Graduate School and Research Center in Digital Sciences

Addressing the curse of mobility in massive MIMO with Prony-based angular-delay domain channel predictions

Yin, Haifan; Wang, Haiquan; Liu, Yingzhuang; Gesbert, David

Submitted to IEEE Journal on Selected Areas in Communications, 24 December 2019

Massive MIMO is widely touted as an enabling technology for 5th generation (5G) mobile communications and beyond. On paper, the large excess of base station (BS) antennas promises unprecedented spectral efficiency gains. Unfortunately, during the initial phase of industrial testing, a practical challenge arose which threatens to undermine the actual deployment of massive MIMO: user mobility-induced channel Doppler. In fact, testing teams reported that in moderate-mobility scenarios, e.g., 30 km/h of user equipment (UE) speed, the performance drops up to 50% compared to the low-mobility scenario, a problem rooted in the acute sensitivity of massive MIMO to this channel Doppler, and not foreseen by many theoretical papers on the subject. In order to deal with this “curse of mobility”, we propose a novel form of channel prediction method, named Prony-based angulardelay domain (PAD) prediction, which is built on exploiting the specific angle-delay-Doppler structure of the multipath. In particular, our method relies on the very high angular-delay resolution which arises in the context of 5G. Our theoretical analysis shows that when the number of base station antennas and the bandwidth are large, the prediction error of our PAD algorithm converges to zero for any UE velocity level, provided that only two accurate enough previous channel samples are available. Moreover, when the channel samples are inaccurate, we propose to combine the PAD algorithm with a denoising method for channel estimation phase based on the subspace structure and the long-term statistics of the channel observations. Simulation results show that under a realistic channel model of 3GPP in rich scattering environment, our proposed method is able to overcome this challenge and even approaches the performance of stationary scenarios where the channels do not vary at all.

Arxiv Bibtex

Title:Addressing the curse of mobility in massive MIMO with Prony-based angular-delay domain channel predictions
Keywords:mobility, massive MIMO, 5G, channel aging, channel prediction, angular-delay domain, Prony’s method
Type:Journal
Language:English
City:
Date:
Department:Communication systems
Eurecom ref:6144
Copyright: © 2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Bibtex: @article{EURECOM+6144, year = {2019}, month = {12}, title = {{A}ddressing the curse of mobility in massive {MIMO} with {P}rony-based angular-delay domain channel predictions}, author = {{Y}in, {H}aifan and {W}ang, {H}aiquan and {L}iu, {Y}ingzhuang and {G}esbert, {D}avid}, journal = {{S}ubmitted to {IEEE} {J}ournal on {S}elected {A}reas in {C}ommunications, 24 {D}ecember 2019}, url = {http://www.eurecom.fr/publication/6144} }
See also: