Research On Beamforming Technology In Cooperative Transmissions

With growing numbers of smart equipment and increasing data volume, future mobile networks will face the challenges of system capacity and coverage. Dense network deployment becomes necessary in the evolution of network architecture in the fifth generation (5G) systems.However, this can bring severe inter-cell interference. Cooperation among nodes in networks is an important approach for addressing the complex interference, which is regarded as a key technology in the implementation of 5G systems. By introducing the cooperation and data sharing among transmit (Tx) nodes, information cooperative transmission can jointly transmit data to serving users, which can turn the interferences into useful signals and improve the receive (Rx) performance of the cell edge users. Moreover, with advanced functions of equipment, the energy consumption poses a prominent problem, and also becomes a bottleneck for improving the performance of equipment and network. With energy harvesting, energy cooperation transmission has a great potential in addressing the shortage of energy. Tx points can transmit energy in a cooperative manner, making the energy-constrained equipment operate uninterruptedly. Since beamformiing can improve the performance in multi-antenna systems, to enhance the efficiency of cooperation, it is required to study the beamforming design in information and energy cooperative transmission systems. In addition, with the increasing scale of the future network, it is necessary to design scalable and low-complexity beamformers in order to reduce the implementation overhead in the systems.This paper focuses on multi-antenna information and energy transmission systems, and investigates the beamforming design in different scenarios. Consider non-ideal features of the systems and the network scale, this paper proposes centralized and decentralized beamformer designs, respectively, which are significant for research on cooperative transmissions in future 5G networks. The contributions and novelty of this paper can be summarized as follows:Firstly, this paper proposes centralized and distributed beamforming in multiple-input multiple-out (MIMO) information cooperative transmission systems, under the consideration of non-ideal backhaul.Based on a utility of mean square error (MSE) and backhaul consumption,an iterative beamformer design is proposed based on Hessenberg-Schur method, which can reduce the backhaul overhead while keeping the MSE performance. Moreover, consider the diverse quality of service (QoS)requirement at users, a sum rate maximization is studied under the constraints of backhaul capacity. An alternating updating centralized beamforming is proposed based on difference of convex (DC) method.Due to the increasing of the network scale, a decentralized beamforming design is proposed based on dual decomposition, and an implementation framework on cloud is designed. The proposed algorithm can substantially reduce the complexity without compromising the performance of centralized algorithm, which can be adapted to large scale and large capacity information cooperative transmission systems.Secondly, integrating the time splitting (TS) and power splitting (TS)techniques in energy transmission, the beamformers are designed based on the uplink and downlink performance irn energy cooperative transmission systems. For joint throughput of uplink and downlink,centralized and distributed algorithms are proposed respectively, which can also be extended to the case of imperfect channel state information(CSI). Further, consider the non-negligible circuit consumption at receivers in a multi-cell energy cooperative transmission system, a joint design of beamformers, time allocation and power splitting factors is proposed based on semidefinite relaxation (SDR), which can improve the uplink data rate while providing a guarantee of downlink performance.Consider the user capacity in practical systems, from the perspective of cross-layer design, a joint beamforming and user selection scheme is proposed based on DC, which can implement user selection in beamforming procedure. Compared with user selection based on mixed integer programming, the complexity can be substantially reduced.Thirdly, beamforming in simultaneous information and energy transmission systems is proposed, combined with energy cooperative cloud radio access networks (C-RAN). Consider the limited ability of fronthaul, the load on fronthaul is balanced to save the required bandwidth, under the constraints of data and energy transmission. An iterative centralized beamforming is proposed based on norm relaxation and second-order cone programming (SOCP). To further enhance the scalability of the algorithm, a decentralized beamforming is proposed based on alternating direction multiplier method (ADMM), which can decrease the required execution time of the algorithm, and improve the efficiency of the beamforming.