The Study And Implementation Of Energy-Efficient Optimization Precoding For Multicell MIMO Networks

Nowadays,high data transmission speed is desired for the rapid development of the wireless communication,which can be achieved by equipping multiple antennas at Base stations(BS),without adding extra bandwidth.However,the corresponding power consumption increases dramatically,which contradicts the latest idea of Green Communications.Hence,the energy efficiency(EE)has been attracted the research interests recently,in which the computational complexity can be low and has fewer environmental impacts.In this paper,we consider the problem of Max-Min Energy-Efficient precoding over the multicell MIMO networks with receive correlation.Unfortunately,the underlying optimization problem is a nonconvex fractional programming problem,whose optimal solutions are hard to be found.Therefore,by using the block coordinate descent(BCD)approach,we transform the nonconvex problem into a series of convex subproblems.Based on the relationship between the user rate and the minimum mean square error(MMSE),the optimization of the transmitter matrix turns to a semidefinite program.Finally,the optimal solutions are achieved iteratively with the optimum EE.Simulation results demonstrate the convergence of the proposed algorithm,and illustrate that the proposed max-min energy-efficient algorithm can improve the value of EE in the system with a performance loss in terms of the sum rate.