Beam forming optimization method and device for minimizing transmitting power of ultra-dense network

Abstract

The invention discloses a beam forming optimization method and device for minimizing the transmitting power of an ultra-dense network. According to the method disclosed in the invention, in an ultra-dense network with a macro base station and a plurality of small base stations, a user accesses a corresponding base station according to the position of the user; transmitting beam forming of a macrobase station and all small base stations is jointy optimized by constructing an optimization problem where QoS (Quality of Service) requirement of the user and the limitation of backhaul rates of the small base stations are takens as constraints and minimization of total transmitting power of the system is taken as a target. The optimization process comprises the following steps: firstly, introducing an intermediate variable; iteratively solving an optimization problem related to an intermediate variable, solving an SDP problem in each iteration process, obtaining a series of transmitting beam forming meeting the constraint of the original problem as alternative solutions by adopting Gaussian randomization on the basis of the optimal intermediate variable, and selecting a group of solutions with the minimum transmitting power as the optimal transmitting beam forming. Compared with a traditional zero-forcing transmission solution, the method is advantageous in that total transmittingpower can be remarkably reduced.

Description

technical field [0001] The invention relates to an ultra-dense network, in particular to a beamforming optimization method and device for minimizing the transmission power of an ultra-dense network. Background technique [0002] With the continuous development of the communication system, the demand for network information transmission rate continues to increase, and the traditional macro base station cellular system is difficult to cope with the challenges brought by the explosive growth of communication services. It will be further narrowed, and the macro base station plus a large number of various types of small base stations form a macro-micro heterogeneous ultra-dense network (UDN). [0003] However, with the large-scale deployment of small base stations, energy consumption and backhaul rate requirements are problems that need to be solved urgently. On the one hand, as the number of base stations increases, the energy consumption and cost of base stations will also ris...

AI Technical Summary

Problems solved by technology

[0004] In the MIMO transceiver system, multiple antennas can bring space diversity and multiplexing, improve the reliability of data transmission and channel gain, but the interference between users will have a certain impact on the signal-to-interference-noise ratio (SINR) of the receiving end. affect service quality

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