Impact of General Channel Aging Conditions on the Downlink Performance of Massive MIMO

Abstract

Abstract-Recent works have identified massive multiple-inputmultiple-output (MIMO) as a key technology for achieving substantial gains in spectral and energy efficiency. Additionally, the turn to low-cost transceivers, being prone to hardware impairments is the most effective and attractive way for costefficient applications concerning massive MIMO systems. In this context, the impact of channel aging, which severely affects the performance, is investigated herein by considering a generalized model. Specifically, we show that both Doppler shift because of the users' relative movement as well as phase noise due to noisy local oscillators (LOs) contribute to channel aging. To this end, we first propose a joint model, encompassing both effects, in order to investigate the performance of a massive MIMO system based on the inevitable time-varying nature of realistic mobile communications. Then, we derive the deterministic equivalents (DEs) for the signal-to-noise-and-interference ratios (SINRs) with maximum ratio transmission (MRT) and regularized zero-forcing precoding (RZF). Our analysis not only demonstrates a performance comparison between MRT and RZF under these conditions, but most importantly, it reveals interesting properties regarding the effects of user mobility and phase noise. In particular, the large antenna limit behavior depends profoundly on both effects, but the burden due to user mobility is much more detrimental than phase noise even for moderate user velocities (≈ 30 km/h), while the negative impact of phase noise is noteworthy at lower mobility conditions. Moreover, massive MIMO systems are favorable even in general channel aging conditions. Nevertheless, we demonstrate that the transmit power of each user to maintain a certain quality of service can be scaled down at most by 1 √ M (M is the number of BS antennas), which indicates that the joint effects of phase noise and user mobility do not degrade the power scaling law, but only the achievable sum-rate.

Nuts and Bolts of a Realistic Stochastic Geometric Analysis of mmWave HetNets: Hardware Impairments and Channel Aging

“…Interestingly, steps forward towards a more realistic approach necessitate the incorporation of RATHIs in the design. In fact, from conventional wireless systems and continuing to 5G networks such as massive MIMO systems, the inclusion of RATHIs in the analysis results in more down-to-earth conclusions [16]- [19], [23], [24], [26], [27], [43].…”

“…Unfortunately, although 5G networks, and especially, mmWave systems and HetNets should be the cynosure regarding the study of residual transceiver hardware impairments (RTHIs), the situation is different as a literature survey reveals. In the majority of literature, ideal transceiver hardware is assumed which is far form realistic, considering the inevitability of RTHIs [16]- [21], [21]- [27] 1 . In particular, the additive RTHIs (RATHIs), which describe the aggregate effect of many impairments, are modeled as additive Gaussian noises at both the BS and user's side [16], [17].…”

“…The RTHIs denote the amount of distortions, which occur by the partially mitigation of the transceiver hardware because although real-world applications employ calibration schemes at the transmitter and compensation algorithms at the receiver, the transceiver hardware impairments are only partially mitigated[16],[26],[27] …”

Performance analysis of (TDD) massive MIMO with Kalman channel prediction

“…Another paper that investigated the effects of channel aging assuming Jakes spectrum is [3], where the sum-rate for massive MIMO systems with matched filter and zeroforcing receivers in the presence of channel aging was derived. In [4], the authors showed that the Doppler shift due to relative movement of users as well as the phase noise due to noisy local oscillators contribute to channel aging. They incorporated both these effects in their channel aging analysis based on random matrix theory for massive MIMO systems.…”

Performance Scaling Law for Multicell Multiuser Massive MIMO

“…Meanwhile, the impact of other practical factors such as channel aging [13], [14], hardware limits [15], and Rician fading [16] on the performance of massive MIMO systems was studied. However, a comprehensive scaling law analysis for multi-cell multi-user massive MIMO is still missing in existing works.…”