Energy Optimization Algorithms For Lte-Advanced System

Nowdays, energy consumption of wireless cellular network is a very important research topic. Low energy efficiency will not only bring a waste of energy, but also aggravate environmental degradation worldwide. In addation, With the improvement of people’s wireless speed and coverage requirements, energy consumption of communications equipment also will increase dramatically over the next ten years. Therefor, either profitability or reducing the effects of evironment drive worldwile researchers and standards organizations to do their in-depth study. In this paper, we investigate the celluar network’s planning and optimization and propose algorithms which can reduce the communication devices’energy consumption in the case to ensure users’QoS in order to improve the energy efficiency of the whole system.The main work includes:I, summerizing the metric of evaluating network’s performance by some reseaching, and then doing a survey about the power saving technology of cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we sum up some approaches to reduce base station’s energy consumption, e.g. cell layout adaptation or relay. After introducing energy efficiency metric, it will inevitably impact existing communications network performance. So in the following of this paper we summerize the restrict relations between the energy efficiency and deployment costs, spectral efficiency, bandwidth, power, latency by a few simple model.II, for large scale network in the dense urban area, proposing an energy efficient network planning and optimizing algorithm which tunes the base stations and relays’ antenna parameters such as azimuth, downtilt, transmitting power and height to reduce the energy consumption and improve users’experience of the whole network. Simulation results show that compared with the traditional algorithm the proposed one can achieve the same performance with the computation time reduceding within the acceptable range.Ⅲ, for the characteristics of uneven distribution of traffic in time and space domain in practical networks, proposing a semi-dynamic base stations switching-off algorithm which switches off the antennas or the whole base station in low traffic areas, and transfer the traffic to adjacent base stations, then re-allocate the remainings’power to reduce the energy consumption of the entire network. From the simulation results we can see that this algorithm can greatly reduce the energy consumption of the network, especially in lower QoS erea.The proposed network optimization and base station switching off algorithms can improve the system’s energy effiency, and minimize the impact on users rate meanwhile, which have a high value on both theory and applications.