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Grouping-Based Interference Alignment With IA-Cell Assignment in Multi-Cell MIMO MAC Under Limited Feedback. / Cao, Pan; Zappone, Alessio; Jorswieck, Eduard.

In: IEEE Transactions on Signal Processing, Vol. 64, No. 5, 01.03.2016, p. 1336-1351.

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@article{d73f2d9478e94a23b0b097224aa55622,
title = "Grouping-Based Interference Alignment With IA-Cell Assignment in Multi-Cell MIMO MAC Under Limited Feedback",
abstract = "Interference alignment (IA) is a promising technique to efficiently mitigate interference and to enhance the capacity of a wireless communication network. This paper proposes a grouping-based interference alignment (GIA) with optimized IA-Cell assignment for the multiple cells interfering multiple-input multiple-output (MIMO) multiple access channel (MAC) network under limited feedback. This work consists of three main parts: 1) an improved version (including some new improvements) of the GIA with respect to the degrees of freedom (DoF) and optimal linear transceiver design is provided, which allows for low-complexity and distributed implementation; 2) based on the GIA, the concept of IA-Cell assignment is introduced. Three IA-Cell assignment algorithms are proposed with different backhaul overhead and their DoF and rate performance is investigated; 3)the performance of the proposed GIA algorithms is studied under limited feedback of IA precoders. To enable efficient feedback, a dynamic feedback bit allocation (DBA) problem is formulated and solved in closed-form. The practical implementation, the backhaul overhead requirements, and the complexity of the proposed algorithms are analyzed. Numerical results show that our proposed algorithms greatly outperform the traditional GIA under both unlimited and limited feedback.",
author = "Pan Cao and Alessio Zappone and Eduard Jorswieck",
year = "2016",
month = "3",
day = "1",
doi = "10.1109/TSP.2015.2496356",
language = "English",
volume = "64",
pages = "1336--1351",
journal = "IEEE Transactions on Signal Processing",
issn = "1053-587X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",

}

RIS

TY - JOUR

T1 - Grouping-Based Interference Alignment With IA-Cell Assignment in Multi-Cell MIMO MAC Under Limited Feedback

AU - Cao, Pan

AU - Zappone, Alessio

AU - Jorswieck, Eduard

PY - 2016/3/1

Y1 - 2016/3/1

N2 - Interference alignment (IA) is a promising technique to efficiently mitigate interference and to enhance the capacity of a wireless communication network. This paper proposes a grouping-based interference alignment (GIA) with optimized IA-Cell assignment for the multiple cells interfering multiple-input multiple-output (MIMO) multiple access channel (MAC) network under limited feedback. This work consists of three main parts: 1) an improved version (including some new improvements) of the GIA with respect to the degrees of freedom (DoF) and optimal linear transceiver design is provided, which allows for low-complexity and distributed implementation; 2) based on the GIA, the concept of IA-Cell assignment is introduced. Three IA-Cell assignment algorithms are proposed with different backhaul overhead and their DoF and rate performance is investigated; 3)the performance of the proposed GIA algorithms is studied under limited feedback of IA precoders. To enable efficient feedback, a dynamic feedback bit allocation (DBA) problem is formulated and solved in closed-form. The practical implementation, the backhaul overhead requirements, and the complexity of the proposed algorithms are analyzed. Numerical results show that our proposed algorithms greatly outperform the traditional GIA under both unlimited and limited feedback.

AB - Interference alignment (IA) is a promising technique to efficiently mitigate interference and to enhance the capacity of a wireless communication network. This paper proposes a grouping-based interference alignment (GIA) with optimized IA-Cell assignment for the multiple cells interfering multiple-input multiple-output (MIMO) multiple access channel (MAC) network under limited feedback. This work consists of three main parts: 1) an improved version (including some new improvements) of the GIA with respect to the degrees of freedom (DoF) and optimal linear transceiver design is provided, which allows for low-complexity and distributed implementation; 2) based on the GIA, the concept of IA-Cell assignment is introduced. Three IA-Cell assignment algorithms are proposed with different backhaul overhead and their DoF and rate performance is investigated; 3)the performance of the proposed GIA algorithms is studied under limited feedback of IA precoders. To enable efficient feedback, a dynamic feedback bit allocation (DBA) problem is formulated and solved in closed-form. The practical implementation, the backhaul overhead requirements, and the complexity of the proposed algorithms are analyzed. Numerical results show that our proposed algorithms greatly outperform the traditional GIA under both unlimited and limited feedback.

U2 - 10.1109/TSP.2015.2496356

DO - 10.1109/TSP.2015.2496356

M3 - Article

VL - 64

SP - 1336

EP - 1351

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

SN - 1053-587X

IS - 5

ER -