Finite-Precision Conjugate Gradient Method for Massive MIMO Detection
The implementation of the conjugate gradient (CG) method for massive MIMO detection is computationally challenging, especially for a large number of users and correlated channels. In this paper, we propose a low computational complexity CG detection from a finite-precision perspective. First, we develop a finite-precision CG (FP-CG) detection to mitigate the computational bottleneck of each CG iteration and provide the attainable accuracy, convergence, and computational complexity analysis to reveal the impact of finite-precision arithmetic. A practical heuristic is presented to select suitable precisions. Then, to further reduce the number of iterations, we propose a joint finite-precision and block-Jacobi preconditioned CG (FP-BJ-CG) detection. The corresponding performance analysis is also provided. Finally, simulation results validate the theoretical insights and demonstrate the superiority of the proposed detection.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Conjugate gradient MIMO iterative learning control using data-driven stochastic gradients
Data-driven iterative learning control can achieve high performance for systems performing repeating tasks without the need for modeling. The aim of this paper is to develop a fast data-driven method for iterative learni…
Learned Conjugate Gradient Descent Network for Massive MIMO Detection
In this work, we consider the use of model-driven deep learning techniques for massive multiple-input multiple-output (MIMO) detection. Compared with conventional MIMO systems, massive MIMO promises improved spectral eff…
Residual-Based Detections and Unified Architecture for Massive MIMO Uplink
Massive multiple-input multiple-output (M-MIMO) technique brings better energy efficiency and coverage but higher computational complexity than small-scale MIMO. For linear detections such as minimum mean square error (M…
Stochastic Channel Models for Massive and XL-MIMO Systems
In this paper, stochastic channel models for massive MIMO (M-MIMO) and extreme large MIMO (XL- MIMO) system applications are described, evaluated and systematically compared. This work aims to cover new aspects of massiv…
Precoder Design for User-Centric Network Massive MIMO with Matrix Manifold Optimization
In this paper, we investigate the precoder design for user-centric network (UCN) massive multiple-input multiple-output (mMIMO) downlink with matrix manifold optimization. In UCN mMIMO systems, each user terminal (UT) is…
Computational Efficiency