When Are Low Resolution ADCs Energy Efficient in Massive MIMO?

被引:30
作者
Sarajlic, Muris [1 ]
Liu, Liang [1 ]
Edfors, Ove [1 ]
机构
[1] Lund Univ, Dept Elect & Informat Technol, S-22363 Lund, Sweden
关键词
5G mobile communication; MIMO; energy efficiency; digital signal processing; circuits; analog-digital conversion; CHANNEL ESTIMATION; SYSTEMS;
D O I
10.1109/ACCESS.2017.2731420
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Massive MIMO (MaMI) is often promoted as a technology that will enable the use of low-quality, cheap hardware. One particular component that has been in the focus of MaMI-related research is the analog-to-digital converter (ADC), and use of very low-resolution ADCs has been proposed. However, studies about whether this strategy is justified from an energy-efficiency point of view have largely been inconclusive. In this paper, we choose system setup and models that re pect the hardware implementation reality as close as possible and perform a parametric analysis of uplink energy-efficiency as a function of ADC resolution. If antenna scaling and decrease of ADC resolution are considered independently, the energy efficiency is shown to be maximized at intermediate ADC resolutions, typically in the range of 4-8 bits. Moreover, optimal ADC resolution does not decrease when more antennas are used except in some specific cases, and when it does, the decrease is approximately logarithmic in the number of antennas. In the case when antenna scaling and ADC degradation are coupled through a constant-performance constraint, it is shown that energy efficiency cannot improve with reduced bit resolution unless the power consumption of blocks other than ADCs scales down with the upscaling of antennas at a fast enough rate. Altogether it is concluded that in MaMI, intermediate ADC resolutions are optimal in energy efficiency sense, and, except in some special cases, scaling up the antennas to very large numbers does not change this conclusion.
引用
收藏
页码:14837 / 14853
页数:17
相关论文
共 29 条
[1]  
[Anonymous], 2004, RANDOM MATRIX THEORY
[2]  
[Anonymous], 2014, MASSIVE MIMO 1 BIT A
[3]   Energy efficiency maximization for 5G multi-antenna receivers [J].
Bai, Q. ;
Nossek, J. A. .
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2015, 26 (01) :3-14
[4]   Training-based MIMO channel estimation: A study of estimator tradeoffs and optimal training signals [J].
Biguesh, M ;
Gershman, AB .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (03) :884-893
[5]   Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design [J].
Bjoernson, Emil ;
Matthaiou, Michail ;
Debbah, Merouane .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2015, 14 (08) :4353-4368
[6]   Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits [J].
Bjornson, Emil ;
Hoydis, Jakob ;
Kountouris, Marios ;
Debbah, Merouane .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2014, 60 (11) :7112-7139
[7]  
Dai Zhang, 2011, 2011 European Conference on Circuit Theory and Design (ECCTD 2011), P556, DOI 10.1109/ECCTD.2011.6043594
[8]  
Desset C., 2014, P IEEE ONL C GREEN C, P1
[9]   Uplink Achievable Rate for Massive MIMO Systems With Low-Resolution ADC [J].
Fan, Li ;
Jin, Shi ;
Wen, Chao-Kai ;
Zhang, Haixia .
IEEE COMMUNICATIONS LETTERS, 2015, 19 (12) :2186-2189
[10]  
Gersho A., 2012, Vector Quantization and Signal Compression, V159