System and related methods for clustering multi-point communication targets
First Claim
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1. A method comprising:
- measuring one or more performance characteristics associated with each of at least a subset of a plurality of targets in a wireless communication system, each target a communication target with which to engage in two-way communication, measuring the performance characteristics including;
initializing K sets of weights;
estimating the signal to interference and noise ratio (SINR) for each target for each of the K weights;
selecting one of the K weights for each of the targets that maximizes each targets SINR, to produce K clusters of targets based, at least in part, on each target'"'"'s SINR;
identifying a target within each of the cluster(s) with a lowest SINR;
generating a new weight for each of the cluster(s) based, at least in part, on the SINR of the identified target within the cluster(s);
estimating the performance characteristics of each of the target(s) within each of the cluster(s) using the generated new weight for each of the cluster(s); and
regrouping targets according to the weights that provide the best SINR for each of the targets; and
selectively building one or more clusters, each cluster including one or more target(s) and which share common wireless communication channel(s), based at least in part on the performance characteristics.
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Abstract
A system and related methods for clustering multi-point communication targets is presented. According to one aspect of the invention, a method comprising measuring one or more performance characteristics associated for each of at least a subset of a plurality of targets in a wireless communication system, and selectively building one or more clusters, each cluster including one or more target(s) and sharing a wireless communication channel, based at least in part on the performance characteristics.
45 Citations
19 Claims
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1. A method comprising:
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measuring one or more performance characteristics associated with each of at least a subset of a plurality of targets in a wireless communication system, each target a communication target with which to engage in two-way communication, measuring the performance characteristics including; initializing K sets of weights; estimating the signal to interference and noise ratio (SINR) for each target for each of the K weights; selecting one of the K weights for each of the targets that maximizes each targets SINR, to produce K clusters of targets based, at least in part, on each target'"'"'s SINR; identifying a target within each of the cluster(s) with a lowest SINR; generating a new weight for each of the cluster(s) based, at least in part, on the SINR of the identified target within the cluster(s); estimating the performance characteristics of each of the target(s) within each of the cluster(s) using the generated new weight for each of the cluster(s); and regrouping targets according to the weights that provide the best SINR for each of the targets; and selectively building one or more clusters, each cluster including one or more target(s) and which share common wireless communication channel(s), based at least in part on the performance characteristics. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A communication station comprising:
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wireless communication resources; and a communication agent, coupled with the wireless communication resources, to populate cluster(s) with one or more communication target(s) based, at least in part, on one or more estimated performance characteristics associated with the targets that share a common wireless communication channel in the cluster(s), and to develop a weighting value for at least a subset of the populated clusters to generate a transmission beam to target(s) within the cluster(s) based, at least in part, on the developed weighting value; the communication agent including a clustering engine, to measure one or more performance characteristics associated for each of at least a subset of a plurality of targets in a wireless communication system, and to selectively build one or more clusters, each cluster including one or more target(s) and sharing a wireless communication channel, based at least in part on the performance characteristics, wherein to measure the performance characteristics including initialize K sets of weights, estimate the signal to interference and noise ratio (SINR) for each target for each of the K weights, and select one of the K weights for each of the targets that maximizes each targets SINR, and to selectively build the cluster including produce K clusters of targets based, at least in part, on each targets SINR, identify a target within each of the cluster with a lowest SINR, dynamically generate a new set of weights based, at least in part, on the SINR of the identified target, estimate the performance characteristics of each of the target(s) within each of the cluster(s) using the generated new weight for each of the cluster(s), and regroup targets in clusters according to the weights that provide the best SINR for each of the targets. - View Dependent Claims (9, 10, 11, 12, 13)
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14. In a wireless communication system implementing general packet radio services (GPRS), a method comprising:
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populating cluster(s) with one or more communication target(s) based, at least in part, on measured performance characteristics of each of the one or more target(s) that share a common wireless communication channel in the cluster(s), measuring one or more performance characteristics associated for each of at least a subset of a plurality of targets in a wireless communication system, and selectively building one or more clusters, each cluster including one or more target(s) and sharing a wireless communication channel, based at least in part on the performance characteristics, measuring the performance characteristics including initializing K sets of weights, and estimating the signal to interference and noise ratio (SINR) for each target for each of the K weights, and selectively building the clusters includes selecting one of the K weights for each of the targets that maximizes each targets SINR, to produce K clusters of targets based, at least in part, on each targets SINR, identifying a target within each cluster with a lowest SINR, generating a new weight for each of the cluster(s) based, at least in part, on the SINR of the identified target, estimating the performance characteristics of each of the target(s) within each of the cluster(s) using the generated new weight for each of the cluster(s), regrouping targets according to the weights that provide the best SINR for each of the targets; and developing a weighting value for at least a subset of the populated clusters to generate a transmission beam to target(s) within the cluster(s) based, at least in part, on the cluster spatial signature. - View Dependent Claims (15, 16, 17, 18, 19)
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Specification