Secure Power Control for Downlink Cell-Free Massive MIMO With Passive Eavesdroppers

This work studies secure communications for a cell-free massive multiple-input multiple-output (CF-mMIMO) network which is attacked by multiple passive eavesdroppers overhearing communications between access points (APs) and users in the network. It will be revealed that the distributed APs in CF-mMIMO allows not only legitimate users but also eavesdroppers to reap the diversity gain, which seriously degrades secrecy performance. Motivated by this, this work proposes an artificial noise (AN)-aided secure power control scheme for CF-mMIMO under passive eavesdropping aiming to achieve a higher secrecy rate and/or guarantee security. In particular, it will be demonstrated that a careful use of AN signal in the power control is especially important to improve the secrecy performance. The performance of the proposed power control scheme is evaluated and compared with various power control schemes via numerical experiments, which clearly shows that the proposed power control scheme outperforms all the competing schemes.

Joint Design of Power Control and Access Point Scheduling for Uplink Cell-Free Massive MIMO Networks

This work proposes a joint power control and access points (APs) scheduling algorithm for uplink cell-free massive multiple-input multiple-output (CF-mMIMO) networks without channel hardening assumption. Extensive studies have done on the joint optimization problem assuming the channel hardening. However, it has been reported that the channel hardening may not be validated in some CF-mMIMO environments. In particular, the existing Use-and-then-Forget (UatF) bound based on the channel hardening often seriously underestimates user rates in CF-mMIMO. Therefore, a new performance evaluation technique without resorting to the channel hardening is indispensable for accurate performance estimations. Motivated by this, we propose a new bound on the achievable rate of uplink CF-mMIMO. It is demonstrated that the proposed bound provides a more accurate performance estimate of CF-mMIMO than that of the existing UatF bound. The proposed bound also enables us to develop a joint power control and APs scheduling algorithm targeting at both improving fairness and reducing the resource between APs and a central processing unit (CPU). We conduct extensive performance evaluations and comparisons for systems designed with the proposed and existing algorithms. The comparisons show that a considerable performance improvement is achievable with the proposed algorithm even at reduced resource between APs and CPU.