Abstract

As an effective technology for boosting the performance of wireless communications, massive multiple-input multiple-output (MIMO) systems based on symmetric antenna arrays have been extensively studied. Using low-resolution analog-to-digital converters (ADCs) at the receiver can greatly reduce hardware costs and circuit complexity to further improve the energy efficiency (EE) of the system. There are significant research on the design of MIMO detectors but there is limited study on their performance in terms of EE. This paper studies the effect of signal detection on the EE in practical systems, and proposes to apply several signal detectors based on lattice reduction successive interference cancellation (LR-SIC) to massive MIMO systems with low-precision ADCs. We report results on their achievable EE in fading environments with typical modeling of the path loss and detailed analysis of the power consumption of the transceiver circuits. It is shown that the EE-optimal solution depends highly on the application scenarios, e.g., the number of antennas employed, the cell size, and the signal processing efficiency. Consequently, the signal detector must be properly selected according to the application scenario to maximize the system EE. In addition, medium-resolution ADCs should be selected to balance their own power consumption and the associated nonlinear distortion to maximize the EE of system.

Highlights

  • Massive multiple-input multiple-output (MIMO) systems employing symmetric antenna arrays can be used to improve the spectrum efficiency (SE) of wireless communications [1,2,3,4]

  • MIMO systems with low-resolution analog-to-digital converters (ADCs); We analyze the transmission power required for achieving a target bit error rate (BER), the power required for signal detection, and the power consumption due to the ADCs given the system configuration; We analyze and compare the EE for several different MIMO detectors under a universal system-level power consumption model, and discuss the influence of the number of antennas, the ADC resolution and the signal processing algorithms on the performance

  • It is seen that in such a scenario the linear minimum mean squared error (MMSE) detector can be advantageous. This is because the transmission power required for achieving BER0 = 10−2 becomes similar for different detectors but nonlinear detectors exhibit higher signal processing complexity, which translates into higher receiver power consumption and lower EE

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Summary

Introduction

Massive multiple-input multiple-output (MIMO) systems employing symmetric antenna arrays can be used to improve the spectrum efficiency (SE) of wireless communications [1,2,3,4]. More advanced detectors lead to improved bit error rate (BER) performance for MIMO systems (with either ideal or low-resolution ADCs) and higher computational complexity and higher power consumption. MIMO systems with low-resolution ADCs; We analyze the transmission power required for achieving a target BER, the power required for signal detection, and the power consumption due to the ADCs given the system configuration; We analyze and compare the EE for several different MIMO detectors under a universal system-level power consumption model, and discuss the influence of the number of antennas, the ADC resolution and the signal processing algorithms on the performance. R received signal after QR decomposition ξ noise variance after QR decomposition y received signal

System Model
MIMO With Low-Precision ADC
MIMO Detection
MMSE Detector
LR-SIC Detector
Energy Efficiency
Transmission Power
Power Consumption by Signal Detection
ADC Power Consumption
Simulation Results and Discussion
EE Performance
Conclusions
Full Text
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