Cost-Efficient GPIP Processing for Large-Scale Multi-User MIMO Systems

This paper investigates a joint user selection, power allocation, and beamforming strategy for maximizing a weighted sum-spectral efficiency in a single-cell multi-user multiple-input multiple-output (MU-MIMO) system. Finding such a joint strategy is challenging due to the non-convexity of the sum-s...

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Bibliographic Details
Published in:IEEE access 2023-01, Vol.11, p.1-1
Main Authors: Moon, Seungsik, Lee, Namyoon, Lee, Youngjoo
Format: Article
Language:English
Subjects:
Algorithms
Array signal processing
Beamforming
Complexity
Computational efficiency
Convexity
Costs
Efficiency
Heuristic algorithms
Iterative methods
Low-complexity
MIMO communication
MU-MIMO
Optimization
Polynomials
power allocation
Precoding
Resource management
Sums
User centered design
user selection
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Summary:This paper investigates a joint user selection, power allocation, and beamforming strategy for maximizing a weighted sum-spectral efficiency in a single-cell multi-user multiple-input multiple-output (MU-MIMO) system. Finding such a joint strategy is challenging due to the non-convexity of the sum-spectral efficiency function for the optimization variables. The recent algorithm, referred to as generalized power iteration precoding (GPIP), allows finding a stationary point in polynomial time for this non-convex problem. GPIP, however, is not scalable to a large-scale MU-MIMO system because of the overwhelming computational complexity. This high complexity makes the hardware energy efficiency worse as the number of antennas and users increases. This paper presents a low-cost simplified GPIP algorithm by jointly taking into account the implementation-level efficiency and algorithm-level performance. The proposed algorithm is to jointly harness the ideas of i ) multiply-accumulate (MAC) operation reduction, ii ) dynamic range reduction, and iii ) low-complexity matrix inversion with approximate computing. Experimental results reveal that the proposed simplified GPIP algorithm reduces the total cost for solving the GPIP algorithm up to 99% while attaining a similar sum-spectral efficiency compared to that of a naive implementation method for GPIP in large-scale MU-MIMO systems.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3297223