Joint User Scheduling, Power Allocation, and Precoding Design for Massive MIMO Systems: A Principal Component Analysis Approach

Ahstract-This paper considers massive multiple-input multiple-output (MIMO) downlink system with imperfect channel state information at transmitter (CSIT). A new optimization framework for the joint user-scheduling, power control, and precoding design is presented. The key idea of the proposed optimization framework is to equivalently reformulate an sum-spectral efficiency maximization problem into the maximization problem of the product of Rayleigh quotients. Although this reformulated optimization problem is not convex, the sub-optimal solution that guarantees the first-order optimality condition is found using the proposed general power iteration algorithm. One major observation is that the proposed sub-optimal solutions provide significant gains in terms of the sum-spectral efficiency compared to the conventional user-scheduling algorithm conjunction with zero-forcing precoding for the massive MIMO systems.

• Publication year

  2018

• Venue

  International Symposium on Information Theory

• Publication date

  2018-06-01

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/ISIT.2018.8437617
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• On the Ergodic Rate Lower Bounds With Applications to Massive MIMO

  2017cited by this paper
• Fundamentals of massive MIMO

  2016cited by this paper
• A New Approach to User Scheduling in Massive Multi-User MIMO Broadcast Channels

  2014cited by this paper
• Joint Spatial Division and Multiplexing—The Large-Scale Array Regime

  2012cited by this paper
• A Coordinated Approach to Channel Estimation in Large-Scale Multiple-Antenna Systems

  2012cited by this paper
• Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas

  2011cited by this paper
• Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

  2010cited by this paper
• Achievable Sum-Rate Maximizing AF Relay Beamforming Scheme in Two-Way Relay Channels

  2008cited by this paper
• On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming

  2006influential reference
• Capacity and power allocation for fading MIMO channels with channel estimation error

  2006cited by this paper
• On the achievable throughput of a multiantenna Gaussian broadcast channel

  2003cited by this paper
• Fading channels: how perfect need "perfect side information" be?

  1999cited by this paper
• Matrix computations

  1983cited by this paper

• Deep Reinforcement Learning-Based Scheduling for Multiband Massive MIMO

  2022cites this paper
• Joint Resource Allocation for Linear Precoding in Downlink Massive MIMO Systems

  2021cites this paper
• A DRL-Based Automated Algorithm Selection Framework for Cross-Layer QoS-Aware Scheduling and Antenna Allocation in Massive MIMO Systems

  2021cites this paper
• Joint user selection and power allocation optimization for energy-efficient MU-MIMO systems with limited feedback

  2021cites this paper
• Sparse Joint Transmission for Cloud Radio Access Networks With Limited Fronthaul Capacity

  2021influential citation
• Exploring pilot assignment methods for pilot contamination mitigation in massive MIMO systems

  2020cites this paper
• Noncooperative Precoding for Massive MIMO HetNets: SILNR Maximization Precoding

  2020influential citation
• Distributed Precoding Using Local CSIT for MU-MIMO Heterogeneous Cellular Networks

  2020cites this paper
• Joint User Selection, Power Allocation, and Precoding Design With Imperfect CSIT for Multi-Cell MU-MIMO Downlink Systems

  2019cites this paper
• Sparse Joint Transmission for Cell-Free Massive MIMO: A Sparse PCA Approach

  2019cites this paper
• Group-Sparse Beamforming for Sum-Spectral Efficiency Maximization in Cloud-RAN

  2019cites this paper