User scheduling for massive MIMO OFDMA systems with hybrid analog-digital beamforming

This paper proposes a new user scheduling and sub-carrier allocation algorithm for multiuser downlink massive multiple input multiple output (MIMO) orthogonal frequency division multiple access (OFDMA) systems with hybrid analogdigital beamforming (HB). We assume that the transmitter having N antenn...

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Vydáno v:2015 IEEE International Conference on Communications (ICC) s. 1757 - 1762
Hlavní autoři: Bogale, Tadilo Endeshaw, Long Bao Le, Haghighat, Afshin
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2015
Témata:
Antennas
Array signal processing
Fading
Hybrid Analog-Digital beamforming
Massive MIMO
Millimeter wave
MIMO
Radio frequency
Resource management
RF chain
Scheduling
ISSN:1550-3607
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Popis
Shrnutí:This paper proposes a new user scheduling and sub-carrier allocation algorithm for multiuser downlink massive multiple input multiple output (MIMO) orthogonal frequency division multiple access (OFDMA) systems with hybrid analogdigital beamforming (HB). We assume that the transmitter having N antennas is serving K i decentralized single antenna receivers by sub-carrier i. The scheduling algorithm leverages the solutions of the digital beamforming (DB) result and is designed to maximize the total sum rate of all sub-carriers under per carrier power constraint. For this system and problem setup, the proposed algorithm is explained as follows: First, we express the HB matrix of sub-carrier i as a product of AB i , where the high dimensional matrix A ∈ C N×Na is common to all subcarriers whereas, B i ∈ C Na×Ki is a low dimensional matrix which is designed for sub-carrier i, and Na is the number of RF chains satisfying N ≥ Na ≥ K i . Second, we compute A as the first Na eigenvectors of the left singular value decomposition of the combined DB precoder matrices of sub-carriers having the highest sum rate. Finally, for fixed A, we compute Bi and its corresponding users such that the total sum rate of all sub-carriers is maximized. The performance of the proposed scheduling is studied analytically. Furthermore, the superiority of the proposed algorithm over that of the existing one is quantified analytically and demonstrated by computer simulations.
ISSN:1550-3607
DOI:10.1109/ICC.2015.7248579