Research On Resource Allocation In Massive MIMO Systems

Next generation 5G wireless communication systems are already promis-ing mainfold increase in data rate,connectivity and quality of service(QoS).To meet the explosive growth in data demand for higher data rates,a novel tech-nique called Massive multiple-input multiple-output(Massive MIMO)has been proposed to further improve system performances,especially energy efficiency(EE)and spectral efficiency(SE)these two critical metrics.The fundamental method of massive MIMO is that,as the number of antennas at the base station(BS)goes to infinity,the channels between transmitters and recievers tend to be asymptotic orthogonal,therefore multi-user interference can be mitigated,which is also called favorable propagation.This technology is considered to be a potential candidate that can achieve better EE performance coinciding with"green radio".In terms of the strengths of massive MIMO,the resource allocation of enengy-efficient Massive MIMO systems is investigated in this paper.Ini-tially,the characteristics of massive MIMO are specifically analysed with the aid of RMT tools,the EE performance is fully studied in two scenarios,i.e.,the downlink of a Massive MIMO single cell and Massive MIMO relay networks.Moreover,we analysed several factors,such as the number of antennas,user scheduling and power allocation,which have significantly effects on EE per-formance.The resource allocation problems for Massive MIMO systems are solved based on the analysed results above.The proposed schemes can jointly optimize several system configuration parameters based on large-scale fading with low complexity,meanwhile ensuring certain constraints.The main innovations and contributions are summarized as follows:1)The characteristics of massive MIMO systems are analysed,such as channel hardening,energy efficiency and power consumption.We derive and study sum rate and EE performances of the considered system by means of RMT,and prove that when deploying large-scale antennas,the channel vectors appears to be asymptotically orthogonal,thus can improve system performance in terms of raising spectral efficiency and decreasing transmit powers.More-over,a more realistic and accurate power consumption model is given consid-ering system configurations which affects circuit power consumption signifi-cantly compared to small MIMO systems.2)We develop a low-complexity resource allocation scheme for the down-link of an energy-efficient Massive MIMO system.A single cell where the base station adopts zero-forcing processing is considered.Asymptotic expressions of sum rate,power consumption and EE are derived,which only depend on system configurations and large-scale fading.Based on these tight approxima-tions,we aim at optimizing the number of antennas,user selection and power allocation jointly to maximize EE with user quality-of-service constraint.The proposed scheme can achieve a higher EE with low complexity.Furthermore,it is demonstrated by simulation that the proposed scheme performs better com-pared with the conventional brute-search scheme.3)For two-hop Massive MIMO relay networks,an energy-efficient resource allocation strategy is designed.An accurate and tight asymptotic expression of EE is derived considering both uplink and downlink with the leverage of RMT tools.Moreover the trade-off between EE and sum rate is discussed.Based on the approximations,a large-scale resource allocation scheme is provided.The scheme jointly optimizes user selection and power allocation at both source users and the relay with sum rate requirement.