Research On Energy-Efficient Heterogeneous Wireless Networks

With the rapid development of mobile communication technologies, high quality communication experience with high speed and multiple services has been available for everyone. Meanwhile, the energy consumptions of communication systems increase dramatically. Green communication technologies aiming at energy efficiency optimization have attracted more and more attentions. Heterogeneous networks have great advantages in increasing network capacity and satisfying different services. It is a key feature of the future network deployment, and is widely concerned by the academic and industrial circles. Therefore, the energy efficiency and energy saving technologies of heterogeneous wireless networks are studied in this paper.The optimal small base station density for energy efficiency optimization of a two-tier heterogeneous network under coverage performance constraints is studied in this paper. And the influence of related parameters on network energy efficiency is also analyzed. The base stations are assumed to be distributed according to the Poisson Point Process, and the closed form expressions of the users' coverage probabilities and the network energy efficiency are derived using the stochastic geometry tool. Conclusions can be obtained that the coverage probabilities decrease with the increase of the small base station density, and the upper bound of the small base station density is determined. In addition, the relationship between energy efficiency and small base station density can be obtained through the derivation, leading to the optimal small base station deployment density for energy efficiency. Simulation results verify the validity of the theoretical derivations of the coverage probabilities and the energy efficiency, which also show the great advantage of stochastic geometry theory in the analysis of network energy efficiency.In this paper, the optimal power allocation for energy efficiency in heterogeneous network scenario is investigated. Assuming that there is a hot spot area in the network, and the minimum rate requirements are different between the hot spot users and the others. In this paper, constrained by the minimum rate requirements, the energy efficiency optimization problem is established. Since the objective function is not convex, we introduce fractional programming and its related theories to convert it into an equivalent parametric programming problem, which is solved by a two-lever interative algorithm. Finally, simulation results verify the convergence of the algorithm, and demonstrate that the proposed algorithm is superior to the spectral efficiency maximization algorithm in improving the energy efficiency of the system.