Dynamic scheduling of non-interfering clusters in a distributed diversity communications system

Abstract

In certain embodiments, a cellular wireless communications network has clusters, each cluster having a plurality of cells and a cluster-level controller that dynamically divides the cluster into non-interfering sub-clusters for each resource allocation unit (e.g., physical resource block) . Each sub-cluster has one or more cells that transmit to a single user in the cluster for the resource allocation unit, and at least one sub-cluster has at least two cells that transmit to a single user for the resource allocation unit using a distributed diversity mode of communication in which the at least two cells transmit the same data to the single user. The controller divides the cluster into sub-clusters based on determinations of whether users in the cluster are susceptible to interference from non-serving cells in the cluster. By assigning potentially interfering, non-serving cells to the sub-cluster for a user, those non-serving cells are eliminated as sources of interference.

Description

BACKGROUND[0001]1. Field of the Invention[0002]The present invention relates to wireless communications and, more specifically but not exclusively, to cellular communications systems that can operate in a distributed diversity mode in which multiple base stations transmit the same data to a single user.[0003]2. Description of the Related Art[0004]This section introduces aspects that may help facilitate a better understanding of the invention. Accordingly, the statements of this section are to be read in this light and are not to be understood as admissions about what is prior art or what is not prior art.[0005]In order to realize the enormous data capacity demand of smart mobile devices and meet user quality-of-service requirements, cellular communications systems having low-power, low-cost, small cells have been widely considered as one of the most-promising solutions. However, there are three major limitations: 1) when additional small cells are added to the system to improve capa...

AI Technical Summary

Benefits of technology

This approach reduces interference, lowers the cost of increasing cell density, and efficiently manages bursty traffic by ensuring that only necessary cells transmit, thereby improving user experience and network capacity while minimizing resource waste.

Problems solved by technology

However, there are three major limitations: 1) when additional small cells are added to the system to improve capacity, the cell-edge users (i.e., users located at or near the edge of one cell that is adjacent to another cell) can experience a lot of strong interference levels degrading the throughput performance and actual user experience; 2) each cell is costly to build and operate; and 3) the traffic at each cell fluctuates over time such that the cell may have to be designed to handle the maximum traffic expected, causing a waste of processing resources at off-peak times.

As the density of a small-cell network increases, the interference increases.

Although this type of transmission scheme achieves good performance, it has a high backhaul requirement because CSI exchange is required between BSs.

CSI exchanges among base stations is not required for this type of transmission scheme; however, the performance is typically not as good as the one offered by the coherent joint transmission scheme.

Therefore, it is not suitable for unicast transmission, where BSs need to support independent communications with multiple UEs simultaneously.

The above solutions are not sufficient because the cost of increasing the density of small-cell architectures is high.

It is also inefficient because traffic is likely bursty in time, resulting in processing resources being wasted when traffic is light.

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