Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems

Abstract

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink (DL) for optimal energy efficiency (EE). To address this fundamental topic, we assume that each access point (AP) is deployed with multiple antennas and serves multiple users on the same time-frequency resource while the APs are Poisson point process (PPP) distributed, which approaches realistically their opportunistic spatial randomness. Relied on tools from stochastic geometry, we derive a lower bound on the DL average achievable spectral efficiency (SE). Next, we consider a realistic power consumption model for CF mMIMO systems. These steps enable the formulation of a tractable optimization problem concerning the DL EE, which results in the analytical determination of the optimal pilot reuse factor, the AP density, and the number of AP antennas and users that maximize the EE. Hence, we provide useful design guidelines for CF mMIMO systems relating to fundamental system variables towards optimal EE. Among the results, we observe that an optimal pilot reuse factor and AP density exist, while larger values result in an increase of the interference, and subsequently, lower EE. Overall, it is shown that the CF mMIMO technology is a promising candidate for next-generation networks achieving simultaneously high SE and EE.

Energy Efficiency of User-Centric, Cell-Free Massive MIMO-OFDM with Instantaneous CSI

“…The power control coefficients of different RBs within the coherent bandwidth can be solved simultaneously, and the power control coefficients of RBs in different coherent bandwidths are solved independently, so that parallelization can be achieved. Therefore, Problem (18)…”

“…First-order methods are suitable for solving large-scale problems, and the literature has used first-order methods for solving energy efficiency optimization problems with conjugate beamforming precoding and zero-forcing precoding, respectively, to significantly improve the speed [ 15 , 16 , 17 ]. Papazafeiropoulos optimizes the pilot reuse factor and AP density to maximize the energy efficiency per square power [ 18 ]. An energy efficiency problem is formulated for determining the optimal energy efficiency with respect to the pilot reuse factor, the AP density, and the number of UEs and antennas per AP.…”

Downlink Resource Allocation in Multiuser Cell-free MIMO Networks with User-centric Clustering

“…where µ ru and λ ru are the Lagrange multipliers corresponding to the constraints in (19b) and (19c) respectively. We can then write the Lagrangian formulation of (19) as…”

“…Furthermore, in [18] the authors control the power to decrease pilot contamination. Also, [16], [19], [20], study energy efficiency under a cell-free distributed MIMO scheme.…”

Secure Transmission in Cell-Free Massive MIMO With RF Impairments and Low-Resolution ADCs/DACs

“…As a scalable implementation of the distributed system, cell-free massive MIMO can provide significant advantages in terms of throughput and service coverage through a larger number of geographically distributed access points (APs) [5], [6]. Recently, various contributions in existing literatures, including performance analysis, full-duplex system, relaying communication, power allocation etc, have been presented on cell-free massive MIMO systems [7], [8], [9], [10].…”