Large-scale MIMO (Multiple Input Multiple Output) optimal user scheduling number configuration method

Abstract

The invention discloses a large-scale MIMO (Multiple Input Multiple Output) optimal user scheduling number configuration method. In a large-scale MIMO system, a base station needs to be configured with tens of, even hundreds of antennas. Specific to the aim of lowering hardware cost and system power consumption, the antennas of the base station are configured with 1-bit-quantified DACs (Digital-to-Analog Converters), and single antenna users adopt finite-bit-quantified ADCs (Analog-to-Digital Converters). Oriented to downlink data transmission in a system, normalized zero-forcing precoding is adopted. Under the condition that the number of the base station antennas, user ADC accuracy, a signal-to-noise ratio, a pilot frequency length and a coherence interval are given, an optimal user scheduling number is calculated through maximization of an achievable rate provided by each antenna. Through adoption of the method, calculation is easy, and the optimal user number can be determined rapidly. The method has guiding significance to multi-user scheduling parameter configuration of the large-scale MIMO system.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for configuring the number of optimal user scheduling for massive MIMO. Background technique [0002] In recent years, due to its huge energy efficiency advantages and room for capacity improvement, the massive MIMO (Multiple Input Multiple Output) scheme has become a key technology for the next generation of mobile communication solutions (5G). In a massive MIMO system, a base station needs to be configured with dozens or even hundreds of antennas and serve multiple users at the same time. Since each transmitting antenna needs to configure a digital-to-analog conversion unit (DAC) for the real part and the imaginary part of the signal, as the number of antennas increases, the hardware and power consumption costs of the system increase accordingly. There are currently two solutions to this problem. One is to use low-precision DAC (because the...

AI Technical Summary

Problems solved by technology

Usually, if the number of users is too small, although each user can obtain a higher channel capacity, the sum of the multi-user channel capacity of the system as a whole will not be very high; on the contrary, if the number of users is too large, the channel capacity of each user The capacity will be very low, which will also affect the sum of the multi-user channel capacity of the system as a whole

Images