Cell-Free Massive MIMO With Rician K-Adaptive Feedback

Abstract

Cell-free massive multiple-input multiple-output (CF-mMIMO) systems have been developed primarily in time-division duplex (TDD) systems to provide uniformly good service to all users in network area. However, frequency division duplex (FDD) systems still prevail in the communication systems to date. In FDD systems, there is always an issue of channel state information (CSI) acquisition at access points (APs) due to channel feedback overhead and this issue becomes even more prominent when the FDD systems are applied to CF-mMIMO systems. To overcome this limitation, we propose a Rician <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$K$</tex> -adaptive feedback method that significantly reduces feedback overhead by selecting paths with small Rician <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$K$</tex> -factors in multipath Rician fading channel and feeding back only the channels for the selected paths. In addition, we propose a channel-mixed angle-based zero-forcing (CM-AZF) beamforming technique that mixes angle information from angle-reciprocity and the quantized channel information from the channel feedback. The performance of our Rician <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$K$</tex> -adaptive feedback method and CM-AZF beamforming technique has been validated through simulation results and shows a higher average achievable rate for the same amount of feedback compared to the conventional leakage power-based path selection method.