Energy Efficiency of Multiple-Input, Multiple-Output Architectures: Future 60-GHz Applications

Large antenna systems at millimeter-wave (mmwave) can concentrate the transmit power and the receive region over narrow beams, as well as enable spatial multiplexing. Thanks to these benefits, large antenna systems at mm-wave are the core technologies for future wireless local area network (WLAN) and 5G/ beyond 5G (B5G) cellular standards. Energy efficiency is a crucial design objective for new technologies to reduce operating costs, minimize the environmental impact, and enable battery-powered applications. Power consumption and system performance depend on the design of the beamforming architecture. The objective of this article is to compare the energy efficiency of three different architectures using power consumption measurements of a 60-GHz CMOS transceiver. We compare a full digital architecture, in which each digital chain is connected to a single antenna, against hybrid partially connected (HPC) and hybrid fully connected (HFC) architectures, using fewer digital chains than antennas. The system throughput performance is evaluated considering the hardware nonidealities, including power amplifier saturation, quantization, and phase noise (PN). We show that the number of users spatially multiplexed impacts the hybrid beamforming tradeoff. When few users are multiplexed, the main drain of energy is the digital front end, as it needs to execute operations such as filtering and fast Fourier transform (FFT) on a wide modulation bandwidth of 1.76 GHz. In this case, reducing digital redundancy using a hybrid architecture is beneficial, and a HPC architecture is the most attractive. Scaling the system to a massive multiple-input, multiple-output (mMIMO) scenario instead allows full digital architectures to achieve the highest energy efficiency.

[1]  André Bourdoux,et al.  13.5 A 4-antenna-path beamforming transceiver for 60GHz multi-Gb/s communication in 28nm CMOS , 2016, 2016 IEEE International Solid-State Circuits Conference (ISSCC).

[2]  Andreas F. Molisch,et al.  Hybrid Beamforming for Massive MIMO: A Survey , 2017, IEEE Communications Magazine.

[3]  André Bourdoux,et al.  Multi-User Hybrid MIMO at 60 GHz Using 16-Antenna Transmitters , 2019, IEEE Transactions on Circuits and Systems I: Regular Papers.

[4]  Koichiro Tanaka,et al.  A Fully Integrated 60-GHz CMOS Transceiver Chipset Based on WiGig/IEEE 802.11ad With Built-In Self Calibration for Mobile Usage , 2013, IEEE Journal of Solid-State Circuits.

[5]  Piet Wambacq,et al.  mmWave Semiconductor Industry Technologies : Status and Evolution , 2016 .

[6]  Erik G. Larsson,et al.  Efficient DSP and Circuit Architectures for Massive MIMO: State of the Art and Future Directions , 2018, IEEE Transactions on Signal Processing.

[7]  IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond M Series Mobile , radiodetermination , amateur and related satellite services , 2015 .

[8]  Ingrid Moerman,et al.  A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives , 2018, IEEE Communications Surveys & Tutorials.

[9]  Jan Craninckx,et al.  3.1 A 3.2GS/s 10 ENOB 61mW Ringamp ADC in 16nm with Background Monitoring of Distortion , 2019, 2019 IEEE International Solid- State Circuits Conference - (ISSCC).

[10]  Sridhar Ramesh,et al.  Performance, Power, and Area Design Trade-Offs in Millimeter-Wave Transmitter Beamforming Architectures , 2018, IEEE Circuits and Systems Magazine.

[11]  Robert W. Heath,et al.  Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems , 2014, IEEE Journal of Selected Topics in Signal Processing.

[12]  Claude Desset,et al.  Modeling the hardware power consumption of large scale antenna systems , 2014, 2014 IEEE Online Conference on Green Communications (OnlineGreenComm).