE MODULATION AND CODING IN OFDMA

1 is a diagram showing the structure of the Band-AMC proposed in the IEEE 802.22 WRAN system.

2 is a diagram showing the structure of Scattered-AMC proposed in the IEEE 802.22 WRAN system.

3 is a flowchart illustrating a CQI control method for AMC in an OFDMA system according to an embodiment of the present invention.

4 is a cluster structure for explaining the embodiment of FIG. 3 in more detail.

5 is a diagram illustrating a control information transmission format for feeding back through an uplink channel according to an embodiment of the present invention.

6 is a block diagram illustrating a CQI control apparatus for AMC in an OFDMA system according to an embodiment of the present invention.

7 is a diagram comparing performance and uplink overhead, which is a result performed according to an exemplary embodiment of the present invention, with other methods.

FIG. 8 is a diagram illustrating sector throughput performance, which is a result performed according to an exemplary embodiment of the present invention.

FIG. 9 is a diagram illustrating capacity and fairness performance of each user, which is a result performed according to an exemplary embodiment of the present invention.

The present invention relates to a wireless communication system, and more particularly, to maximize system performance using AMC technology in an OFDMA system, to more efficiently use uplink radio resources, and to reduce uplink feedback information. CQI control method for adaptive modulation and coding and apparatus therefor.

Adaptive Modulation and Coding (AMC) technology that selects an appropriate modulation method and coding rate according to each user's channel environment to provide high quality and high reliability communication even in a poor wireless transmission environment in an OFDMA system for multiple users. This system is used, and this system is called AOFDM (Adaptive OFDM) system.

AMC technology is a link application technique that determines the most suitable transmission scheme among predefined MCS levels according to the change of channel environment.In order to support AMC, the base station must know the channel quality information of the terminal and the channel quality of the terminal An indicator called Channel Quality Indicator (CQI) is used to convey

Looking at the existing AMC algorithm for the AOFDM system, the packet scheduler of the base station needs all subcarrier channel information of the downlink of each terminal to operate at the best performance.

J. Campello proposed an algorithm with optimal performance by feeding back channel information of all subcarriers and selecting an appropriate modulation method for each subcarrier. However, it is impossible to feed back channel information of all subcarriers to an uplink limited control channel. To solve this problem, a method of feedback including a large amount of channel information with a small amount of information has been proposed.

In order to reduce feedback information, T. Keller and L. Hanzo proposed a method of applying subchannel information in block units like Band-AMC, which is a simple block using SBLA (channel block information) for HIPERLAN / 2 system. -wise Loading Algorithm). However, Scattered-AMC sub-channelization of WRAN system requires 4 times as much feedback amount as Band-AMC even with SBLA. Many of the feedback information can operate better AMC technology, but in the uplink side, the overhead of the system has the adverse effect of reducing the spectral efficiency (Spectral Effciency).

The technical problem to be achieved by the present invention for solving the above problems is the channel quality index (Channel quality index, which is a cluster structure and uplink control channel information for maximizing the performance of Scatterd-AMC sub-channelization in OFDMA system) Quality Indicator: Provides a way to reduce (CQI).

Other objects and advantages of the present invention can be understood by the following description, and will be more clearly understood by the embodiments of the present invention. Also, it will be readily appreciated that the objects and advantages of the present invention may be realized by the means and combinations thereof indicated in the claims.

CQI control method for adaptive modulation and coding in the OFDMA system of the present invention for achieving the above technical problem, (a) effective selected according to a predetermined criterion among clusters including one or more bins which are a plurality of subcarrier groups Calculating an average CINR of each cluster; (b) determining an optimal MCS level of each of the valid clusters based on the average CINR value; And (c) determining an optimal cluster among the valid clusters based on the optimal MCS level.

In the OFDMA system of the present invention for achieving the above technical problem, the CQI control apparatus for adaptive modulation and coding, each of the effective clusters selected according to a predetermined criterion among the clusters including one or more bins which are a plurality of subcarrier groups A CINR calculation unit for calculating an average CINR; An MCS level determiner which determines an optimum MCS level of each of the valid clusters based on the average CINR value; And a cluster determination unit that determines an optimal cluster among the valid clusters based on the optimal MCS level.

In order to achieve the above technical problem, the present invention provides a computer-readable recording medium having recorded thereon a program for executing a CQI control method for adaptive modulation and coding in an OFDMA system.

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that the same elements among the drawings are denoted by the same reference numerals and symbols as much as possible even though they are shown in different drawings. In the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted.

Also, when a part is referred to as "including " an element, it does not exclude other elements unless specifically stated otherwise.

Figure 1 shows the structure of the band AMC (Band-AMC) proposed in the IEEE 802.22 WRAN system.

Referring to FIG. 1, Band-AMC is used in a situation where there is little channel change in the frequency domain. When the channel change in the frequency domain is small, dynamic channel allocation can be performed by increasing the accuracy of the channel state information (CSI) fed back due to the small channel change in one band. In the WRAN system, the most basic unit of the band-type AMC sub-channel structure is a bin, and is composed of 14 consecutive subcarriers in the frequency domain. Four contiguous bins in the frequency domain, that is, 56 contiguous subcarriers are gathered to form one band. When the FFT size is 2048, the band consists of 30 bands in total. The user feeds back channel status information to the base station in units of bands, and uses one or more bands as subchannels according to a requested service. As a result, multi-user diversity gains and implicit frequency diversity gains are obtained, thereby improving capacity and frequency efficiency of the system.

2 shows the structure of Scattered-AMC proposed in the IEEE 802.22 WRAN system.

Referring to FIG. 2, Scattered-AMC uses dynamic resource allocation like Band-AMC. Scattered-AMC subchannels are used in environments where channels in the frequency domain change more rapidly than band-AMC. Like Band-AMC, the Scattered-AMC subchannel structure is the most basic unit, which is composed of 14 contiguous subcarriers in the frequency domain, and one bin consists of 12 contiguous data subcarriers. It consists of two pilot sub-carriers for channel estimation. Scattered-AMC is similar to Band-AMC in that one or more contiguous bins are gathered together in a frequency domain to form a band. However, Scattered-AMC is different from Band-AMC in that scattered bins are combined to form subchannels. Scattered-AMC is indexed to the carrier in each sub-channel after the assignment to the sub-channel is performed through the same process as Band-AMC. Scattered-AMC, unlike the band-type AMC subchannel structure in which the channel status information is fed back to the base station on a band basis and allocated for each band according to a requested service, the Scattered-AMC feeds back channel status information for each bin or scatter band. This has the advantage of improving the capacity and frequency efficiency of the system by obtaining multi-user diversity gain and frequency diversity gain.

However, since the channel status information is fed back to the base station in a scattered bin or scattered-band unit, it is a factor of decreasing uplink frequency efficiency. Therefore, there is a need for a technique for reducing overhead of uplink.

The present invention proposes a method of maximizing system performance while reducing uplink overhead.

3 is a flowchart illustrating a CQI control method for adaptive modulation and coding according to an embodiment of the present invention.

Referring to FIG. 3, the CQI control apparatus configures a cluster for the plurality of received subcarriers, and classifies the cluster from the lowest cluster group to the highest cluster group according to the cluster size (S310).

A cluster is defined as a group of bins including one or more bins (BINs), which are a plurality of subcarrier groups, and one bin is composed of a pilot subcarrier and a data subcarrier. Here, the cluster size is expressed as the number of beans constituting the cluster. The cluster level (CL) is a hierarchy of cluster groups based on the cluster size. The cluster level increases as the number of bins constituting the cluster increases. The lowest cluster group, which is a group of clusters composed of the smallest number of bins, is designated as cluster level 1 and expressed as CL-1. Clusters in each cluster group are assigned a cluster index in turn from the first cluster.

The cluster structure of the present invention has a dynamically changing cluster structure because the cluster in the upper cluster group is configured to include a predetermined number of consecutive clusters in the lowest cluster group.

When configuring a cluster structure classified into cluster level 1 to cluster level 4, each cluster of cluster level 1 is composed of one bin, and each cluster of cluster level 2 includes two clusters of cluster level 1 in succession. Can be configured to Hereinafter, the configuration of assigning an index from zero will be described.

For example, a cluster consisting of the first bin (BIN-1), the second bin (BIN-2), the third bin (BIN-3), and the fourth bin (BIN-4) each is a cluster level 1 first It becomes a cluster CL-1 (0), the 2nd cluster CL-1 (1), the 3rd cluster CL-1 (2), and the 4th cluster CL-1 (3). The cluster composed of BIN-1 and BIN-2, BIN-2 and BIN-3, and BIN-3 and BIN-4, respectively, includes a cluster level 2 of the first cluster CL-2 (0) and the second cluster CL. -2 (1)) and a third cluster CL-2 (2). The cluster consisting of BIN-1, BIN-2 and BIN-3, BIN-2, BIN-3 and BIN-4, respectively, is a cluster level 3 of the first cluster (CL-3 (0)) and the second cluster (CL). -3 (1)). The cluster composed of BIN-1, BIN-2, BIN-3, and BIN-4 becomes a cluster level 4 first cluster (CL-4 (0)).

Next, a carrier-to-interference-plus-noise ratio (CINR) for a specific cluster selected according to a predetermined criterion among the clusters is calculated (S330).

More specifically, the average CINR is calculated for each cluster in the lowest cluster group, that is, cluster level 1 (CL-1), which is a group of clusters composed of the minimum number of bins (S331). Here, the average CINR (CINR _av ) is the CINR average value for the subcarriers in one bin constituting each cluster in CL-1.

It selects a first valid clusters having the largest CINR _av value of the CINR _av value calculated in the CL-1 (S333).

Upper valid clusters including the first valid cluster are selected from all upper cluster groups (S335). Since the upper cluster is configured to include a predetermined number of consecutive clusters in the lowermost cluster group, each upper cluster includes the lowermost cluster as part. Therefore, at each position of the first valid cluster selected in CL-1, the upper effective cluster including the first valid cluster in both left and right directions is selected from each upper cluster group.

An average CINR value is calculated for each selected upper effective cluster (S337). Here, the average CINR is an average value calculated for the bins constituting the cluster. Since each selected upper effective cluster includes the first valid cluster selected from the lowest cluster, the CINR _av calculated in CL-1 may be used.

Next, an optimal MCS level of each of the valid clusters is determined based on the average CINR value calculated for each of the valid clusters (S350).

Modulation and Coding Scheme (MCS) is a combination of one user's transmittable Modulation Order and coding rate, i.e. a predefined modulation and channel coding, from level 1 to level N depending on the number of MCSs. Up to a plurality of MCSs can be defined. Each MCS level has a matching Target SNR (SNR _Target ) value. The SNR _Target is a reference SNR value capable of guaranteeing a specific PER (packet error rate) performance. For example, the target SNR at a specific PER of 1% may be determined as the SNR _Target . Frame Error Rate (FER) is an important measure of reception channel quality determination.

More specifically, the average CINR (CINR _av ) value of each higher effective cluster is used as the SNR _Target. The value is compared (S351). Comparison Result CINR _av This SNR _Target If above, the SNR _Target The optimal MCS level of each higher cluster is determined by determining an optimal MCS level matching S (S353).

Next, an optimal cluster among the valid clusters is determined based on each optimal MCS level (S370).

More specifically, the throughput of each of the effective clusters is calculated based on the optimal MCS level (S371), and the cluster having the largest capacity is determined as the optimal cluster (S373). In general, the packet scheduler tries to improve the performance of the system by increasing the throughput so that the most data can be transmitted. Therefore, it is desirable to select a cluster with the largest capacity.

Capacity calculation can be calculated as {(1-PER) × bits per symbol} for subcarrier / symbol time as an example, and other methods. It can also be calculated as

Next, the selected optimal cluster information is transmitted on the uplink as a channel quality indicator (CQI) (S390). The channel quality index is an indicator used to transmit the reception quality of the terminal through a feedback channel, and uses the MCS level, the adjacent channel level (ACL), and the index of the optimal cluster.

The ACL is represented by the level of the cluster group to which the optimal cluster belongs. For example, when the cluster to which index 4 of cluster level 3 is assigned is selected as the optimal cluster, the ACL becomes CL-3.

If it is assumed that CQI information of n clusters is required according to the requirements of the system, in step 331, n first valid clusters are selected in order of CINR _av from CL-1 in CL-1, and each first valid cluster is selected. Repeat steps 333 to 373 for. As a result, n optimal clusters are determined, and the MCS levels, ACLs and indexes of each optimal cluster, i.e., n MCS levels, n ACLs, n indexes, are determined. Here, n ACLs and indexes are transmitted as CQIs in order of the lowest MCS level among the n MCS levels and the capacity of the cluster.

4 is a diagram illustrating an example of a CQI control method for adaptive modulation and encoding according to the embodiment of FIG. 3.

Referring to FIG. 4, the example is a cluster structure in which the number of subcarriers constituting the entire band is 1024 and classified into four cluster levels. Each bin of the cluster consists of nine subcarriers, including one pilot and eight consecutive data sets. It will be apparent to those skilled in the art that the number of pilots and data constituting the bin can vary.

In the above example, the lowest cluster group CL-1 is composed of 96 clusters consisting of one bin, and each cluster is assigned an index from 0 to 95 in order. The second higher cluster group CL-2 is composed of two consecutive clusters of CL-1, that is, clusters containing two bins, which in turn are also assigned an index. For example, cluster CL-2 (0) of index 0 of CL-2 is composed of clusters of index 0 and 1 of CL-1, and cluster CL-2 (1) of index 1 of CL-2 is CL-. It consists of clusters of indexes 1 and 2 of 1. In addition, the third upper cluster group CL-3 is composed of three consecutive clusters of CL-1, that is, clusters containing three bins, which are in turn assigned an index. For example, cluster CL-3 (0) of index 0 of CL-3 is composed of clusters of indexes 0, 1 and 2 of CL-1, and cluster CL-3 (1) of index 1 of CL-3 It consists of clusters of indexes 1, 2 and 3 of CL-1. Similarly, the fourth higher cluster group CL-3 is composed of four consecutive clusters of CL-1, that is, clusters including four bins, and in turn are assigned an index. For example, cluster CL-4 (0) of index 0 of CL-4 is composed of clusters of indexes 0, 1, 2, and 3 of CL-1, and cluster CL-4 (1 of index 1 of CL-4 (1). ) Is composed of clusters of indexes 1, 2, 3, and 4 of CL-1.

The average CINR value of each cluster to which the index is assigned in CL-1 is calculated, and the first valid cluster having the largest value among the calculated average CINR values of CL-1 is selected. In this example, cluster CL-1 (5) at index 5 was selected as the first valid cluster.

In each upper cluster group, an upper effective cluster including a cluster of the CL-1 (5) as a part is selected from the cluster position of the CL-1 (5) to the left and right directions. In the above example, CL-2 (4, 5), CL-3 (3, 4, 5) and CL-4 (2, 3, 4, 5) were selected as higher effective clusters.

The average CINR value is calculated using the average CINR value of CL-1 for each selected upper effective cluster.

The average CINR value of each calculated effective cluster is compared with the target SNR value to determine the MCS level that matches the target SNR value when the average CINR value is greater than or equal to the target SNR value.

Each determined MCS level is used to calculate the throughput of each effective cluster.

Comparing the calculated capacity results, the optimal cluster having the largest value is selected, and the MCS level, belonging cluster group level (ACL), and index of the optimal cluster are selected as CQI information. In this example, CL-4 (5) was selected. Here, ACL is CL-4 and index is 5.

If CQI information of n clusters is needed, n-1 clusters are additionally selected in CL-1, and n optimal clusters are selected by repeating the process n-1 additional times for the n-1 clusters. At this time, the lowest MCS level is selected among the selected n MCS levels, and a feedback signal is transmitted to the selected MCS level.

5 is a diagram illustrating a format for sending an MCS, an ACL, and an index calculated through an uplink channel according to an embodiment of the present invention.

Referring to FIG. 5, when CQI information of n selected optimal clusters is requested, the first field is filled with the lowest MCS level among the MCS levels determined for the n optimal clusters, and the ACLs and indexes of the n optimal clusters are filled. Fill in the fields after the second one in turn, starting with this large cluster.

If n = 5, five optimal clusters are determined, and five ACLs and indexes are also determined. The cluster having the lowest MCS level among the determined 5 cluster MCS levels is selected as the cluster for CQI reporting, and the MCS level of the selected cluster is filled in the first field. The five ACLs and indexes are then populated in subsequent fields, starting with the corresponding value in the lower capacity cluster.

6 is a block diagram schematically illustrating a CQI control apparatus 600 in an OFDMA system using adaptive modulation and coding (AMC) according to an embodiment of the present invention. Detailed descriptions of contents overlapping with the above description will be omitted.

Referring to FIG. 6, the CQI control apparatus 600 includes a cluster constructing unit 610, a control information constructing unit 630, and a transmitting unit 670.

The cluster configuration unit 610 classifies and levels clusters including one or more bins, which are a plurality of subcarrier groups, into groups based on the number of bins. The clusters in the upper cluster group are configured to include a predetermined number of clusters in the lowest cluster group. The clusters in each cluster group are assigned indexes in turn.

The control information configuring unit 630 determines the CQI information to be carried in the feedback signal to be transmitted on the uplink. The control information configuring unit 630 includes a CINR calculation unit 640, an MCS level determination unit 660, and a cluster determination unit 680.

The CINR calculator 640 calculates an average CINR of the valid clusters selected according to a predetermined criterion among the clusters. The CINR calculator 640 includes a calculator 641 and a selector 645. The calculation unit 641 calculates an average CINR of each cluster in the lowest cluster group, which is a group of clusters consisting of a minimum number of bins, and the selection unit 645 is the first validity having the largest average CINR value in the lowest cluster group. Select a cluster and select the upper valid clusters that include as part of the first valid cluster in all higher cluster groups. The calculator 641 calculates an average CINR value of each of the upper valid clusters.

The MCS level determiner 660 determines an optimal MCS level of each of the valid clusters based on the average CINR value of the valid clusters. The MCS level determiner 660 includes a comparator 661 and a selector 665. The comparison unit 661 compares the average CINR value of each valid cluster with the target SNR value, and the selection unit 665 selects an optimal target SNR value at which the average CINR value is equal to or greater than the target SNR value, and matches the target SNR value. Determine the MCS level.

The cluster determiner 680 determines an optimal cluster among valid clusters based on the optimal MCS level. The cluster determiner 680 includes a capacity calculator 681 and a cluster selector 685. The capacity calculator 681 calculates a capacity based on the optimal MCS level determined for each of the effective clusters, and the cluster selector 685 determines the cluster having the largest capacity as the optimal cluster.

The transmitter 670 selects the information of the optimal cluster as the channel quality index, configures a predetermined format, and transmits the information on the uplink. The channel quality index is the MCS level of the optimal cluster, the level and index of the cluster group to which the optimal cluster belongs. When the transmitter 670 intends to transmit a plurality of channel quality indexes in the uplink, the lowest MCS level among the MCS levels of the plurality of optimal clusters and the cluster group level of each of the plurality of optimal clusters according to the format of FIG. 5. And the indexes are transmitted in order starting from the value for the high capacity cluster.

The apparatus according to the present invention enables more efficient use of uplink radio resources, increases frequency efficiency by reducing the amount of feedback of a limited uplink control channel, and has more or less uplink overhead than existing systems. You can expect improved performance.

7 is a diagram comparing the performance and uplink overhead of the method and the other method according to an embodiment of the present invention.

Referring to FIG. 7, System A uses Band-AMC to show performance differences between Scattered-AMC and Band-AMC, and feeds back 5 indexes of the band, such as IEEE 802.16e Mobile WiMAX. System B reduces the amount of CQI feedback by introducing the concept of unidirectional cluster. System C is a system for feeding back CQI in a manner in which the bidirectional cluster concept proposed in the present invention is introduced. System D is an ideal system where all terminals carry MCS information for all bands.

Comparing the uplink overhead of each system, the system D that provides channel information for all bands has the largest uplink overhead, and the system C to which the method according to the present invention is applied is less than the system A of IEEE 802.16e. You can see that it has link overhead. It can be seen that the invention according to the present invention shows the performance improvement of the system with a smaller amount of uplink overhead than the existing Band-AMC.

It can be seen from FIG. 7 and FIG. 8 that the system B has a lower performance than the system C according to the present invention due to the smallest amount of uplink overhead but uncertain channel information.

FIG. 8 is a diagram illustrating sector throughput of each system model of FIG. 7.

Referring to FIG. 8, it can be seen that the system D, which feeds back the CQI for the entire band, shows the largest throughput. This is because it has a large amount of uplink overhead, but because the correct channel information can be assigned to the correct channel.

On the other hand, the system C to which the present invention is applied has a performance degradation of about 4.3% compared to the system D, which is an ideal system, but the performance of about 11.8% and 5.8% is improved for the systems A and B. That is, the system C to which the present invention is applied can be confirmed that the frequency efficiency is improved and the capacity is improved by feeding back CQI information more efficiently than the systems A and B.

FIG. 9A illustrates a data transmission rate for each user according to each system model of FIG. 7, and FIG. 9B illustrates a standard deviation of capacity for each user of each system of FIG. 7. The lower the standard deviation, the higher the fairness.

Referring to FIG. 9, as can be seen in FIGS. 9A and 9B, the system C to which the present invention is applied has a high data rate but a performance deterioration in terms of fairness when compared to the system A. FIG. . This is because system C has a flexible allocation unit, so that a user with a good channel situation is allocated more channels than system A having a fixed allocation unit, whereas system A has a fixed band size. This is because the channel is allocated more evenly to the user.

In addition, system B has the advantage of requiring the smallest amount of CQI transmission bits, but because of this, the accuracy of CQI information is inferior, and thus performance is lower in terms of capacity and fairness than system C.

Finally, system D uses the smallest, fixed allocation unit of the four systems. Because of the highest accuracy of the CQI information, it shows very high performance in terms of capacity. However, due to the smallest allocation unit, more channels are allocated to users having better channel conditions than system C to which the present invention is applied.

Although the present invention has been described with reference to a base station and a mobile station using the OFDMA technology for convenience of description, it can be applied to a base station and a mobile station of a wireless communication and cellular mobile communication system using the OFDM-FDMA / CDMA / TDMA technology. Those skilled in the art will fully know.

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may be implemented in the form of a carrier wave (for example, transmission via the Internet) . The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the art to which the present invention belongs.

So far, the present invention has been described with reference to preferred embodiments. Although specific terms have been used herein, they are used only for the purpose of describing the present invention and are not used to limit the scope of the present invention as defined in the meaning or claims.

Therefore, it will be understood by those skilled in the art that the present invention may be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

The present invention is a flexible block-wise loading (FBL) method that can maximize performance using AMC technology in an OFDMA system.

The present invention avoids the conventional method of transmitting channel information for a fixed size subcarrier group by including a combination of a variable size and a modulation scheme of a subcarrier group having a maximum transmission amount within limited feedback information in the limited feedback information. Improves frequency efficiency and capacity and fairness performance of OFDMA systems.

In the present invention, the system performance is improved by enabling more efficient CQI reporting than the conventional method by calculating channel similarity in both directions at the selected cluster position in the lowest cluster group as a reference.

The cluster structure proposed in the present invention can be applied to all communication systems using Adaptive Modulation and Coding (AMC).

Claims (21)

(a) calculating an average CINR of each valid cluster selected from among clusters including one or more bins that are a plurality of subcarrier groups; (b) determining an optimal MCS level of each of the valid clusters based on the average CINR value; And and (c) determining an optimal cluster among the valid clusters based on the optimal MCS level. According to claim 1, wherein the step (a), (a1) calculating an average CINR of each cluster in the lowest cluster group, which is a group of clusters consisting of a minimum number of bins; (a2) selecting a first valid cluster having a largest average CINR value in the lowest cluster group; (a3) selecting upper valid clusters including the first valid cluster in all upper cluster groups; And (a4) calculating an average CINR value of each of the upper effective clusters; and the CQI control method for adaptive modulation and coding in an OFDMA system. According to claim 1, wherein step (b), (b1) comparing an average CINR value of each of all valid clusters with a target SNR value; And (b2) determining an optimal MCS level that matches the target SNR value at which the average CINR value is equal to or greater than a target SNR value; and CQI control method for adaptive modulation and coding in an OFDMA system. The method of claim 1, wherein step (c) comprises: (c1) calculating the capacity of each of the effective clusters based on the optimal MCS level; And (c2) determining a cluster having the largest capacity as an optimal cluster; CQI control method for adaptive modulation and coding in an OFDMA system, comprising: a. The method of claim 1, wherein before step (a), (d) classifying the clusters into groups based on the number of bins; CQI control method for adaptive modulation and coding in an OFDMA system. The method of claim 5, wherein step (d) CQI control method for adaptive modulation and coding in an OFDMA system, characterized in that the cluster in the upper cluster group comprises a predetermined number of clusters in the lowest cluster group. The method of claim 1, (e) transmitting the information of the optimal cluster on the uplink as a channel quality index; CQI control method for adaptive modulation and coding in an OFDMA system, characterized in that the. The method of claim 7, wherein Wherein the channel quality index is the MCS level of the optimal cluster, the level and index of the cluster group to which the optimal cluster belongs, and the CQI control method for adaptive modulation and coding in an OFDMA system. The method of claim 8, wherein step (e) In case of transmitting a plurality of channel quality indexes in the uplink, the lowest MCS level among the MCS levels of the plurality of optimal clusters, the cluster group and the index of each of the plurality of optimal clusters are transmitted. CQI control method for adaptive modulation and coding. The method of claim 9, wherein step (e) CQI control method for adaptive modulation and coding in the OFDMA system, characterized in that for transmitting the cluster group and the index belonging to the cluster from the optimal cluster having a large capacity among the plurality of optimal cluster. A CINR calculator configured to calculate an average CINR of each of the effective clusters selected from among clusters including one or more bins which are a plurality of subcarrier groups; An MCS level determiner which determines an optimum MCS level of each of the valid clusters based on the average CINR value; And And a cluster determiner configured to determine an optimal cluster among the effective clusters based on the optimal MCS level. The method of claim 11, wherein the CINR calculation unit, A calculation unit for calculating an average CINR of each cluster in the lowest cluster group, which is a group of clusters consisting of a minimum number of bins, and an average CINR value of each of the upper effective clusters selected from all upper cluster groups; And And selecting a first effective cluster having the largest average CINR value in the lowest cluster group, and selecting the upper valid clusters including the first valid cluster from all the upper cluster groups. CQI control apparatus for adaptive modulation and coding in an OFDMA system. The method of claim 11, wherein the MCS level determiner, A comparison unit comparing an average CINR value of each of all valid clusters with a target SNR value; And And a selector configured to determine an optimal MCS level matching the target SNR value at which the average CINR value is equal to or greater than a target SNR value. 2. The CQI control apparatus for adaptive modulation and coding in an OFDMA system, comprising: a; The method of claim 11, wherein the cluster determination unit, A capacity calculation unit calculating a capacity of each of the effective clusters based on the optimal MCS level; And And a cluster selector configured to determine a cluster having the largest capacity as an optimal cluster. The method of claim 11, And a cluster configuration unit for classifying the clusters into groups based on the number of bins. 2. The CQI control apparatus for adaptive modulation and coding in an OFDMA system, further comprising: a cluster configuration unit. The method of claim 15, wherein the cluster configuration unit, CQI control apparatus for adaptive modulation and coding, characterized in that the cluster in the upper cluster group comprises a predetermined number of consecutive clusters in the lowest cluster group. The method of claim 11, CQI control apparatus for adaptive modulation and coding in the OFDMA system, characterized in that it further comprises; transmitting unit for transmitting the information of the optimal cluster on the uplink as a channel quality index. The method of claim 17, Wherein the channel quality index is the MCS level of the optimal cluster, the level and index of the cluster group to which the optimal cluster belongs, and the CQI control apparatus for adaptive modulation and coding in an OFDMA system. The method of claim 18, wherein the transmission unit, In case of transmitting a plurality of channel quality indexes in the uplink, the lowest MCS level among the MCS levels of the plurality of optimal clusters, the cluster group and the index of each of the plurality of optimal clusters are transmitted. CQI control device for adaptive modulation and coding. The method of claim 19, wherein the transmission unit, The CQI control apparatus for adaptive modulation and coding in the OFDMA system, characterized in that for transmitting the cluster group and the index belonging to the cluster from the optimal cluster having a large capacity among the plurality of optimal clusters. A computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 1 to 10 on a computer.

Images