RU2420889C1 - Method and device for reducing feedback delays in wireless communication - Google Patents

Abstract

FIELD: information technology.

SUBSTANCE: averaging, compression or both processes are employed to reduce the number of bits required for transmitting channel quality information.

EFFECT: reduced feedback delays in wireless communication system.

15 cl, 5 dwg

Description

FIELD OF THE INVENTION

The present invention relates to wireless communications.

State of the art

In wireless communication systems, it is desirable to minimize signaling overhead. In particular, this applies to feedback transmissions and, more specifically, to channel quality feedback, which is measured by, for example, signal-to-noise ratio or another channel quality indicator. A mobile node, for example, can determine the quality of one or more channels and transmit this information to the base station, allowing it to select a set of the best channels for communication at a given point in time.

In previously proposed schemes, denoted by the term “Best M” schemes, the overhead for feedback of quality information is reduced by reporting quality measurements for M transmission bands with the best quality.

SUMMARY OF THE INVENTION

A method and apparatus are disclosed for reducing feedback costs in a wireless communication system. Averaging, compression, or both of these processes are used to reduce the number of bits or overhead required to transmit channel quality information. The method disclosed herein requires fewer transmitted bits than previously proposed Best M schemes.

Brief List of Drawings

A deeper understanding of the present invention can be obtained by studying the following detailed description and the accompanying drawings, in which:

1 is a flowchart according to a first embodiment of a method for reducing costs;

FIG. 2 is a flowchart according to a second embodiment of a method for reducing costs; FIG.

Figure 3 is an example of a third embodiment of a method for reducing costs;

4 is an illustration of an alternative example of a second embodiment; and

5 is an example of a wireless transmit / receive unit configured to implement any of the embodiments of the present invention.

Detailed description

As used herein, the term "Wireless Transmit / Receive Unit (WTRU) includes, but is not limited to, User Equipment (UE), a mobile station, a fixed or mobile subscriber station, a pager, a cell phone, Personal Digital Assistant (PDA), a computer, or any other type of user device capable of operating in a wireless environment. As used herein, the term “base station” includes, but is not limited to, Node-B, a local controller, an Access Point (AP), or any other type of interface device capable of operating in a wireless environment .

1 is a flowchart illustrating a first embodiment of a method 100 for reducing feedback transmission costs in a wireless system. This method is referred to by the term “Conventional Hybrid Best M Scheme M”. Specialists in the art know that the bandwidth of the communication channel, as a rule, is divided into a number of subbands. The method 100 begins with step 105, in which the signal quality in each subband is determined. A quality measure is a pre-defined quality metric, such as signal-to-noise ratio or Channel Quality Index (CQI). At step 110, the number M of subbands with the best metric values is selected. The number M is less than the total number of subbands.

At 120, M selected subbands are preferably grouped in Q groups. The number of Q groups is preferably at least 2 and less than the selected number M of subbands. As Q decreases, the number of bits (overhead) needed to report quality metrics decreases, but the accuracy (resolution) of reports on the best M ranges also decreases. Therefore, the value of Q is preferably selected so as to optimize this compromise. An example of optimization is the selection of Q so that there is no more than one group containing exactly one subband. After grouping the subbands in step 130, the average value of the metrics of the subbands in each of the Q groups is determined. The result is Q primary averages. At 140, one average of the subband metrics is determined that are not among the M best subbands. This average value is referred to as the secondary average value. At step 150, Q primary average values and one secondary average value are transmitted. At 160, the locations of the M best subbands and Q groups in the passband are transmitted.

In one specific example, said average values and locations are transmitted from the Wireless Transmit / Receive Unit (WTRU) to the Base Station, which allows the base station to optimize transmissions by using only subbands with the best quality. In general, said averages can be transmitted to any wireless receiver.

Several alternatives may be used for transmitting locations to notify the receiver of which subbands are among the M best and which ones are in each of the Q groups. In one alternative embodiment, said average values may be transmitted according to a predetermined order, as described in more detail below. In yet another alternative embodiment, a set of labels may be transmitted. As a final example, we consider the case when Q = 2. One tag may be transmitted to indicate the locations of the M subbands with the best quality in the bandwidth. A second mark may be transmitted indicating which of the mentioned M subbands are in one of two groups.

By default, the remaining ranges are in another group. In general, Q locations are transmitted according to this scheme. Since Q is less than M, the number of bits (overhead) used to transmit useful subband quality information may be less compared to the case when quality information is transmitted for all M bands, i.e., according to the so-called individual notification scheme for M best subbands .

An alternative circuit in the framework of the first embodiment, denoted by the term “differential hybrid Best M scheme”, can further reduce the required overhead. In this alternative embodiment, as in the hybrid Best M scheme, Q location indices are transmitted — one for M best subbands and Q-1 for ranges in Q-1 groups from Q groups. In this scheme, however, Q is ordered and only one primary average value of the quality metric for the first of Q groups is reported. Each of the remaining Q-1 primary average values is reported as the difference between each average value and the average value preceding in said order. The secondary average value is reported as the difference between the secondary average value and the last of the primary average values.

As an example of a differential circuit, we consider the case when Q = 2. In this case, the transmitted average values are:

a) one primary mean value for the first of two groups,

b) the difference between the primary average of the second group and the primary average of the first group, and

c) the difference between said secondary average value and the primary average value of the second group.

Compared to the regular hybrid Best M scheme described above, elements a) and b) combined can save at least two more bits, and element c) can save at least one more bit.

2 is a flowchart illustrating a second embodiment of a method 200 for reducing feedback transmission costs. In this embodiment, a compression transformation is used to reduce costs.

Similarly to the first embodiment of FIG. 1, in step 205, a quality metric is determined for each subband, and in step 210, M subbands with the best quality metric are selected. At step 240, the average value of the metrics for the subbands not included in the number of the mentioned M best subbands is determined. At 250 M, the metrics and average are compressed, and at 260, these compressed values are transmitted. Compression reduces the required transmission overhead.

The following is a specific example of using a compression transformation. The values of M metrics and the average value can be arranged as elements of a vector. The order of the elements of the vector indicates which of the M best subbands correspond to the metric value and which of the elements is the average value. For example, for M = 5, the following vector of eight elements can be defined:

y = [CQI ₁ CQI ₂ CQI ₃ CQI ₄ CQI ₅ CQI _avg 0 0],

where CQI ₁ - CQI ₅ are the quality metrics for subbands 1-5, respectively, and CQI _avg is the average of the metrics for subbands that are not among the M best. Two null elements are described below.

The information contained in the vector y is compressed by the compression transformation represented by the matrix W. Compression can be represented as matrix multiplication to obtain the compressed vector y3:

y3 = yW.

Elements of the compressed vector y3 are quantized and transmitted.

As a specific example, the compression transformation may be a Haar transformation. The Haar transform, which is a specific type of wavelet transform, is used for applications such as image compression. The Haar transform can reduce transmission costs by shifting the weight of the elements of the vector into one element.

For the above example with the vector M = 5, a suitable Haar transformation can be performed using the following matrix:

This Haar transformation is reversible and the compressed vector y can be restored without loss by inverting this process, which is expressed as y = y ₃ F, where

It should be noted that for this example, the presence of two zeros in the vector y leads to the fact that the last element of the compressed vector y3 will be zero. Therefore, this last element can be deleted before transmission without loss of information.
Alternatively, the elements of the vector y are reordered as follows:

y '= [CQI ₁ CQI ₂ CQI ₃ CQI ₄ CQI ₅ 0 CQI _avg 0].

After compression, the last two elements of the transformed vector can be deleted without loss of information, because the receiver knows in advance which elements of the vector y 'are zero, and it uses this a priori information to decode CQI ₅ and CQI _avg without loss.

Alternatively, additional cost reduction can be achieved by transmitting compressed metrics and averages across more than one Transmission Time Interval (TTI). This alternative is illustrated in FIG. 4. Assume that the compression results of quality information fit in P bits. Without diversity, these P bits are transmitted in each TTI 400. With diversity P, the bits are divided between the K TTI 410 intervals, where K is greater than 1. Then the average overhead in bits will be P / K instead of P.

This embodiment may be extended for multi-level communication with multiple codes. In this scenario, quality metrics are reported for each level for each subband. In this case, the quality metrics are contained in the matrix, and not in the vector. The elements of the matrix can be the metric values themselves or the differences between each metric value and, for example, the maximum metric value. This information is further compressed by applying a two-dimensional compression transformation, such as a two-dimensional Haar transformation. The result can be a matrix in which one element has a relatively large value, and the remaining elements have small values. This can lead to a significant reduction in feedback overhead during transmission of said compressed matrix.

This embodiment can be applied to frequency partitioning. In this scenario, the transmission band is subblocked. Quality metrics are defined for each sub-block. The transmission band divides into K sections, where K is greater than or equal to 2. The first section contains N1 subblocks with the best quality, the second section contains the following N2 subblocks that are not in the first section, and so on up to K. For the first section of N1 subblocks select M1 subunits with the best M1 quality metrics and apply the above embodiment of the Best M1 with Haar transform. For the second section, the best M2 subunits are selected, where M2 may be unequal to M1, and the embodiment of the Best M2 with Haar transformation is applied. Similarly, Haar compression is applied to each of the K sections. This method reduces transmission overhead to a value

A similar split can be used in circuits with Multiple Inputs and Multiple Outputs (Multiple Input / Multiple Output, MIMO). For example, splitting can be performed by code words, levels, or both of these elements.

3 is an illustration of an example of a third embodiment of a method for reducing feedback transmission costs. In this embodiment, the compression may be distributed at different time intervals. Communication resources, such as assigned frequencies and time resources, are collected in resource blocks, which in turn are grouped into Resource Block Groups (RBGs). Quality metrics are defined for each RBG.

The set of RBG is divided into N groups. The locations of these groups are known in advance in both the WTRU and the base station. In the first reporting time interval (for example, the TTI interval), a compression transformation, such as Haar's Best M transformation, can be applied to quality metrics in one of the groups, and then the compressed metrics are transmitted. In each subsequent reporting time interval, compressed metrics for another of the N groups are reported. This continues until quality metrics for the entire frequency range are transmitted. In this embodiment, the costs are reduced, at least because the vector of metric values is reduced from N _RBG elements to N _RBG / N elements.

3, a specific example of this embodiment is illustrated, where N = 2. The set of RBG 300 is divided into N = 2 groups, one of which contains even RBG 310, and the other contains odd RBG 340. In the interval i of the report transmission, the Best M compression by Haar method is applied to the even group 320, and then the results are transmitted 330. B the next reporting interval i + 1, the odd group 350 is compressed using the Haar method of Best M compression, and then the results are transmitted 360.

The table compares various reduction schemes, including some embodiments of the present invention. This table assumes that each uncompressed quality metric is represented by 5 bits. In particular, the percentage reduction in costs for the Individual Best M Scheme with Haar Transformation and its comparison with the Single Best M Scheme without Haar compression are shown.

Cost comparison across various CQI compression schemes

The described embodiments may be implemented, for example, in a WTRU, such as the WTRU of FIG. 5. The WTRU may employ a method for transmitting channel quality information to a base station, which, in turn, can use this information for channels with the best quality to use them to communicate with this WTRU. The WTRU 500 may comprise a receiver 510, a transmitter, and a processor 520. The receiver 510 may receive signals through various channels. The processor 520 may use the received information to determine quality metrics, organize these metrics into groups, determine the average values of these metrics, and to compress them. Transmitter 515 may transmit averaged and / or compressed metrics with costs reduced according to the disclosed method.

Options for implementation

1. A method of compressing quality metrics transmitted in a wireless communication system using multiple subbands, comprising the steps of:

selecting the M best quality metrics for each subband;

measure the average value of quality metrics in the remaining sub-ranges;

creating a vector containing M best quality metrics and said mean value; and

transform this vector with compression to produce a transformed vector.

2. The method according to claim 1, further comprising the step of removing the last element of the transformed vector before transmitting.

3. The method according to claim 2, further comprising the step of quantizing the remaining elements of the transformed vector.

4. The method according to claim 1, 2 or 3, in which the values M of the best quality metrics are reported in the aforementioned vector in the order of the respective subbands.

5. The method according to any one of the preceding embodiments, further comprising the step of transmitting the transformed vector.

6. User equipment in a wireless communication network that transmits compressed quality metrics according to the method of claim 1, 2, 3 or 4.

7. A base station in a wireless communication network that receives compressed quality metrics from user equipment according to claim 6.

8. The method according to any one of claims 1, 3 or 5, further comprising the step of reordering the M best values of the vector by dispersing any zero values before performing the compression transformation.

9. The method of claim 8, further comprising the step of removing two elements of the transformed vector before transmitting.

10. The method of claim 8 or 9, further comprising the step of transmitting compressed quality metrics.

11. User equipment in a wireless communication network that transmits a quality metric compressed according to the method of any one of claims 8-10.

12. A base station in a wireless communication network that receives a compressed quality metric from user equipment according to claim 11.

13. The method according to any one of claims 1-5 or 9-10, wherein in a system with multiple codes / multiple levels, quality metrics of each level are compressed and reported.

14. The method according to item 13, further comprising the step of reporting the quality metrics for each level for each subband.

15. The method according to item 13 or 14, further comprising stages in which:

Report the highest quality metric

determining a difference between said highest value and metric values for each of the remaining levels; and

report the difference for each of the remaining levels.

16. A method for compressing a channel quality metric, comprising the steps of:

break the bandwidth into two or more sections;

M1 selects the best quality metrics for each subband in the first section;

measuring the average value of the remaining subranges in the first section;

create the first vector; and

converting the first vector with compression to produce the first transformed vector.

17. The method according to clause 16, in which the first section contains N1 best subunits in the set of subunits.

18. The method according to clause 16 or 17, further comprising stages in which:

M2 selects the best quality metrics for each subband in the second section;

measure the average value of the remaining subranges in the second section;

create a second vector; and

transform the second vector with compression to produce a second transformed vector.

19. The method according to p, in which the second section contains the following N2 best blocks that are not included in the first section.

20. The method according to any one of claims 16-19, further comprising the step of removing the last element in the transformed vectors.

21. The method according to claim 20, further comprising the step of quantizing the remaining elements of the transformed vectors.

22. The method according to any one of claims 17-19, further comprising the step of removing two elements in the transformed vectors before transmitting.

23. The method according to any of the preceding embodiments, further comprising the step of transmitting the transformed vectors.

24. User equipment in a wireless communication network that transmits compressed quality metrics according to the method according to any one of claims 1-5, 8-10 and 13-23.

25. A base station in a wireless communication network that receives compressed quality metrics from user equipment according to paragraph 24.

26. A method for reporting channel quality metrics in a wireless communication network, comprising the steps of:

selecting M the best frequency ranges based on signal strength;

classify these M ranges into Q groups based on signal strength;

determine Q averaged average values of quality metrics for Q groups from M ranges; and

determine the average secondary quality metric for all other ranges.

27. The method according to p, in which the first of Q groups contains the best ranges, and the second of Q groups contains the next quality range.

28. The method according to any of the preceding embodiments, further comprising the step of transmitting from the first wireless device a first location index relating to the first communication range to the second wireless device.

29. The method of claim 28, wherein the first communication range has the best quality metric value.

30. The method of claim 28 or 29, further comprising the step of transmitting from the first wireless device a second location index related to the second communication range to the second wireless device.

31. The method of claim 30, wherein the second communication range has a second highest quality metric value.

32. The method according to any of the preceding embodiments, in which the Q value is selected so that one range contains no more than one group of Q groups.

33. The method according to any of the preceding embodiments, in which 1 <Q <M.

34. The method according to any one of claims 31-33, further comprising the step of transmitting from the first wireless device a location index relating to each of the communication ranges for which a primary average value has been determined to the second wireless device.

35. The method according to any one of claims 31-34, further comprising the step of transmitting from the first wireless device a plurality of average values of groups of quality metrics to the second wireless device.

36. The method according to clause 35, further comprising the step of determining the average value of each of the many groups with the best quality metrics.

37. The method according to clause 36, further comprising determining the average value of the remaining group, which is not a member of many groups with the best metrics.

38. The method according to clause 36 or 37, further comprising the step of transmitting from the first wireless device to the second wireless device the average value of each of the many groups with the best quality metrics.

39. The method according to clause 37 or 38, further comprising the step of transmitting from the first wireless device to the second wireless device the average value of the remaining groups.

40. The method according to any one of claims 31-39, further comprising the step of transmitting from the first wireless device to the second wireless device the average value of the first group, the first group containing the best quality metrics.

41. The method according to claim 40, further comprising the step of transmitting from the first wireless device to the second wireless device, a measure of a quality metric based on the average of the first group.

42. The method according to any one of the preceding embodiments, further comprising the step of transmitting from the first wireless device a mark indicating the location of M best ranges.

43. The method according to any of the preceding embodiments, further comprising transmitting a label showing the number of ceil (M / 2) ranges included in the first group of Q groups, wherein the ceil (M / 2) value is calculated as the smallest integer which is greater than M / 2.

44. The method according to any one of paragraphs.31-41, wherein said first wireless device is a WTRU.

45. The method according to any one of paragraphs.31-42, wherein said second wireless device is a Node B (Node-B).

46. The method according to any of the preceding embodiments, further comprising the step of compressing quality metrics and spaced bits.

47. The method according to any of the preceding embodiments, further comprising the step of dividing the Resource Block Groups (RBG) into N groups.

48. The method according to any of the preceding embodiments, in which the locations of the groups are known in the WTRU and / or in Node B.

49. The method according to any of the preceding embodiments, further comprising the step of uniformly distributing the plurality of RBGs over a range.

50. The method according to any of the preceding embodiments, further comprising the step of applying a compression transformation to each of the plurality of report transmission intervals.

51. The method according to any of the preceding embodiments, further comprising the step of dividing the plurality of RBGs into even and odd groups.

52. The method according to § 51, further comprising the step of applying Best M compression to either the even group or the odd group.

53. The method according to any of the preceding embodiments, further comprising the step of expanding the feedback update interval to the number K of Transmission Time Intervals (TTI).

54. The method according to any of the preceding embodiments, in which the average number of bits of the quality metric is reduced by spreading over several TTIs.

55. The method according to any of the preceding embodiments, in which the average overhead in bits is P / K, where P bits are generated as a result of compression.

56. The method according to any of the preceding embodiments, in which the quality metric is a Channel Quality Indication (CQI).

57. The method according to any one of the preceding embodiments, wherein the compression transformation is a Haar transformation.

58. WTRU, configured to implement the method according to any of the preceding embodiments.

59. A base station configured to implement the method of any of the preceding embodiments.

60. An integrated circuit configured to implement the method according to any of the preceding embodiments.

Despite the fact that the functions and elements have been described above in specific combinations, each function or element can be used separately without other functions and elements, or in various combinations with other functions and elements or without them. The methods or flowcharts of the present invention may be implemented in a computer program, software, or firmware implemented in a computer-readable medium for execution by a general purpose computer or processor. Examples of computer-readable media include ROM, RAM, register, cache, semiconductor storage devices, magnetic media such as internal hard drives and removable drives, magneto-optical disks and optical media such as CD-ROMs and DVDs.

Suitable processors include, for example, a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in connection with a digital signal processor core, a controller, a microcontroller, specialized integrated circuits, programmable gate arrays, other types of integrated circuits and / or state machine.

The processor, together with the software, can be used to implement a radio frequency transceiver for use in a wireless transmit / receive unit (WTRU), user equipment, terminal, base station, radio network controller, or any host computer. The WTRU can be used in conjunction with modules implemented in hardware and / or software, such as a camera, camcorder, video phone, speakerphone, vibration device, speaker, microphone, television transceiver, handsfree, keyboard, Bluetooth® module , frequency-modulated radio block, liquid crystal display, OLED display, digital music player, media player, video game module, Internet browser and / or any wireless LAN module or module for Ultrashi okopolosnoy (Ultra Wide Band, UWB) communications.

Claims (15)

1. A method of reducing feedback transmission costs in a wireless communication system, comprising the steps of:
determining a quality metric for each subband in the passband;
select M subbands with the best M quality metrics, where M is less than the total number of subbands in the passband,
group said M subbands in Q groups, where 1 <Q <M;
determining the average value of the metrics for the subbands in each of the Q groups, thereby determining Q primary average values;
determining an average value of metrics in all subbands not included in said M subbands with best quality metrics, thereby determining a secondary average value; and
transmit primary and secondary averages,
and at the stage of transmission:
assign Q groups a specific order;
transmitting the primary average value of the first group in said order;
transmitting the difference between the primary average value of each group other than the first group and the primary average value of the previous group in the above order; and
transmit the magnitude of the difference between said secondary average value and the primary average value of the last group in said order. 2. The method according to claim 1, in which the quality metric is an indicator of the quality of the channel. 3. The method according to claim 1, further comprising stages in which:
transmitting a location index indicating the locations of said M subbands with the best M quality metrics; and transmitting a location index for each of Q-1 from Q groups, 4. The method according to claim 1, in which no more than one subband contains no more than one group. 5. A method of reducing feedback transmission costs in a wireless communication system, comprising the steps of:
determining a quality metric for each subband in the passband;
selecting M subbands with the best M quality metrics, where M is less than the total number of subbands in the passband;
determine the average value of the metrics in all subbands not included in said M subbands with the best quality metrics;
compress the mentioned M quality metrics and the average value;
and at the compression stage:
forming a vector containing M best quality metrics and said mean value; and
apply the Haar transform to this vector to get a compressed vector; and
transmit a compressed vector. 6. The method according to claim 5, further comprising stages in which:
determine the M best metrics for each of the many additional levels of code;
determine the average value for each additional level of code;
group M best metrics and average values for all code levels into a matrix;
apply the two-dimensional Haar transformation to this matrix in order to transform it into a compressed matrix; and
transmit this compressed matrix. 7. A method of reducing feedback transmission costs in a wireless communication system, comprising the steps of:
determining a quality metric for each subunit in the transmission band;
divide the transmission band into sections according to the order of certain quality metrics so that each sub-block is included in one section;
for each section, M subblocks with M are selected with the best quality metrics, where M may differ for different sections;
for each section, the average value of quality metrics for subblocks not included in the M selected metrics is obtained;
for each section, these M quality metrics and average value are compressed;
and at the compression stage:
forming a vector containing M best quality metrics and said mean value; and
apply the Haar transform to this vector to get a compressed vector; and
for each section, this compressed vector is transmitted. 8. A method of reducing feedback transmission costs in a wireless communication system, comprising the steps of:
measuring a quality metric for each Resource Block Group (RBG) of the plurality of RBGs;
divide this set of RBGs into N groups, where N>1;
compress quality metrics for multiple RBGs in one of the groups during the reporting time interval,
and at the compression stage:
form a vector containing quality metrics; and
apply the Haar transform to this vector to get a compressed vector;
transmit this compressed vector; and
repeat the compression and transmission for each of the remaining N-1 groups in subsequent transmission time intervals. 9. A wireless transmit / receive unit (WTRU) comprising:
a receiver configured to receive signals in a plurality of subbands in a passband; and
a processor configured to:
determine from these signals a quality metric for each subband;
select M subbands with the best M quality metrics, where M is less than the total number of subbands;
group these M subbands in Q groups, where 1 <Q <M;
determine the average value of the metrics for the subbands in each of the Q groups, thereby determining Q primary average values; and
determine the average value of the metrics in all subbands not included in said M subbands with the best quality metrics, thereby determining a secondary average value;
assign order to the mentioned Q groups;
determine the primary average value of the first group in order;
determine the difference between the primary average value of each group other than the first group and the primary average value of the previous group in order; and
determine the difference between the said secondary average value and the primary average value of the last group in order. 10. The block according to claim 9, in which the processor is configured to measure the channel quality index as a quality metric. 11. The block of claim 10, in which:
the transmitter is configured to transmit:
the difference between the primary average value of each group other than the first group and the primary average value of the previous group; and
the difference between said secondary average value and the primary average value of the last group. 12. A wireless transmit / receive unit (WTRU), comprising:
CPU;
transmitter and
receiver;
moreover, the receiver is configured to receive signals in multiple subbands in the passband;
the processor is configured to:
define a quality metric for each subband;
select M subbands with the best M quality metrics, where M is less than the total number of subbands in the passband,
determine the average value of the metrics in all subbands not included in the mentioned M subbands with the best quality metrics; and
compress the mentioned M quality metrics and average by
forming a vector containing M best quality metrics and said mean value; and
applying the Haar transform to this vector to get a compressed vector; and
the transmitter is configured to transmit this compressed vector. 13. The block according to item 12, in which:
the processor is configured to:
determine the M best metrics for each of the many additional levels of code;
determine the average value for each additional code level;
group in the matrix M the best metrics and average values for all levels of the code; and
apply two-dimensional Haar compression to said matrix in order to transform it into a compressed matrix; and
the transmitter is configured to
transmit said compressed matrix. 14. A wireless transmit / receive unit (WTRU), comprising:
receiver;
transmitter and
CPU;
the receiver is configured to receive over a transmission band;
the processor is configured to determine a quality metric for each subunit in the transmission band;
to divide the transmission band into sections according to the order of certain quality metrics so that each sub-block is included in one section;
for each section, select M subunits with M best quality metrics,
for each section, obtain the average value of quality metrics for subblocks not included in the M selected metrics;
for each section, compress the mentioned M best quality metrics and average value by:
forming a vector containing M best quality metrics and said mean value; and
applying the Haar transform to this vector to get a compressed vector; and
the transmitter is configured to transmit this compressed vector for each section. 15. A wireless transmit / receive unit (WTRU), comprising:
receiver;
transmitter and
CPU;
wherein the receiver is configured to receive a plurality of Resource Block Groups (RBGs);
the processor is configured to:
measure the quality metric for each group of resource blocks;
divide this set of RBG into N groups, where N>1;
compress quality metrics for multiple RBGs in one group during the first reporting time interval,
and at the compression stage:
form a first vector containing quality metrics; and
apply the Haar transform to this vector to get the first compressed vector; and
repeat the compression of quality metrics for each of the N-1 remaining groups in the transmission time intervals following the first interval, thereby creating N-1 additional vectors;
the transmitter is configured to:
transmit the first compressed vector for multiple RBGs in one of the groups during the first report transmission time interval; and
transmit N-1 additional compressed vectors for each of the N-1 remaining groups in subsequent transmission time slots.

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