Traffic aware scheduling for interference mitigation in cognitive femtocells

Abstract

Femtocells are designed to co-exist alongside macrocells, providing spatial frequency re-use, higher spectrum efficiency and data rates. However, interference between two networks is imminent; therefore, ways to manage it must be employed to efficiently avoid problems such as coverage holes. In this chapter, we employ cognitive radio enabled femtocells (CFs) and propose a novel scheduling algorithm to address the problem of cross and co-tier interference in a two-tier network system. Macrocell user equipments (MUEs) usually transmit with varying traffic loads and at times it is highly likely for their assigned resource blocks (RBs) being empty. Based on the interweave concept of spectrum assignment, CFs in our proposed scheme assign the RBs of MUEs with a low-data traffic load and low-interference temperature to its FUEs, thereby mitigating cross-tier interference, whereas co-tier interference is mitigated by resolving the contention for the same RBs by employment of matching policy among the coordinating CFs. System-level simulations are performed to investigate the performance of proposed scheme and results obtained are compared with best channel quality indicator and proportional fair schemes both in no fading and fading conditions. It is found that our proposed scheduling scheme outperforms compared schemes in no fading conditions; however, it provides competitive results when fading conditions are considered. The concept of matching policy successfully mitigates the effect of co-tier interference in collocated femtocells by providing improved signal-to-interference-plus-noise ratio, throughput and spectral efficiency results, thereby proving the effectiveness of scheme.