Research On Energy-saving Methods In Wireless Communication Networks

In this paper, the key energy saving methods in wireless communication networks are studied, and we mainly concentrates on two kinds of typical wireless communication networks, the cognitive radio(CR) network and the wireless powered communication network(WPCN), involving four major energy-saving methods, namely energy efficiency (EE) maximization method, the energy saving method considering hardware impairment, multi-antenna technology and multi-base station cooperative transmission.First of all, this paper studies the energy efficiency maximization method with non-perfect power amplifier (PA) considered in cognitive OFDM system. Compared to traditional communication systems, the peak-to-average power ratio (PAPR) issue of the transmission signal is severe in communication system using orthogonal frequency division multiplexing (OFDM) technology. Thus it is difficult to ensure that the PA works in its linear range all the time. Therefore, the traditional algorithm design based on the ideal linear PA is not applicable. To tackle with the aforementioned problem, this paper establishes the nonlinear energy consumption model of three kinds of power amplifiers, which are widely used in wireless communications,and proposes a modified energy efficiency maximization model. Due to the nonlinearity of PA, the original optimization problem is difficult to be solved directly by the traditional fractional programming method. Thus, we aim at designing a sub-optimal but efficient power allocation algorithm. Simulation results show the effectiveness of the proposed algorithm, and verify that the nonlinear characteristics of the power amplifier will have a significant impact on the system's energy efficiency.Next, this paper focuses on the energy efficiency issue in WPCN,and proposes an energy-saving strategy combining with beamforming technology of multi-antenna and cooperative transmission technology of multi-PB for the first time. In order to simplify the analysis, we first consider the scenario with two users. According to the communication process of WPCN, the original optimization problem is divided into two sub problems: the rate maximization and the energy consumption minimization, and the optimal resource allocation algorithm is designed by adopting Golden Search (GS). Furthermore, this paper considers a more general multi-user scenario, the optimization problem for this scenario is even more complex, which is difficult to directly obtain the optimal solution. Therefore, this paper designs a distributed and efficient sub-optimal algorithm by taking advantage of game theory. Finally, the simulation results validate the efficiency of the proposed strategy and algorithms, namely, multi-antenna beamforming technology and multi PB cooperative energy transfer technology have great potential to improve the energy efficiency of WPCN.