Hybrid CPU–GPU implementation of the transformed spatial domain channel estimation algorithm for mmWave MIMO systems

Hybrid platforms combining multicore central processing units (CPU) with many-core hardware accelerators such as graphic processing units (GPU) can be smartly exploited to provide efficient parallel implementations of wireless communication algorithms for Fifth Generation (5G) and beyond systems. Ma...

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Vydáno v:The Journal of supercomputing Ročník 79; číslo 9; s. 9371 - 9382
Hlavní autoři: Lloria, Diego, Aviles, Pablo M., Belloch, Jose A., Roger, Sandra, Botella-Mascarell, Carmen, Lindoso, Almudena
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.06.2023
Springer Nature B.V
Témata:
5G mobile communication
Algorithms
Antennas
Central processing units
Compilers
Computer Science
CPUs
Fourier transforms
Graphics processing units
Interpreters
Microprocessors
Millimeter waves
MIMO communication
Processor Architectures
Programming Languages
Random variables
Signal processing
Wireless communications
MIMO communication systems
Multicore CPU
Channel estimation
Graphic processing units
ISSN:0920-8542, 1573-0484
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Shrnutí:Hybrid platforms combining multicore central processing units (CPU) with many-core hardware accelerators such as graphic processing units (GPU) can be smartly exploited to provide efficient parallel implementations of wireless communication algorithms for Fifth Generation (5G) and beyond systems. Massive multiple-input multiple-output (MIMO) systems are a key element of the 5G standard, involving several tens or hundreds of antenna elements for communication. Such a high number of antennas has a direct impact on the computational complexity of some MIMO signal processing algorithms. In this work, we focus on the channel estimation stage. In particular, we develop a parallel implementation of a recently proposed MIMO channel estimation algorithm. Its performance in terms of execution time is evaluated both in a multicore CPU and in a GPU. The results show that some computation blocks of the algorithm are more suitable for multicore implementation, whereas other parts are more efficiently implemented in the GPU, indicating that a hybrid CPU–GPU implementation would achieve the best performance in practical applications based on the tested platform.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-05018-w