The value of dynamic clustering of base stations for future wireless networks

Abstract

Multicell Cooperative Processing (MCP) has been identified as a key technology to underpin future 4G wireless systems. In MCP enabled systems, the Base Stations (BSs) of the network form groups that jointly process user signals in order to reduce inter-cell interference and boost performance. Although MCP can lead to significant gains, it is also accompanied by overheads that are proportional to the number of BSs that are grouped together, called the cluster size. Thus it is crucial that BS clusters are of a limited size and formed in an intelligent way for achieving high performance. In this paper we present different dynamic clustering approaches for forming BS clusters of limited size. BS clustering is no longer based on geographical criteria, e.g. proximity-based static clustering, but on the channel conditions that users experience to different BSs. Dynamic clustering algorithms capture the effect of changing channel conditions and thus exploit the inherent macrodiversity of multicell wireless systems. More specifically, we propose a dynamic clustering scheme that provides significant gains while being resilient to inaccurate information on the state of wireless channels.