designing multi-user mimo for energy efficiency
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Designing Multi-User MIMO for Energy Efficiency
Emil Björnson‡*
Joint work with: Luca Sanguinetti‡§, Jakob Hoydis†, and Mérouane Debbah‡
‡Alcatel-Lucent Chair on Flexible Radio, Supélec, France*Dept. Signal Processing, KTH Royal Institute of Technology, Sweden
§Dip. Ingegneria dell’Informazione, University of Pisa, Pisa, Italy†Bell Laboratories, Alcatel-Lucent, Stuttgart, Germany
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 1
When is Massive MIMO the Answer?
Outline
• Presentation is based onE. Björnson, L. Sanguinetti, J. Hoydis, M. Debbah, “Designing Multi-User MIMO for Energy Efficiency: When is Massive MIMO the Answer?,” Submitted IEEE WCNC 2014 Preprint available on arXiv: http://arxiv.org/abs/1310.3843.
• Main Question- How should a single-cell downlink system be designed to
maximize energy efficiency?- Optimization variables: Number of base station
antennasNumber of active user
equipmentsData rate guaranteed per user
• Conclusions- Result depends strongly on physical layer precoding scheme- Unconventionally many users and antennas can be optimal!2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 2
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 3
Introduction
What are the Expectations?
• Tons of Plenary Talks and Overview Articles- Fulfilling dream of ubiquitous wireless connectivity
• Expectation: Many Metrics Should Be Improved in 5G- Higher user data rates - Higher area throughput- Great scalability in number of connected devices- Higher reliability and lower latency- Better coverage with more uniform user rates- Improved energy efficiency
• These are Conflicting Metrics!- Impossible to maximize all metrics simultaneously- Our goal: High energy efficiency (EE) with uniform user rates
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 4
Multi-User MIMO System
• Multi-User Multiple-Input Multiple-Output (MIMO)- One base station (BS) with array of antennas- single-antenna user equipments (UEs)- Downlink: Transmission from BS to UEs- Share a flat-fading carrier
• Multi-Antenna Precoding- Spatially directed signals- Signal improved by array gain- Adaptive control of interference- Serve multiple users in parallel
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 5
Space-division multiple access(SDMA)
Multi-User MIMO System (2)
• Cell: Area with user location and pathloss distribution• Scheduling: Pick users randomly, with random location
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 6
Clean-Slate Design
Select and to maximize EE!
Some UEDistribution
How to Measure Energy Efficiency?
• Energy Efficiency in bits/Joule
• Conventional Academic Approaches- Maximize throughput with fixed power- Minimize transmit power for fixed throughput
• New Problem: Balance throughput and power consumption- Crucial: Account for overhead signaling- Crucial: Use reasonable power consumption model
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 7
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 8
System Model:Average Sum Throughput
Time-Division Duplex (TDD) Protocol
• Coherence Period: [channel uses]
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 9
Assumption:Perfect estimation
Average Sum Throughput
• System Model- Precoding vector of User : - Channel vector of User :
• Random User Selection, - Channel variances Independent random variables,
• Achievable Rate of User :
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 10
Cost of estimation
Average over channels and user selectionSignal-to-interference+noise ratio
(SINR)
𝐡1❑ 𝐡2
❑
Impact of Precoding
• What Determines User Rates?- Precoding (vector directions and power allocations)- “Optimal” precoding: Extensive computations – Not efficient
• Notation- Matrix form: , - Total radiated power: )
• Heuristic Closed-Form Precoding- Maximum ratio transmission (MRT): - Zero-forcing (ZF) precoding: - Regularized ZF (RZF) precoding:
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 11
Maximizesignal
Minimizeinterference
Balance signal and interference
Uniform User Performance
• Assumption: Uniform user performance- Same rate at every user: - Scaling parameter can be optimized
• Consequence:- We use ZF in analysis and other precoding for simulation
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 12
Lemma 1
Consider ZF precoding and the user rates above, the average radiated power is
where depends on UE distribution, propagation, etc.
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 13
System Model:Power Consumption
Reasonable Power Consumption Model
• What Consumes Power?- Examples will motivate our model
• Transmit Power: - = Average radiated transmit power- = Efficiency of power amplifier at BS
• Transceiver Chains: - = Circuit power / BS antenna (converters, mixers, filters)- = Power of common oscillator at BS- = Circuit power / UE (oscillator, converters, mixer, filters)
• Coding and Decoding: - = Power for coding at BS / user- = Power for decoding at each user
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 14
Reasonable Power Consumption Model (2)
• Computational Efficiency: operations per Joule
• Uplink Channel Estimation: - Only once per coherence period- channel components per user, processed separately
• Precoding: - Only once per coherence period- Depends on precoding:
• Architectural Costs: - Control signaling, backhaul infrastructure,
load-independent processing, etc.
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 15
Reasonable Power Consumption Model (3)
• Summary- General model of power consumption: for some parameters and
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 16
Energy Efficiency for ZF
User rate: Radiated power:
Design parameters: , , and
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 17
Optimize System Parametersfor Energy Efficiency
Preliminaries
• Our Goal:- Optimize number of antennas - Optimize the (normalized) transmit power - Optimize number of active UEs
• Definition- Lambert function, , solves equation - The function is increasing and satisfies - behaves almost as linear:
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 18
Optimal Number of BS Antennas
• Find that maximizes EE with ZF precoding:
• Observations- Increases sublinearly with power but linearly at high - Increases with circuit power coefficients independent of - Decreases with circuit power coefficients multiplied with
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 19
Theorem 1 (Optimal )
Optimal Transmit Power
• Find that maximizes EE with ZF precoding:𝜌
• Observations- Increases power with number of antennas as - Opposite to recent claim: Power should decrease as - Intuition: Higher circuit power Use more transmit power
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 20
Theorem 2 (Optimal 𝜌)
Optimal Number of Active UEs
• Find that maximizes EE with ZF precoding:
where and are fixed.
• Observations- Decreases with circuit power coefficients multiplied with or - Increases with the static hardware power - Increases with the propagation parameter
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 21
Theorem 3 (Optimal )
Solution is a root to a quartic polynomial:Closed-form but very large expressions
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 22
Numerical Illustrations
Simulation Scenario
• Main Characteristics- Circular cell with radius 250 m- Uniform user distribution with 35 m minimum distance- Uncorrelated Rayleigh fading, typical 3GPP pathloss model
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 23
Optimal System Design: ZF Precoding
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 24
Optimum
User rates:as 256-QAM
Massive MIMO!
Very many antennas,
Optimal System Design: MRT
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 25
Optimum
User rates:as 64-QAM
Single-user transmission!
Only exploitprecoding gain
Why This Huge Difference?
• Interference is the Limiting Factor- ZF: Suppress interference actively- MRT: Only indirect suppression by making
• More results: RZFZF, same trends under imperfect CSI
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 26
Only 2xdifference
in EE
100xdifference
in throughput
Energy Efficient to Use More Power?
• Recall Theorem 2: Transmit power increases with - Figure shows EE-maximizing power for different
• Intuition: More Circuit Power Use More Transmit Power2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 27
Essentiallylinear
growth
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 28
Conclusions
Conclusions
• What if a Single-Cell System Designed for High EE?- Need: Reasonable throughput model- Need: Reasonable power consumption model
• Contributions- General power consumption model- Closed-form results for ZF: Optimal number of antennas
Optimal number of active UEsOptimal transmit power
- Observations: More circuit power Use more transmit power
• Numerical Example- ZF/RZF precoding: Massive MIMO system is optimal- MRT precoding: Single-user transmission is optimal- Small difference in EE, but huge difference in throughput!
2013-11-07 Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH) 29
2013-11-07 30Greentouch Open Forum, Designing Multi-User MIMO for Energy Efficiency, E. Björnson (Supélec & KTH)
Thank You for Listening!
Questions?
Main reference:E. Björnson, L. Sanguinetti, J. Hoydis, M. Debbah, “Designing Multi-User MIMO for Energy Efficiency:
When is Massive MIMO the Answer?”
Submitted IEEE WCNC 2014Preprint available on arXiv: http://arxiv.org/abs/1310.3843
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