Decentralized adaptive range expansion in heterogeneous WCDMA networks

Abstract

A decentralized adaptive range expansion for small cells deployed in the macro cell coverage area is proposed and analyzed in WCDMA heterogeneous networks. The algorithm is based on a direct traffic balancing between macro and small cells assuming that the macro cell periodically informs all other cells in its coverage area on its load using some adaptation performance metric. Then, each small cell can compare its own adaptation metric with the macro's and decide if it could accept or release some users by means of updating its own range expansion parameter. To study such a decentralized adaptation algorithm we introduce a semi-analytic approach (analytic for the given signal-interference scenario) based on the theory of absorbing Markov chains. It allows us to study convergence properties of the algorithm such as convergence probability, convergence rate, effects of selection of algorithm parameters and adaptation metrics, probability of non-convergence (ping-pong) and possible ways of its recovery. The semi-analytic study is illustrated in a dual carrier network configuration with a dedicated carrier for small cells.