Resource Allocation for Transmit Hybrid Beamforming in Decoupled Millimeter Wave Multiuser-MIMO Downlink

This paper presents a study on joint radio resource allocation and hybrid precoding in multi-carrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficie...

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Vydané v:IEEE access Ročník 5; s. 170 - 182
Hlavní autori: Ahmed, Irfan, Khammari, Hedi, Shahid, Adnan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
5G mobile communication
Algorithm design and analysis
Algorithms
Array signal processing
Beamforming
Cellular communication
Chains
Computational geometry
Constraints
Convexity
Efficiency
Millimeter wave communication
Millimeter waves
Millimeter-wave
MIMO
MIMO communication
Noise levels
Optimization
Radio frequency
Resource allocation
Resource management
Semidefinite programming
Signal to noise ratio
Spectra
ISSN:2169-3536, 2169-3536
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Shrnutí:This paper presents a study on joint radio resource allocation and hybrid precoding in multi-carrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficiency under the per subchannel power and the beamforming rank constraints. Two heuristic algorithms are designed. The proportional fairness hybrid beamforming algorithm provides the transmit precoder with a proportional fair spectral efficiency among users for the desired number of radio-frequency (RF) chains. Then, we transform the number of RF chains or rank constrained optimization problem into convex semidefinite programming (SDP) problem, which can be solved by standard techniques. Inspired by the formulated convex SDP problem, a low-complexity, two-step, PF-relaxed optimization algorithm has been provided for the formulated convex optimization problem. Simulation results show that the proposed suboptimal solution to the relaxed optimization problem is near-optimal for the signal-to-noise ratio SNR ≤ 10 dB and has a performance gap not greater than 2.33 b/s/Hz within the SNR range 0-25 dB. It also outperforms the maximum throughput and PF-based hybrid beamforming schemes for sum spectral efficiency, individual spectral efficiency, and fairness index.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2016.2634096