APPROACHES TO SELF-CLUSTERING RESOURCE BLOCKS FOR IMPROVED NOISE ESTIMATION THROUGH IMBALANCE DETECTION
Introduced here are processes in which noise covariance is estimated across resource blocks that have similar distributions of noise. These processes result in more accurate estimation of noise occurring in a given channel, as accuracy can be improved by increasing the number of resource blocks being examined while also identifying and then filtering those resource blocks that are contaminated with interference. At a high level, these processes represent an automated approach to detecting imbalance between resource blocks with noise and resource blocks with interference in addition to noise and then forming clusters of resource blocks having similar characteristics to provide more samples that can be used in estimating noise covariance.
1 . A method for distinguishing resource blocks having dissimilar noise distributions, the method comprising:
initializing a sliding window having a size of m resource blocks that occupy bandwidth of a given channel, m being a value of at least two;
calculating average covariance of noise in the m resource blocks contained in the sliding window;
producing a distance metric by comparing the average covariance of the m resource blocks to covariance of noise in a next resource block that follows the m resource blocks;
determining that the distance metric exceeds a threshold;
defining, in response to said determining, the m resource blocks as representative of a cluster of resource blocks having comparable noise distributions; and
associating the average covariance with each resource block of the m resource blocks.
2 . The method of claim 1 , further comprising:
reinitializing, responsive to said determining, the sliding window such that the sliding window contains n resource blocks that follow the m resource blocks, n being a value of at least two,
wherein the next resource block is the first resource block in the n resource blocks.
3 . The method of claim 1 , wherein the threshold is based on the given channel.
4 . The method of claim 1 , wherein the bandwidth occupied by each resource block is based on spacing configuration of subcarriers occupied by the resource blocks of the given channel.
5 . The method of claim 1 , wherein said determining indicates that the next resource block is a different type from the series of resource blocks.
6 . The method of claim 5 , wherein each resource block in the series of resource blocks is affected by interference while the next resource block is not affected by interference.
7 . The method of claim 5 , wherein each resource block in the series of resource blocks is not affected by interference while the next resource block is affected by interference.
8 . The method of claim 1 , wherein said associating comprises:
indicating in a data structure that the average covariance is representative of each resource block of the m resource blocks,
wherein the data structure includes an entry for each resource block of the given channel, and
wherein each entry associated with one of the m resource blocks is populated with the average covariance.
9 . A non-transitory computer-readable medium with instructions that, when executed by a processor of a computing device, cause the computing device to perform operations comprising:
initializing a sliding window so that the sliding window contains a series of resource blocks that occupy bandwidth of a given channel;
calculating average covariance of noise in the series of resource blocks contained in the sliding window;
comparing the average covariance of the series of resource blocks to covariance of noise in a first resource block that follows the series of resource blocks; and
determining, based on an outcome of said comparing, whether the first resource block has a comparable amount of interference as the series of resource blocks.
10 . The non-transitory computer-readable medium of claim 9 , wherein the given channel is a physical channel defined in accordance with the 5G New Radio (NR) standard.
11 . The non-transitory computer-readable medium of claim 9 ,
wherein said comparing results in a distance metric being produced that is indicative of similarity in terms of interference in the series of resource blocks and interference in the first resource block, and
wherein said determining comprises:
establishing that the distance metric exceeds a threshold, and
defining the series of resource blocks as representative of a cluster of resource blocks having a comparable amount of interference.
12 . The non-transitory computer-readable medium of claim 11 , further comprising:
associating the average covariance with each resource block in the series of resource blocks.
13 . The non-transitory computer-readable medium of claim 9 ,
wherein said comparing results in a distance metric being produced that is indicative of similarity in terms of interference in the series of resource and interference in the first resource block, and
wherein said determining comprises:
establishing that the distance metric does not exceed a threshold, and
expanding the sliding window so that the sliding window contains the series of resource blocks and the first resource block.
14 . The non-transitory computer-readable medium of claim 13 ,
wherein the series of resource blocks and the first resource block are representative of a second series of resource blocks, and
wherein the operations further comprise:
calculating average covariance of the second series of resource blocks contained in the expanded sliding window;
comparing the average covariance of the second series of resource blocks to covariance of a second resource block that follows the second series of resource blocks; and
determining, based on an outcome of said comparing, whether the second resource block has a comparable amount of interference as the second series of resource blocks.
15 . The non-transitory computer-readable medium of claim 14 ,
wherein the operations are performed repeatedly until all resource blocks that occupy bandwidth of the given channel are assigned to a cluster of resource blocks having a comparable amount of interference, and
wherein each cluster of resource blocks includes at least one resource block.
16 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
outputting a list of all resource blocks that occupy bandwidth of the given channel,
wherein the list specifies, for each resource block, a covariance value that is representative of the average covariance calculated for the corresponding cluster of resource blocks.
17 . A method comprising:
determining that resource blocks that occupy bandwidth of a given channel have been sorted into a series of clusters,
wherein each cluster includes at least one resource block, and
wherein the at least one resource block included in each cluster has a comparable amount of interference;
identifying a given cluster of the series of clusters whose number of resource blocks falls beneath a threshold;
establishing that a first cluster that precedes the given cluster has a comparable amount of interference from a same source as a second cluster that follows the given cluster;
combining the first and second clusters into a superset cluster by
computing a covariance metric based on average covariance of the first cluster and average covariance of the second cluster; and
associating the covariance metric with each resource block included in the first and second clusters.
18 . The method of claim 17 , wherein said combining causes a number of clusters to be lessened without filtering any resource blocks.
19 . The method of claim 17 , wherein said establishing is based on a comparison of the average covariance of the first cluster and the average covariance of the second cluster.
20 . The method of claim 17 , wherein said identifying, said establishing, and said combining are performed repeatedly until the superset cluster includes at least a predetermined number of resource blocks.