Highly Efficient Hybrid Beamforming Design In B5G Massive MIMO Systems

With the globalization of information,the demand for data capacity of wireless networks is rising rapidly.The available frequency resources of millimeter-wave(mmWave)far exceed the existing communication systems,which alleviates the problem of spectrum shortage.Thus,the research of millimeter communication gets wide attention.But high frequency communication also has its shortcomings,that is,the serious path attenuation of the signal,which brings challenges to its practical application.Beamforming technology in large scale multiple input multiple output(MIMO)systems can form highly directional signals,which can suppress interference and bring spatial multiplexing gain.Thus,the problem of signal attenuation can be effectively solved.Hybrid beamforming can reduce hardware overhead while maintaining satisfied performance.Therefore,hybrid beamforming is the first choice in the 5th generation(5G).How to design a low-cost and efficient hybrid beamforming strategy for large-scale MIMO systems is a problem worth studying.This paper focuses on the above problems and studies the key technologies of physical layer beamforming.Two typical scenarios are considered.The first one is the single cell hybrid beamforming design.Different from the traditional minimum mean square error(MMSE)communication transceiver,this paper directly designs the algorithms based on the bit error rate performance,which takes the reliability of signal transmission into consideration.Meanwhile,the deep unfolding neural network(NN)is utilized to reduce the computational complexity.The second scenario is the multi-cell coordinated user scheduling and hybrid beamforming design.Focusing on the cost overhead constraints of the actual implementation of multi-cell communication,the low complexity cooperative communication scheme is studied in this paper.Specifically,for the first scenario,this paper mathematically formulates the problem of hybrid transceiver design under the minimum symbol error rate(MSER)optimization criterion and then develops an MSER-based iterative gradient descent(GD)algorithm to find the related stationary points.In order to accelerate the convergence,a deep-unfolding algorithm is proposed,where the iterative GD algorithm is unfolded into a multi-layer structure and several trainable parameters are introduced to improve the overall performance of the system.To implement the training stage,this paper derives the relationship between adjacent layers’ gradients based on the generalized chain rule(GCR).The deep-unfolding NN is developed for both quadrature phase shift keying(QPSK)and M-ary quadrature amplitude modulated(QAM)signals,and its convergence is investigated theoretically.Furthermore,the transfer capability,computational complexity,and generalization capability of the proposed deep-unfolding NN are analyzed.The simulation results show that the deep-unfolding NN significantly outperforms the traditional MMSE based algorithms and can approach the MSER iterative algorithms at a reduced complexity.In the second scenario,the joint optimization of user scheduling and hybrid beamforming design under multi cell cooperative architecture is discussed in this paper.Considering the constraint of limited interactive information,the original problem is effectively approximated and is decomposed into two subproblems,which are solved iteratively.Then,in order to balance the capacity of edge users and the overall system performance,a greedy proportional fairness algorithm is proposed to obtain the user scheduling strategy.Several hybrid beamforming algorithms are designed with the fixed scheduling scheme.Specially,a low complexity approximation is proposed to further reduce the collaboration overhead.The simulation results show that the proposed joint user scheduling and hybrid beamforming scheme can effectively suppress inter-cell interference and greatly improve the average throughput of the system.The research results in this paper provide a theoretical and practical basis for the design of hybrid transceiver in large-scale MIMO systems,as well as technical solutions and theoretical support for the further development of wireless communication in the future.