Inference-driven dynamic access scheme for interference management in heterogeneous networks

We propose a scheme for interference management in wireless heterogeneous networks. We, specifically, consider the problem of downlink interference of a Home eNB (HeNB) to nearby macrocell user equipments (MUEs) served by a macrocell base station. We propose a distributed, self-learning channel access mechanism that enables the HeNB to adaptively change its access to channels shared with neighboring MUEs. Basically, the HeNB accesses the channel with a probability that is updated based on the overheard uplink feedback information from neighboring MUEs. We formulate an optimization problem with the goal of maximizing the achieved rate for the HeNB under the constraint of maintaining a quality of service (QoS) requirement for neighboring MUEs.