Inter-Femtocell Interference Identification and Resource Management

Abstract

OFDMA femtocell is a promising technology to improve indoor cellular network coverage cost-effectively. Large-scale deployment of femtocells in the urban area is expected to be realized in the near future. However, inter-femtocell interference significantly limits the achievable throughput of an OFDMA femtocell system, which calls for interference management tailored for femtocell networks. A typical approach to mitigate inter-femtocell interference is known as resource isolation, which aims at assigning non-overlapping resources to interfering femtocells. One of the main challenges for interference mitigation in femtocell networks is that end consumers often install the femtocells. Very limited information about the femtocells is available, making it hard to decipher the inter-femtocell interference. Previous studies either take time to resolve collisions online or adopt a conservative approach to identify interferers. Although the latter approach avoids wasting time on resolving collisions, it may result in resource underutilization. In this paper, we propose an efficient method to identify inter-femtocell interference by analyzing the received patterns observed by mobile stations. We conducted experiments on GNU Radio/USRP to demonstrate that the proposed interference identification method can successfully identify real interferers while excluding non-interfering femtocells from suspect femtocells. Based on the proposed interference identification, we propose a weighted vertex-coloring based resource assignment algorithm to allocate resources with better fairness and higher throughput.