Downlink Spectral Efficiency Analysis in Distributed Massive MIMO with Phase Noise

Abstract

To achieve the advantages provided by massive multiple-input multiple-output (MIMO), a large number of antennas need to be deployed at the base station. However, for the reason of cost, inexpensive hardwares are employed in the realistic scenario, which makes the system distorted by hardware impairments. Hence, in this paper, we analyze the downlink spectral efficiency in distributed massive MIMO with phase noise and amplified thermal noise. We provide an effective channel model considering large-scale fading, small-scale fast fading and phase noise. Based on the model, the estimated channel state information (CSI) is obtained during the pilot phase. Under the imperfect CSI, the closed-form expressions of downlink achievable rates with maximum ratio transmission (MRT) and zero-forcing (ZF) precoders in distributed massive MIMO are derived. Furthermore, we also give the user ultimate achievable rates when the number of antennas tends to infinity with both precoders. Based on these expressions, we analyze the impacts of phase noise on the spectral efficiency. It can be concluded that the same limit rate is achieved with both precoders when phase noise is present, and phase noise limits the spectral efficiency. Numerical results show that ZF outdoes MRT precoder in spectral efficiency and ZF precoder is more affected by phase noise.

Spectral Efficiency Augmentation in Uplink Massive MIMO Systems by Increasing Transmit Power and Uniform Linear Array Gain

“…Figure 9 shows that there is a slight difference in NLoS and LoS as channel fading puts lesser influence on mutual-information among the signals transmitted and received from extra antennas deployed at BS (N has larger value) [ 43 ]. The existing literature [ 41 , 44 , 45 , 46 ], on multi-antenna BSs focused on combating channel fading reception focused on combating channel fading, however, our proposal has been attributed with extra DoF and spatial-diversity that spot sovereign fading-realizations.…”

“…Yet again, it is because of MR combining, that gathers extra signal energy (from an array), deprived of amassing energy of interference signal. Figure 8 illustrate the results of LoS scenario at −10 dBs and −40 dBs, in which SE is an increasing function of N. Figure 9 shows that there is a slight difference in NLoS and LoS as channel fading puts lesser influence on mutual-information among the signals transmitted and received from extra antennas deployed at BS (N has larger value) [43]. The existing literature [41,[44][45][46], on multi-antenna BSs focused on combating channel fading reception focused on combating channel fading, however, our proposal has been attributed with extra DoF and spatial-diversity that spot sovereign fading-realizations.…”

Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers

“…In the D-MIMO system, multiple RAUs are distributed widely in the coverage area and connected to the baseband processing unit (BPU) via backhauls. They cooperate to serve users by transmitting and receiving signals processed collaboratively at the central BPU, for which it can achieve higher spatial diversity/multiplexing gain [7][8][9][10].…”

Massive MIMO Systems: Present and Future

“…Implementation [2,3] and trials [4,5] are actively proceeded. Especially, massive array beamforming has a good match to millimeter wave communication [6] which suffers from link budget shortfall due to its high frequency. Further, thanks to its excessive degree of freedom (DoF), massive MIMO has unlimited potentiality to further enhance system capabilities [7] and still expands various research topics with depth.…”