Optimal Energy Efficiency in Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach

The increasing demand for green wireless communications and the benefits of the promising cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems towards their optimal energy efficiency (EE) are the focal points of this work. Specifically, despite previous works assuming a uniform placement for the access points (APs), we consider that their locations follow a Poisson point process (PPP) which approaches their opportunistic spatial randomness. Based on stochastic geometry, we derive a lower bound on the average spectral efficiency, and under a realistic power consumption model for CF mMIMO systems, we formulate an EE maximization problem achieving to obtain in closed form the optimal EE per unit area in terms of the pilot reuse factor and the AP density. Note that we have defined the EE per unit area and not just the EE to characterize the energy in systems with multi-point transmission. Thus, we provide important design insights for energy-efficient CF mMIMO systems.

[1]  Symeon Chatzinotas,et al.  Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach , 2020, IEEE Transactions on Vehicular Technology.

[2]  Alessio Zappone,et al.  Energy-Efficient Power Control in Cell-Free and User-Centric Massive MIMO at Millimeter Wave , 2019, IEEE Transactions on Green Communications and Networking.

[3]  Antti Toskala,et al.  LTE for UMTS: Evolution to LTE-Advanced , 2011 .

[4]  Tharmalingam Ratnarajah,et al.  Deterministic Equivalent Performance Analysis of Time-Varying Massive MIMO Systems , 2015, IEEE Transactions on Wireless Communications.

[5]  Shlomo Shamai,et al.  Enhancing the cellular downlink capacity via co-processing at the transmitting end , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[6]  Emil Björnson,et al.  Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO , 2015, IEEE Journal on Selected Areas in Communications.

[7]  Mérouane Debbah,et al.  Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need? , 2013, IEEE Journal on Selected Areas in Communications.

[8]  Emil Björnson,et al.  Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer? , 2014, IEEE Transactions on Wireless Communications.

[9]  Emil Björnson,et al.  Network Deployment for Maximal Energy Efficiency in Uplink With Multislope Path Loss , 2017, IEEE Transactions on Green Communications and Networking.

[10]  Bernard Fino,et al.  Multiuser detection: , 1999, Ann. des Télécommunications.

[11]  Hien Quoc Ngo,et al.  Energy Efficiency in Cell-Free Massive MIMO with Zero-Forcing Precoding Design , 2017, IEEE Communications Letters.

[12]  M. Haenggi,et al.  Interference in Large Wireless Networks , 2009, Found. Trends Netw..

[13]  Thomas L. Marzetta,et al.  Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas , 2010, IEEE Transactions on Wireless Communications.

[14]  Muriel Médard,et al.  The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel , 2000, IEEE Trans. Inf. Theory.

[15]  Symeon Chatzinotas,et al.  Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems , 2020, ArXiv.

[16]  Erik G. Larsson,et al.  On the Total Energy Efficiency of Cell-Free Massive MIMO , 2017, IEEE Transactions on Green Communications and Networking.

[17]  Erik G. Larsson,et al.  Cell-Free Massive MIMO Versus Small Cells , 2016, IEEE Transactions on Wireless Communications.

[18]  T. Mattfeldt Stochastic Geometry and Its Applications , 1996 .

[19]  Emil Björnson,et al.  Channel Hardening and Favorable Propagation in Cell-Free Massive MIMO With Stochastic Geometry , 2017, IEEE Transactions on Communications.

[20]  Emil Björnson,et al.  Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency , 2018, Found. Trends Signal Process..