Millimeter-wave massive MIMO systems relying on generalized sub-array-connected hybrid precoding
Millimeter-wave massive MIMO systems relying on generalized sub-array-connected hybrid precoding
In this paper, we consider a generalized sub-array-connected (GSAC) architecture for arbitrary radio frequency (RF) chain and antenna configurations, where the number of RF chains connected to a sub-array and the number of antennas in each sub-array can be arbitrary. Our design objective is to improve the energy efficiency of the hybrid precoder of millimeter-wave massive multiple input multiple output systems. We first propose a successive interference cancellation based hybrid precoding algorithm to maximize the achievable rate for any given RF chain and antenna configuration. This algorithm first decomposes the total achievable rate optimization problem into multiple sub-rate optimization problems, then it successively maximizes these sub-rates. Since the number of RF chains is limited, we can afford using an exhaustive search scheme to evaluate all configurations and identify the one having the best energy efficiency. Moreover, to rely on an attractive limited feedback, we also propose a beamsteering codebook for our hybrid precoding aided GSAC architecture. Our simulation results demonstrate that the proposed scheme achieves a similar rate as the corresponding optimal unconstrained precoder. Furthermore, we show that the energy efficiency of the proposed scheme is better than that of the existing schemes in the fully connected and sub-array-connected architectures.
8940-8950
Chen, Yun
f5d4b8c5-fc18-4cc1-8487-7128635278c3
Chen, Da
1ba7fcb8-b6a0-417b-8484-93df441d7c2c
Jiang, Tao
9e527cf6-43a9-46a5-845e-bc66c9ce15ac
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
September 2019
Chen, Yun
f5d4b8c5-fc18-4cc1-8487-7128635278c3
Chen, Da
1ba7fcb8-b6a0-417b-8484-93df441d7c2c
Jiang, Tao
9e527cf6-43a9-46a5-845e-bc66c9ce15ac
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, Yun, Chen, Da, Jiang, Tao and Hanzo, Lajos
(2019)
Millimeter-wave massive MIMO systems relying on generalized sub-array-connected hybrid precoding.
IEEE Transactions on Vehicular Technology, 68 (9), .
(doi:10.1109/TVT.2019.2930639).
Abstract
In this paper, we consider a generalized sub-array-connected (GSAC) architecture for arbitrary radio frequency (RF) chain and antenna configurations, where the number of RF chains connected to a sub-array and the number of antennas in each sub-array can be arbitrary. Our design objective is to improve the energy efficiency of the hybrid precoder of millimeter-wave massive multiple input multiple output systems. We first propose a successive interference cancellation based hybrid precoding algorithm to maximize the achievable rate for any given RF chain and antenna configuration. This algorithm first decomposes the total achievable rate optimization problem into multiple sub-rate optimization problems, then it successively maximizes these sub-rates. Since the number of RF chains is limited, we can afford using an exhaustive search scheme to evaluate all configurations and identify the one having the best energy efficiency. Moreover, to rely on an attractive limited feedback, we also propose a beamsteering codebook for our hybrid precoding aided GSAC architecture. Our simulation results demonstrate that the proposed scheme achieves a similar rate as the corresponding optimal unconstrained precoder. Furthermore, we show that the energy efficiency of the proposed scheme is better than that of the existing schemes in the fully connected and sub-array-connected architectures.
Text
Millimeter-Wave Massive MIMO Systems Relying on Generalized Sub-Array-Connected Hybrid Precoding
- Accepted Manuscript
More information
Accepted/In Press date: 16 July 2019
e-pub ahead of print date: 23 July 2019
Published date: September 2019
Identifiers
Local EPrints ID: 435350
URI: http://eprints.soton.ac.uk/id/eprint/435350
ISSN: 0018-9545
PURE UUID: 0c5fa25c-a39f-4aac-afa0-eb644900541f
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Date deposited: 31 Oct 2019 17:30
Last modified: 18 Mar 2024 02:36
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Contributors
Author:
Yun Chen
Author:
Da Chen
Author:
Tao Jiang
Author:
Lajos Hanzo
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