Energy efficiency maximization for 5G multi‐antenna receivers

Abstract

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.

On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems

“…The widely used additive quantization noise model (AQNM) can characterize the quantization noise [2], [5], [6]. Under the assumption of Gaussian distributed signaling alphabets, a AQNM based lower capacity bound can be derived to provide valuable insights into the performance of quantized mmWave massive MIMO systems.…”

Performance analysis of uplink massive MIMO systems with variable‐resolution ADCs using MMSE and MRC detection

“…Although the achievable rate is the lowest for b up = 1 under perfect CSI, the power consumption is also the lowest. In this regard, it is possible to achieve the best EE according to (40).…”

“…A bit allocation approach was designed on the condition that each ADC can take only one of two quantization resolutions . Bai and Nossek proposed to treat the ADC resolution as an adaptable parameter and attempted to maximize the EE of the system, with which they investigated the adaptation of ADC resolutions of a multiantenna receiver based on instantaneous channel knowledge.…”

BER performance analysis of coarsely quantized uplink massive MIMO

“…For such assumptions, the linear matrix B can also be simplified as Table I shows the values of ρ and α for b-bit quantization resolution (b ≤ 5). For higher bit-resolution of b > 5, an approximate of ρ = π √ 3 2 2 −2b can be applied [29]. Substituting (7) into (3), we have…”