Research On Power Control For Small Cell Networks In Fifth Generation Mobile Communication System

With the rapid development of wireless communication technologies, spectrum efficiency (SE) and en-ergy efficiency (EE) requirement increases dramatically, which gives highly demand to improve the perfor-mance of 5G mobile communication systems. Small cell networks (SCNs), composed of a large number of small cells with small coverage area and low transmission power, are expected to have higher SE and EE. However, new features including dense multi-cell, two-tier network and self-organizing are emerged in the small cell networks, which led to the complicated resource management. In this paper, the power control problems is studied to improve the performance of small cell communication systems.Firstly, the spectrum efficiency power control algorithm for the small cell networks is studied. We first formulate a power control game based on non-cooperative game theory. In the power control game, an optimization problem with given total power constraints is formulated for each small base station (SBS). Then, the geometric water-filling approach is proposed to solve the optimization problem for each SBS. Simulation results show that the throughput can be improved by 20% by using the proposed algorithm. In addition, we can observe that there is a tradeoff between EE and SE. Therefore, we can optimize system performance according to different requirements of EE and SE.Secondly, the energy efficient power control for small cell network is investigated. We propose a distributed energy efficient power control algorithm and formulate a power control game based on non-cooperative game theory, which allows the small base stations (SBSs) to take individual decisions. In the non-cooperative power control game, a nonconvex optimization problem is formulated for each SBS to maxi-mize their energy efficiency (EE). By exploiting the properties of parameter-free fractional programming and the concept of perspective function, the nonconvex optimization problem for each SBS is transformed into an equivalent constrained convex optimization problem. Then, the constrained convex optimization problem is converted into an unconstrained convex optimization problem by exploiting the mixed penalty function method. The inequality constraints are eliminated by introducing the logarithmic barrier functions and the equality constraint is eliminated by introducing the quadratic penalty function. The existence and the unique-ness of the NE in the non-cooperative power control game are further proved through proper mathematical manipulations. Simulation results show that the EE of proposed scheme increases with the maximum transmit power, and that the EE almost remains constant when the maximum transmit power is large enough, while the EE sharp decrease when the maximum transmit power is large enough by using the existing scheme.Thirdly, the spectrum efficiency and low power consumption power control for small cell networks is investigated. We model the power control problem based on Stackelberg game for both MBS and SBS, in which the MBS player is leader and the SBS player are followers. The formulated power control problem is solved by two-step iterative algorithm. In the first iteration, the leader makes its decision according to the followers'actions and the expression of the optimal transmission power is derived for the MBS. In the second iteration, the transmission power of the SBSs can be achieved by a iterative algorithm and the implicit expression of the optimal transmission power is derived for the SBSs. Simulation results show remarkable improvements in terms of MBS's performance by using the proposed algorithm compared with the non-cooperative game theory based algorithm. And the effectiveness of the Nash equilibrium are improved to some extent by using the proposed algorithm.Finally, energy efficient power control for the uplink two-tier networks where a macrocell tier with a massive multiple-input multiple-output (MIMO) base station is overlaid with a small cell tier is investigated. The distributed power control algorithm is implemented by decoupling the EE optimization problem into two steps. In the first step, we propose to assign the users on the same resource into the same group and each group can optimize its own EE, respectively. In the second step, multiple power control games based on evolutionary game theory (EGT) are formulated for each group, which allows each user optimizing its own EE. In the EGT-based power control games, each player selects a strategy giving a higher payoff than the average payoff, which can improve the fairness among the users. The proposed algorithm has a linear complexity with respect to the number of subcarriers and the number of cells. Simulation results show that the EE of each user approximately approaches the average EE by using the proposed distributed algorithm, while there are quite great differences among the users by using the NGT-based algorithm. Thus, the fairness and the effectiveness of the Nash equilibrium are improved remarkably by using the proposed algorithm.