Radio resource sharing for MTC in LTE-A: An approach based on the bipartite graph

Machine to machine (M2M) communications pose significant challenges to the cellular networks due to its unique features such as the massive number of machine type devices (MTDs) as well as the limited data transmission session. Thus, advanced cellular network releases, such as long-term evolution (LTE) and LTE-Advanced (LTE-A), optimally designed to support human to human (H2H) communications, should cater to M2M communications. In this paper, we consider an M2M/H2H coexistence scenario where a simultaneous access to the spectrum is enabled. Taking the opportunity of the new device to device (D2D) communication paradigm offered in LTE-A and at the aim of enabling an efficient resource sharing, we propose to combine M2M and D2D owing to the MTD low transmit power. First, we formulate the resource sharing problem as a maximization of the sum-rate, problem for which the optimal solution has been proved to be non deterministic polynomial time hard (NP-Hard). Then, we formulate the problem as a novel interference-aware bipartite graph to overcome the computational complexity of the optimal solution. Thus, we consider here a two-phase resource allocation approach. In the first phase, H2H radio resource assignment is performed in a conventional way. In the second phase, we introduce two algorithms, one centralized and one semi-distributed to perform the M2M resource allocation. The computational complexity of both introduced algorithms is of polynomial complexity. Simulation results show that the semi-distributed M2M resource allocation algorithm achieves quite good performance in terms of network aggregate sum-rate with markedly lower communication overhead compared to the centralized one.