Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?

By Emil Björnson, Luca Sanguinetti, Jakob Hoydis, Merouane Debbah. IEEE Transactions on Wireless Communications, 2014

815 citations recorded by the source corpus.

Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4afa918506a45be77b0682156c3dfdc956272fa3

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Citations in the corpus

A Comprehensive Survey of Pilot Contamination in Massive MIMO—5G System (2016, methodology): “6 using the equations (55) and (20) from [26] for area throughput and energy efficiency (EE), respectively.”
An Overview of Sustainable Green 5G Networks (2016, methodology): “In light of this, a realistic power consumpti on model is established in [13], where it was shown that deploying 100-200 antennas to serve a relatively large number of terminals is the EE-optimal solution for today’s circuit technology.”
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead (2016, background): “In [47] and [83] the hardware power is included in the analysis, and it is shown that the network energy efﬁciency is maximized for a ﬁnite number of deployed antennas.”
Energy-Efficient Design of MIMO Heterogeneous Networks With Wireless Backhaul (2015, methodology): “Under the previous assumption, and by using the model in [49], we can write the power consumption on each macro cell link as follows Pm = τmPmt + (1− τm)KmPut + τmKm (Pme + Pud)R DL m + Pmc + (1− τm)Km (Pmd + Pue)R UL m (5) wherePmt andPut are the DL and UL transmit power from the MBS and theKm UEs,”
Prospective Multiple Antenna Technologies for Beyond 5G (2019, background): “There have been serval attempts to maximize the energy efﬁciency of MIMO systems by both optimizing the power allocation [140]–[142] and the network topology [143]–[145].”
On the Total Energy Efficiency of Cell-Free Massive MIMO (2017, background): “The total power consumption is modeled as [12], [18]–[20]”
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication (2018, background): “16: end if 17: end while 18: Output: Φ ( (cid:96) +1) and P ( (cid:96) +1) . according to the 3GPP propagation environment described in [63], whose parameters are summarized in Table I.”
Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays (2019, background): “are the spectral efficiency analysis [18]–[21], system design for high energy efficiency [22]–[24], pilot contamination and decontamination [25]–[29], and power optimization [30]–[32].”
Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks (2016, background): “Therefore, we can no longer expect EE enhancement for M-MIMO systems unless the efﬁciency of the auxiliary circuits can be improved [119].”