Device-to-Device (D2D) communications underlying cellular networks are a way to increase the network capacity and potentially save the battery lifetime of closely located physical devices. However, D2D communications can generate significant interference to the cellular network when the same resources are shared by both systems. Therefore, the design of Power
Control (PC) schemes is required to keep the interference under control, get energy-efficient transmissions and protect cellular devices. In this work, we investigated operating points of the Soft Dropping Power Control (SDPC) and Open-Loop Power Control (OLPC) schemes for energy efficiency of cellular and D2D communications in uplink OFDMA systems. Results indicate that the SDPC performs better for cellular links and OLPC provides higher gains for D2D links in terms of energy efficiency.While high values of pathloss compensation factor α have been widely used in OLPC studies for the LTE standard, α ∈ {0.4, 0.5} has provided high energy efficiency gains for D2D links. Also, by properly setting the parameters of the OLPC applied to D2D links in uplink and considering the most favorable scenario for sharing resources in all cells, the minimum cost for having spectral efficiency gains for D2D communications represents an impact of 11 % on the system spectral efficiency of cellular communications.
Heterogeneous Networks (HetNets) are considered a technology option capable of improving system capacity and spatial spectrum reuse. However, high spectrum reuse causes high inter-cell interference among macro and small cells. Almost Blank Subframe (ABS) is a method of the Enhanced Inter-Cell Interference Coordination (e-ICIC) framework proposed for LTE systems as a means to mitigate interference among macro and small cells, which mutes some of macro cell transmissions in selected subframes to reduce interference to small cells, orthogonalizing macro and small cell transmissions in time-domain. In this work, we use Moving Average Crossover (MAC) based on trading know-how to propose a new dynamic ABS e-ICIC algorithm. Using system-level simulations, we attest that the proposed algorithm outperforms the best fixed e-ICIC by 6.4% in terms of capacity.
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