|Ref.||Focus and coverage||Key findings||Limitations||Year|
|||The work considers the secure transmission issue in CF-mMIMO networks, considering the effects of HI and the presence of spoofing attacks. The work is analyzed using hardware quality scaling law, continuous approximation, convex approximation, and path-following algorithms.||▪ The proposed power control scheme outperforms the conventional average power allocation.||▪ The performance of the system is significantly impacted by the active attacks and the decrease of hardware qualities.||2019|
|||The effect of HI on the UL transmission of a CF massive MIMO system constrained by limited capacity fronthaul links is investigated. Low-complexity fronthaul rate allocations are proposed to minimize transmission of the compressed version of CSI and data signals.||▪ The system’s sum spectral/energy efficiency is significantly improved with the estimate-multiply-compress-forward compared to the other two strategies applied.||
▪ Large portions of the fronthaul capacity for signal transmission impact the achievable rate considerably.|
▪ The performance gain is affected mainly by the processing power of the AP.
|||The authors examined the impact of RF impairments and ADCs imperfections on the performance of UL CF-mMIMO. The work aims at improving the accuracy of channel estimation while ensuring a maximized signal-to-interference-plus-noise ratio.||▪ The hardware expenses can be minimized by reducing the quality of transceiver RF chains and the quantization bits of low-resolution ADCs.||▪ The benefits come at the cost of significant performance degradation.||2020|
|||The performance of distributed massive MIMO (CF and UC systems) and SC systems under practical deployment scenarios is investigated. More precisely, the impact of non-ideal hardware distortions and the Doppler shift effect is considered.||
▪ The study results revealed that distributed massive MIMO is more robust to hardware distortion and the Doppler shift effect compared to SC systems.|
▪ Moreover, SC systems perform poorly under max-min power control.
▪ Distributed massive MIMO suffers significant performance loss when the number of served users per AP is reduced.|
▪ Additionally, the network is preferable for majorly high-mobility conditions.
|||The authors quantitatively examined the effect of HI on the performance of CF-mMIMO. Four low-complexity receiver cooperation is adopted, and a comprehensive review of the fronthaul requirements of the different receiver cooperation is provided.||
▪ Results obtained show that the SE is significantly improved as the hardware qualities increases.|
▪ More so, the reducing hardware quality diminishes with increasing APs.
|▪ The negative effect of HI at UE is not elaborated.||2020|
|||This survey focuses on maximizing the hardware quality in CF massive MIMO. Specifically, the authors examined the optimal HI and ADC bit allocation problem based on the large-scale fading variations of the channel for maximal SE and EE. Regularized zero-forcing (RZF) combined with statistical channel inversion power control is employed in the system.||▪ Compared to equal ADC bit allocation, the EE and sum SE is moderately increased by the optimal ADC bit allocation.||▪ Hardware quality is not fully optimized.||2021|