Energy efficiency maximization for 5G multi-antenna receivers

• Published in: Transactions on emerging telecommunications technologies Vol. 26; no. 1; pp. 3 - 14
• Main Authors: Bai, Q., Nossek, J. A.
• Format: Journal Article
• Language: English
• Published: Blackwell Publishing Ltd 01.01.2015
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.2892

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. In a digital communication system, the bit resolution employed by the analog‐to‐digital converter at the receive side critically affects the achievable data rate as well as the power consumption of the receiver. For the multi‐antenna scenario, the bit resolution of each converter associated with the multiple antennas can be jointly optimized for attaining the maximal energy efficiency of the system. Several near‐optimal algorithms are proposed to tackle the combinatorial problem with reasonable complexity.