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JOINT OPTIMIZATION OF COMPUTATION AND COMMUNICATION POWER IN MULTI-USER MASSIVE MIMO SYSTEMS.

Xiaohu Ge1, Yang Sun1, Hamid Gharavi2

  • 1School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.

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Summary
This summary is machine-generated.

This study optimizes energy efficiency in massive MIMO 5G systems by jointly managing computation and communication power. The PHONE algorithm significantly reduces power consumption, improving overall system efficiency.

Keywords:
Millimeter wavecomputation powerenergy efficiencyhybrid precodingmassive MIMOpartially-connected structure

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Area of Science:

  • Wireless Communication Systems
  • Signal Processing
  • Energy Efficiency in Telecommunications

Background:

  • Massive MIMO and millimeter wave technologies are crucial for 5G, but increase baseband processing demands and power consumption.
  • Conventional energy efficiency analyses often overlook computation power, leading to inaccurate assessments in massive MIMO systems.

Purpose of the Study:

  • To formulate a joint optimization problem for computation and communication power in multi-user massive MIMO systems with partially-connected RF structures.
  • To investigate the impact of computation power on the energy efficiency of massive MIMO systems.

Main Methods:

  • Developed a joint optimization framework for computation and communication power.
  • Derived an upper bound for energy efficiency considering system constraints.
  • Proposed a suboptimal solution using baseband and RF precoding matrices.
  • Introduced the Optimized Hybrid precOding with computation and commuNication powEr (PHONE) algorithm.

Main Results:

  • Energy efficiency decreases with more antennas and RF chains when computation power is included, contrary to previous findings.
  • The proposed suboptimal solution effectively approaches the derived upper bound on energy efficiency.
  • The PHONE algorithm demonstrates significant improvements in energy and cost efficiencies.

Conclusions:

  • Joint optimization of computation and communication power is essential for accurate energy efficiency analysis in massive MIMO.
  • The PHONE algorithm offers a practical approach to enhance energy and cost efficiencies in 5G systems.
  • Up to 76.59% power saving is achievable in multi-user massive MIMO systems with partially-connected structures.