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Table 6 SWIPT technology in cell-free massive MIMO

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

Ref. Focus and coverage Key findings Limitations Year
[68] The work seeks to leverage the underlying practical potentials presented by UL training-based CF-mMIMO with imperfect CSI on the performance of SWIPT. Also, the work explores the attainable harvested energy and UL/DL rates in closed form. ▪ The performance of the SWIPT technique is substantially improved by adopting the CF massive MIMO model.
▪ Exploiting the benefits of distributed transmission/reception and many spatially distributed single antenna APs, an optimal achievable energy-rate trade-off of SWIPT is realized.
▪ Concerning the number of energy users (fixed in this case), the achievable sum rate is moderately increased when the number of APs becomes large.
▪ The authors did not discuss the cases of spatial randomness and channel changes when links are blocked. 2018
[69] The study investigates the coexistence of SWIPT and CF massive MIMO. The work aims at bridging the gap in CF literature by optimizing the underlying issues presented by SWIPT. Stochastic geometry is exploited to model the APs using a homogeneous PPP, resulting in a spatially random network. ▪ The proposed arrangement improves the energy-rate trade-off of SWIPT networks considerably.
▪ A careful balance in power allocated to energy users enhances the mean harvested energy significantly, however, at the cost of a reduced DL rate for non-energy users.
▪ The UL performance of energy users after the energy harvest is not accounted for.
▪ The results show an improved DL rate for energy users due to reduced pilot sequence resulting in fewer users being served.
2020