Dynamic Traffic-aware Energy Efficient MIMO-OFDM System Reconfiguration

In the past decade, the number of mobile communication network users has sharply increased, causing a great demand on the transmission rate of mobile communication network. Mobile users are increasingly using mobile terminals participating in network activity, such as social software, blogging refresh, as well as audio and video viewing and downloading, etc. This requires the mobile communication system to efficiently utilize the limited wireless bandwidth to accommodate the new mobile network rate requirements. Nowadays, 4G mobile communication network system has widely put into use. 4G uses multiple input multiple output(MIMO) as well as orthogonal frequency division multiplexing(OFDM) to improve the spectral efficiency of the system.The main objective of a conventional cellular system is to achieve maximum capacity in limited given bandwidth, which is called spectral efficiency(SE) priority system. However, with widespread attention on the green communication, the waste of resources and environmental pollution problems caused by SE system had gradually led to widespread concern. So system designers began focusing on how to maximize the energy efficient(EE) of wireless network, to achieve energy conservation and environmental sustainability.In this thesis, we study energy-saving technologies in the field of wireless communication, and then propose a Traffic-aware energy efficient System Reconfiguration scheme(TSR) and a Traffic Classified energy efficient Scheduling method(TCS), to improve the energy efficiency of the MIMO-OFDM system.We first describe the background and research status of green communications, and introduce energy-saving theoretical basis and key technologies of wireless mobile communication, and present the definition and relationship of spectral efficiency(SE) and energy efficiency(EE) of MIMO-OFDM network. We also describe the effect of number of antennas of MIMO system on SE and EE, and the traditional adaptive modulation and coding technique, as bases for the following content in this work.Then we propose an energy efficient adaptation modulation and coding(AMC) method and introduce an energy efficient power distribution technology. Based on these technologies combined with a queuing model that we establish for link the call level QoS and outage probability, we propose the TSR and evaluate its performance by simulation on LTE system-level simulator. Numerical results reveal that TSR can maximize the EE through adapting some specified parameters of the system according to the traffic.At last, we explore the basic scheduling technologies of wireless mobile network and propose a Traffic Classified energy efficient Scheduling method(TCS). Simulation results show that, under different types of traffic, TCS can greatly improve the system’s EE compared with the basic scheduling technologies. At the end of the thesis, we conclude the thesis by pointing out some future possible research directions.