Evaluation of allocation algorithms in heterogeneous networks

Long Term Evolution (LTE) and Long Term Evolution-Advanced (LTEA) are by now mature technologies within 4G services. The constant increase of mobile data usage and emergence of new real-time and highdemanding applications such as mobile TV, HD videos, streaming contents have motivated the 3rd Generation Partnership Project (3GPP) to work on LTE and its enhanced version, LTE-Advanced. They are supposed to satisfy users’ requirements till the advent of the 5G, scheduled for the beginning of next decade. In order to support high data rate with low latency, LTE simplifies network architecture and uses orthogonal frequency division multiple access (OFDMA) for downlink transmission technology. LTE system performances largely depends on the high efficiency of MAC packet scheduler. This thesis has the purpose of evaluating the performances of the Smalloc scheduling algorithm in a more realistic scenario than before, by means of two important steps: firstly, it is used for scheduling and resource allocation in a heterogeneous network, a very common scenario nowadays where macrocells and smallcells coexist in order to enhance the overall capacity, but which is severely affected by interference. The algorithm is run either in a macrocell and in a smallcell and its performances are compared with those of other common scheduling algorithms. Secondly, the latency of Channel Quality Indicators (CQI) is introduced in order to test how Smalloc algorithm reacts to a non-instantaneous feedback from the user, again comparing this results with those of other algorithms under test. Finally a thorough analysis of trade-off between maximum capacity and fairness one scheduling algorithm can achieve is presented.