Research On Technology Of Energy Efficient Wireless MIMO Transmission

With the development of mobile communication technology, the concept of green communication achieves extensive attention. In the mobile communication system of the next generation, not only the spec-trum efficiency, but also the energy efficiency will be focused on. According to the energy efficiency op-timization in mobile communication system of the next generation, the paper researches on the technology of energy efficient wireless MIMO communication, considering the energy efficient power allocation and beamforming, the robust algorithm, the distributed implementation and the energy harvesting technology. The main work and innovations are as follows:1. This paper studied the energy efficient wireless MIMO transmission technology of the multi-antenna broadcast channel. Firstly, the maximization problem of the energy efficiency with the power constraints and signal to interference noise ratio constraints in the multi-antenna broadcast scenario was defined. By introducing the duality, the original non-convex problem that was difficult to be directly solved was simplified. By solving the dual virtual uplink transmission problem, the result was transformed to obtain the solution of the downlink transmission problem. The simulation results show that, compared to the existing energy efficiency optimization algorithm, the proposed algorithm has superior performance, easier implementation and lower complexity. Secondly, considering the fact that the system cannot obtain the actual accurate channel information, the robust energy efficiency optimization problem with the presence of channel estimation errors was defined. Using the relationship between the user rate and minimum mean square error and fractional programming, the planning parametric optimization problem was transformed into a polynomial optimization problem. According to the Lagrange duality and monotonous optimization theory, a robust energy efficiency optimization algorithm was described. The simulation results show that, compared to conventional non-robust energy efficiency optimization algorithm, the proposed robust algorithm gains higher energy efficiency and availability, with reducing the impact of channel estimation error.2. This paper studied the multi-cell single-user energy efficient wireless MIMO transmission technology. Firstly, the energy efficiency maximization problem with the power constraints was defined in the multi-cell downlink scene. By analyzing the problem, the solution of the problem was on the energy efficient Pareto boundary. Then the energy efficient Pareto boundary is defined by introducing the concept of interference temperature in the study of the cognitive radio. According to the iterative optimization theory, two distributed algorithms were proposed to achieve Pareto optimal energy efficiency. What’s more, the robust optimization algorithm considering the presence of channel estimation error was discussed. The simulation results show that the algorithm converges faster, needs smaller amount of information exchange between the base stations, and the performance is close to the centralized optimization algorithm. Secondly, the energy efficiency max-imization problem with power constraints was defined in the heterogeneous multi-cell downlink transmission scenario. By introducing the concept of cognitive radio interference temperature and considering the trans-mission characteristics of the small cell, a distributed heterogeneous energy efficiency optimization algorithm was proposed. And the simulation results show that the proposed algorithm converges faster and has superior energy performance with respect to the rate maximization algorithm.3. This paper studied the multi-cell multi-user energy efficient wireless MIMO transmission technology. At first, the energy efficiency maximization problem with the power constraints in the downlink multi-cell multi-user scene was defined. According to the fractional programming theory, the non-convex problem that is difficult to be directly solved was transformed into a subtraction solvable form. By introducing the concept of interference temperature, the optimization problem was transformed into multiple sub-problems. Finally, the iterative beamforming optimization and power allocation optimization algorithm was proposed to optimize the energy efficiency of the multi-cell multi-user scenario. Simulation results show that, compared to the optimized power allocation algorithm with given beamforming vectors, the proposed algorithm is superior and the energy efficiency is close to the centralized optimization algorithm.4. This paper studied the energy efficient wireless MIMO transmission technology with the power trans-fer system. Firstly, the information transmission model with power transfer and the energy efficiency maxi-mization problem in the multi-cell scene were defined. Secondly, by using the fractional programming, the non-convex optimization problem was transformed into a solvable form. Then the optimization problem was solved with the Lagrange optimization theory and the approximate optimization theory. Finally, the energy efficiency optimization algorithm with power transfer was proposed. The simulation results show that, com-pared to the existing energy efficiency optimization algorithms, the proposed algorithm is superior due to the power transfer technology.