Partial Cooperative Zero-Forcing Decoding for Uplink Cell-Free Massive MIMO

We propose a partial cooperative zero-forcing (PCZF) decoding scheme for the uplink cell-free massive MIMO system, wherein the neighboring access points (APs) around each user equipment (UE) share the channel state information (CSI) and jointly suppress the interference using the zero-forcing technique. Using asymptotic analysis, we derive a closed-form asymptotic expression for a lower bound on the achievable rates. Considering the unique and complex form of the achievable rates, we propose power control schemes according to two criteria. The first criterion is to maximize the minimum achievable rate. For this criterion, we propose a target-SINR-tracking (TST)-based bisection algorithm. Since the power control update functions are standard interference functions, the TST-based bisection method always converges to the optimal solution. The second criterion is to maximize the sum rate, for which we propose two power control algorithms: 1) randomization and scaling algorithm (RSA) and 2) fractional programming algorithm (FPA). In each iteration of the RAS algorithm, we first exploit the randomization technique to transform the sum-rate maximization problem into a series of power minimization problems, and then improve the sum rate by scaling. In the FP algorithm, we derive a lower bound on the sum rate, and then propose an iterative approach based on the Lagrangian dual transform and fractional programming to maximize the sum-rate lower bound. Numerical results validate the theoretical analysis and verify the efficiency of the proposed power control algorithms.

Automated summary

In this paper, a partial cooperative zero-forcing (PCZF) decoding scheme is proposed for the uplink cell-free massive MIMO system. Power control algorithms are introduced based on two criteria: maximizing the minimum achievable rate and maximizing the sum rate.