Research On Resource Allocation For Large-scale Antenna Array And Novel Multiple Access

The rapid development of mobile Internet and Internet of Things puts forward high demands on the spectral efficiency,energy efficiency,access capacity and other indicators of the future mo-bile communication system.As one of the key technologies of the future mobile communication system,the large-scale antenna array technology achieves a substantial increase in the spectrum efficiency by increasing the number of antennas.However,on the one hand,energy consumption of the system grows as the number of antennas grows and then the energy efficiency is impaired.On the other hand,pilot contamination is aggravated as the number of antennas grows and then resource allocation in multi-cell get more complex.As one of the key technologies of the future mobile communication system,the novel multiple access technology greatly improves the spectrum efficiency and access capacity,by resource multiplexing and non-linear detection algorithm.Howev-er,resource multiplexing may reuse more resource domains and introduce more optimization objects and complex interference to resource allocation.In view of these problems,the thesis studies the resource allocation of large-scale antenna array and novel multiple access technologies.Firstly,the thesis investigates the resource allocation method of large-scale antenna array tech-nology.As for the high energy efficiency power control problem in multi-cell uplink scenario,the constrained Markov decision process method is introduced to characterize the energy efficiency,and then the high energy efficiency power control problem is formulated as a constrained Markov decision process based optimization problem.A optimization algorithm is proposed to solve the problem and obtain the globally optimal power control scheme.As for the proposed algorithm,Lagrange method is first utilized to transfer the constrained Markov decision process based optimization problem to Markov decision process based optimization problem,and the improved value iterative algorithm is proposed to achieve the globally optimal power control strategy.In the improved value iterative algorithm,value iterative algorithm is in charge of the inner loop,and Q-learning is in charge of the outer loop.For the proposed algorithm,on the one hand,the achieved optimal decision rules can be utilized to establish an off-line lookup table,so as to avoid frequent computation.On the other hand,relevant parameters in the algorithm can be adjusted to achieve the trade-off between system performance and computational complexity.The simulation results show that the proposed algorithm can achieve the globally optimal performance.Secondly,the thesis investigates the novel multiple access technology,and proposes pattern division multiple access with large-scale antenna array(PDMA-LSA).Large-scale antenna array and Pattern division multiple access are bonded based on the beam resources in the spatial domain.In the proposed scheme,pattern is designed in both power domain and beam domain in a joint manner.Pattern mapping at the transmitter utilizes power allocation and beam allocation to superpose user signals,while hybrid detection of spatial filter and successive interference cancellation is employed at the receiver to separate the superposed multiple-domain signals.The PDMA-LSA reduces the computational load of the non-liner detector while greatly enhancing the access capacity.In addition,the PDMA-LSA spontaneously achieves the integration of large-scale antenna array into multiple access,and can give full play to the potential of the two technologies,which makes it significantly different compared to the other non-orthogonal multiple access schemes.Simulation results show that the PDMA-LSA achieve a slight performance gain compared with orthogonal multiple access and power-domain non-orthogonal multiple access scheme,even in the absence of resource allocation.Finally,the thesis investigates the resource allocation of novel multiple access technology.For the proposed PDMA-LSA,power control and beam allocation are studied.In the research on the power control problem,the convexity of the energy efficiency optimization problem is proved,and then the globally optimal transmit power control scheme is obtained.In the research on the beam allocation problem,the physical significances of the beams are first analysed,and then the low interference optimization problem is reduced dimension by means of technical characteristics of beamforming and spatial filter,which greatly reduces the computation complexity.Simulation results show that the power control method contributes slightly to performance gain,and the beam allocation method achieves significant performance improvement.