Energy efficiency maximization for 5G multi‐antenna receivers

In a digital communication system, the analog signal that the receiver receives with its radio frequency front end is converted into digital format by using the analog-to-digital converter A/D converter, ADC. Quantisation takes place during the conversion from continuous amplitude signal to discrete amplitude signal, leading inevitably to losses in information which are dependent on the number of bits that is used to represent each sample. Although employing a higher bit resolution reduces the quantisation error, a higher power dissipation of the ADC is incurred at the same time. This trade-off is essential to the energy efficiency of the receiver, which is commonly measured by the number of information bits conveyed per consumed Joule of energy. We investigate, in this work, the adaptation of ADC resolutions of a multi-antenna receiver based on instantaneous channel knowledge, with the goal of maximising receiver energy efficiency. The formulated optimisation is a combinatorial problem, and we propose several algorithms which yield near-optimal solutions. Results from numerical simulations are presented and analysed, which provide guidelines to operation and deployment of the system. Copyright © 2014 John Wiley & Sons, Ltd.

[1]  Qing Bai,et al.  On the Optimization of ADC Resolution in Multi-antenna Systems , 2013, ISWCS.

[2]  Jeffrey G. Andrews,et al.  Femtocells: Past, Present, and Future , 2012, IEEE Journal on Selected Areas in Communications.

[3]  Qing Bai,et al.  Improving Energy-efficiency of Multi-antenna Receivers via Adaptation of ADC Resolutions , 2014 .

[4]  Geoffrey Ye Li,et al.  Fundamental trade-offs on green wireless networks , 2011, IEEE Communications Magazine.

[5]  Joonhyuk Kang,et al.  Energy efficiency analysis with circuit power consumption in massive MIMO systems , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[6]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[7]  Mohammad Gharavi-Alkhansari,et al.  Fast antenna subset selection in MIMO systems , 2004, IEEE Transactions on Signal Processing.

[8]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[9]  Julian J. Bussgang,et al.  Crosscorrelation functions of amplitude-distorted gaussian signals , 1952 .

[10]  Xiqi Gao,et al.  Cellular architecture and key technologies for 5G wireless communication networks , 2014, IEEE Communications Magazine.

[11]  Emil Björnson,et al.  Designing multi-user MIMO for energy efficiency: When is massive MIMO the answer? , 2013, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[12]  Josef A. Nossek,et al.  Modeling and minimization of transceiver power consumption in wireless networks , 2011, 2011 International ITG Workshop on Smart Antennas.

[13]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[14]  Brian M. Sadler,et al.  Pilot-assisted wireless transmissions: general model, design criteria, and signal processing , 2004, IEEE Signal Processing Magazine.

[15]  Aditya Dua,et al.  Receive antenna selection in MIMO systems using convex optimization , 2006, IEEE Transactions on Wireless Communications.

[16]  Chaitali Chakrabarti,et al.  A System Level Energy Model and Energy-Quality Evaluation for Integrated Transceiver Front-Ends , 2007, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[17]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[18]  Joel Max,et al.  Quantizing for minimum distortion , 1960, IRE Trans. Inf. Theory.

[19]  Lajos Hanzo,et al.  Green radio: radio techniques to enable energy-efficient wireless networks , 2011, IEEE Communications Magazine.

[20]  Moe Z. Win,et al.  Capacity of MIMO systems with antenna selection , 2001, IEEE Transactions on Wireless Communications.

[21]  Qing Bai,et al.  Minimizing the energy per bit for pilot-assisted data transmission over quantized channels , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

[22]  Erik G. Larsson,et al.  Massive MIMO for next generation wireless systems , 2013, IEEE Communications Magazine.

[23]  Robert W. Heath,et al.  Five disruptive technology directions for 5G , 2013, IEEE Communications Magazine.

[24]  Boris Murmann,et al.  A/D converter trends: Power dissipation, scaling and digitally assisted architectures , 2008, 2008 IEEE Custom Integrated Circuits Conference.

[25]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[26]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[27]  Aria Nosratinia,et al.  Antenna selection in MIMO systems , 2004, IEEE Communications Magazine.

[28]  Upamanyu Madhow,et al.  On the limits of communication with low-precision analog-to-digital conversion at the receiver , 2009, IEEE Transactions on Communications.

[29]  J. A. Wepman,et al.  Analog-to-digital converters and their applications in radio receivers , 1995, IEEE Commun. Mag..

[30]  Arogyaswami Paulraj,et al.  Receive antenna selection for MIMO spatial multiplexing: theory and algorithms , 2003, IEEE Trans. Signal Process..

[31]  J. Nossek,et al.  Capacity Lower Bound of MIMO Channels with Output Quantization and Correlated Noise , 2012 .

[32]  Michael N. Vrahatis,et al.  Particle swarm optimization for integer programming , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[33]  Harvey M. Salkin,et al.  Foundations of integer programming , 1989 .

[34]  Josef A. Nossek,et al.  Analysis of Rayleigh-fading channels with 1-bit quantized output , 2008, 2008 IEEE International Symposium on Information Theory.

[35]  Hae-Seung Lee,et al.  Analog-to-Digital Converters: Digitizing the Analog World , 2008, Proceedings of the IEEE.