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Table 8 Cell-free massive MIMO systems with hardware impairments

From: Application of cell-free massive MIMO in 5G and beyond 5G wireless networks: a survey


Focus and coverage

Key findings




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.



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.



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.



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.