Energy-Efficient Flat Precoding for MIMO Systems

IF 5.8 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Signal Processing Pub Date : 2025-02-04 DOI:10.1109/TSP.2025.3537960
Foad Sohrabi;Carl Nuzman;Jinfeng Du;Hong Yang;Harish Viswanathan
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Abstract

This paper addresses the suboptimal energy efficiency of conventional digital precoding schemes in multiple-input multiple-output (MIMO) systems. Through an analysis of the power amplifier (PA) output power distribution associated with conventional precoders, it is observed that these power distributions can be quite uneven, resulting in large PA backoff (thus low efficiency) and high power consumption. To tackle this issue, we propose a novel approach called flat precoding, which aims to control the flatness of the power distribution within a desired interval. In addition to reducing PA power consumption, flat precoding offers the advantage of requiring smaller saturation levels for PAs, which reduces the size of PAs and lowers the cost. To incorporate the concept of flat power distribution into precoding design, we introduce a new lower-bound per-antenna power constraint alongside the conventional sum power constraint and the upper-bound per-antenna power constraint. By adjusting the lower-bound and upper-bound values, we can effectively control the level of flatness in the power distribution. We then seek to find a flat precoder that satisfies these three sets of constraints while maximizing the weighted sum rate (WSR). In particular, we develop efficient algorithms to design weighted minimum mean squared error (WMMSE) and zero-forcing (ZF)-type precoders with controllable flatness features that maximize WSR. Numerical results demonstrate that complete flat precoding approaches, where the power distribution is a straight line, achieve the best trade-off between spectral efficiency and energy efficiency for existing PA technologies. We also show that the proposed ZF and WMMSE precoding methods can approach the performance of their conventional counterparts with only the sum power constraint, while significantly reducing PA size and power consumption.
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多输入多输出(MIMO)系统的高能效扁平精确编码
本文研究了多输入多输出(MIMO)系统中传统数字预编码方案的次优能效问题。通过分析与传统预编码器相关的功率放大器(PA)输出功率分布,可以观察到这些功率分布可能相当不均匀,导致大的PA回退(因此效率低)和高功耗。为了解决这个问题,我们提出了一种称为平坦预编码的新方法,旨在将功率分布的平坦性控制在期望的间隔内。除了降低PA功耗外,平面预编码还提供了对PA要求更小的饱和水平的优势,从而减小了PA的尺寸并降低了成本。为了将平坦功率分配的概念整合到预编码设计中,我们在传统的和功率约束和上功率约束的基础上,引入了一种新的单天线功率约束下限。通过调整上界值和下界值,可以有效地控制功率分布的平整度。然后,我们寻求找到一个平面预编码器,满足这三组约束,同时最大化加权和率(WSR)。特别是,我们开发了有效的算法来设计加权最小均方误差(WMMSE)和零强迫(ZF)型预编码器,这些预编码器具有可控制的平坦度特征,可以最大化WSR。数值结果表明,功率分布为直线的完全平面预编码方法在频谱效率和能量效率之间达到了现有PA技术的最佳平衡。我们还表明,所提出的ZF和WMMSE预编码方法可以在仅具有和功率约束的情况下接近传统预编码方法的性能,同时显着减小了PA尺寸和功耗。
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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