Quantized Precoding in Massive MIMO Systems
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Solution Overview
Problem
Massive MIMO systems face challenges with high hardware costs and power consumption due to the use of high-resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs), which are exacerbated by the need for low-resolution DACs and ADCs to reduce costs and power consumption, leading to signal distortions and performance degradation in conventional precoding schemes.
Innovation Solution
A transmitter is developed that determines a normalized factor for precoding signals, iteratively finding a descending direction of difference between intended and received signals, and quantizes precoded signals for transmission, using a Batch Gradient Descent (BGD) based quantized precoding scheme to achieve efficient precoding with low-complexity and high detection performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution DACs and ADCs are used in massive MIMO systems, then signal quality and detection performance are improved, but hardware cost and power consumption increase exponentially
Solution Approach 1:
The patent changes the resolution parameter of DACs and ADCs from high to low (e.g., 1-bit to 2-4 bits), accepting quantization distortion in exchange for exponential reduction in power consumption and hardware cost. This parameter change is applied to the converter resolution while maintaining system functionality through compensating techniques.
Solution Approach 2:
The patent converts the harmful effect of quantization distortion (caused by low-resolution converters) into a benefit by designing quantized precoding algorithms that specifically address and compensate for this distortion. The distortion pattern becomes predictable and manageable through mathematical modeling, allowing the system to achieve good performance with low-resolution hardware.
2Use of energy by moving object
If low-resolution DACs are used to reduce power consumption, then hardware cost and power consumption are reduced, but signal distortion increases and detection performance degrades
Solution Approach 1:
The patent applies precoding operations before signal transmission to pre-compensate for the quantization distortion that will occur in low-resolution DACs. By performing this compensation action in advance at the transmitter, the system prepares the signal to withstand the upcoming quantization process, thereby maintaining detection performance despite using low-resolution converters.
Solution Approach 2:
The patent incorporates feedback mechanisms where the receiver detects the transmitted signal and sends channel state information back to the transmitter. This feedback enables the transmitter to adapt its quantized precoding strategy to current channel conditions, improving detection performance in the presence of quantization distortion.
3Ease of manufacture
If conventional precoding schemes are used with low-resolution DACs, then hardware cost is reduced, but computational complexity increases and detection performance is insufficient
Solution Approach 1:
The patent segments the precoding process into distinct stages: channel estimation, quantized precoding matrix computation, and signal transmission. This segmentation allows each stage to be optimized independently, reducing overall computational complexity while maintaining detection performance with low-resolution hardware.
Solution Approach 2:
The patent employs computationally efficient algorithms that can be implemented with simpler, lower-cost processing hardware. By designing algorithms that are less computationally intensive, the system can use cheaper baseband processors that consume less power and cost less, aligning with the overall goal of reducing hardware cost while maintaining adequate performance.
4Productivity
If high-order modulations are used to increase data rate, then spectral efficiency is improved, but computational complexity of precoding increases significantly
Solution Approach 1:
The patent changes the modulation order parameter while adapting the quantized precoding algorithm accordingly. For high-order modulations (e.g., 64-QAM, 256-QAM), the system adjusts the precoding computation to account for the increased sensitivity to distortion, using appropriate quantization levels and precoding strategies that balance the higher data rate requirement with manageable computational complexity.
Data Source
AI summary
Example embodiments of the present disclosure relate to a transmitter, method, apparatus and computer readable storage medium for quantized precoding in a massive multiple-input multiple-output (MIMO) system. In example embodiments, a transmitter determines a normalized factor for precoding of a plurality of signals intended for a plurality of receivers. The first device precodes the plurality of intended signals using the normalized factor by iteratively performing acts. The acts include determining, by using the normalized factor, a descending direction of a difference between the plurality of intended signals and corresponding signals received at the plurality of receivers, a descending rate of the difference being above a threshold rate in the descending direction, and determining a plurality of precoded signals based on the descending direction. Then, the first device quantizes the plurality of precoded signals for transmission by the transmitter to the plurality of receivers.