On Feasibility of Interference Alignment in MIMO Interference Networks

Yetis, Cenk M.; Gou, Tiangao; Jafar, Syed A.; Kayran, A.H.

doi:10.1109/tsp.2010.2050480

Cited by 658 publications

(817 citation statements)

References 28 publications

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“…In general, the feasibility of the IA problem is associated with the solvability of a set of polynomial equations, which is the focus of algebraic geometry [10], [11]. There are very few works that studied the feasibility condition of IA problems using algebraic geometry [12]- [15]. In [12], the authors studied the feasibility condition of IA problem in single stream MIMO interference networks using Bernstein's Theorem in algebraic geometry [11,Thm.…”

Section: Introductionmentioning

confidence: 99%

The feasibility conditions of interference alignment for MIMO interference networks

Ruan

Lau

Win

2012

2012 IEEE International Symposium on Information Theory Proceedings

108

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Abstract-Interference alignment (IA) has attracted great attention in the last few years for its breakthrough performance in interference networks. However, despite the numerous works dedicated to IA, the feasibility conditions of IA remains unclear for most network topologies. The IA feasibility analysis is challenging as the IA constraints are sets of high-degree polynomials, for which no systematic tool to analyze the solvability conditions exists. In this work, by developing a new mathematical framework that maps the solvability of sets of polynomial equations to the linear independence of their first-order terms, we propose a sufficient condition that applies to MIMO interference networks with general configurations. We have further proved that this sufficient condition matches with the necessary conditions under a wide range of configurations. These results further consolidate the theoretical basis of IA.

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Section: Introductionmentioning

confidence: 99%

The feasibility conditions of interference alignment for MIMO interference networks

Ruan

Lau

Win

2012

2012 IEEE International Symposium on Information Theory Proceedings

108

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“…This technique has been shown to achieve the DoFs for a range of interference channels [5,7,28]. Finding out the exact number of needed dimensions and the precoding vectors to achieve IA is a cumbersome task but a number of approaches have been presented in the literature for this purpose [21,66,75]. The IA technique was also investigated in the context of cellular networks, showing that it can effectively suppress cochannel interference [9,15,64,66].…”

Section: Classification Of Ia Techniquesmentioning

confidence: 99%

“…Since beamforming schemes are common in the existing point to point MIMO, BC and multiple access networks, linear IA seems to be the most easily accessible form of IA from practical point of view. A linear IA problem becomes a proper or improper based on whether or not the number of equations exceeds the number of variables [75]. The proper systems are likely to be practically feasible and improper systems are likely to be infeasible.…”

Section: Classification Of Ia Techniquesmentioning

confidence: 99%

“…Let us consider K user MIMO interference setting with M number of antennas in each transmitter and N number of antennas in each receiver. According [75], the .M N; d / K linear IA problem, d being the number of independent streams, is proper if and only if the following condition is satisfied: Subspace IA: In this scheme, the interferences are aligned to multidimensional subspace instead of a single dimension. In the context of cellular networks, IA scheme provides advantage due to multiuser gain and aligning interferences becomes challenging in the three cell case since there exist multiple non-intended receivers [64].…”

Section: Classification Of Ia Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Cognitive Interference Alignment for Spectral Coexistence

Sharma

Chatzinotas

Ottersten

2014

Cognitive Radio and Networking for Heterogeneous Wireless Networks

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Interference Alignment (IA) has been widely recognized as a promising interference mitigation technique since it can achieve the optimal degrees of freedom in certain interference limited channels. In the context of Cognitive Radio (CR) networks, this technique allows the coexistence of two heterogeneous wireless systems in an underlay cognitive mode. The main concept behind this technique is the alignment of the interference on a signal subspace in such a way that it can be filtered out at the non-intended receiver by sacrificing some signal dimensions. This chapter starts with an overview of IA principle, Degree of Freedom (DoF) concept, and the classification of existing IA techniques. Furthermore, this chapter includes a discussion about IA applications in CR networks. Moreover, a generic system model is presented for allowing the coexistence of two heterogeneous networks using IA approach while relevant precoding and filtering processes are described. In addition, two important practical applications of the IA technique are presented along with the numerical results for underlay spectral coexistence of (i) femtocell-macrocell systems, and (ii) monobeam-multibeam satellite systems. More specifically, an uplink IA scheme is investigated in order to mitigate the interference of femtocell User Terminals (UTs) towards the macrocell Base Station (BS) in the spatial domain and the interference of multibeam satellite terminals towards the monobeam satellite in the frequency domain.

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“…Although, in general, "clustering" is utilized for reducing the computational complexity, it has the significance in the context of IA, i.e., it can reduce the required DoF (time-slots, bandwidth, antennas, etc.) to perform IA based on the feasibility condition [5], which is exploited in our scheme. Through simulation we evaluate the effect of clustering small-cells in HetNet with IA.…”

Section: Introductionmentioning

confidence: 99%

Clustering small cells in heterogeneous networks with interference alignment

Seno

Ohtsuki

Jiang³

et al. 2017

IEICE ComEX

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In this letter, we consider heterogeneous networks (HetNets) where interference alignment (IA), which is one of the promising interference management techniques, is applied. Using IA in HetNet has an issue that as the number of small-cells increases, small base stations (BSs) become more costly in terms of the number of antennas, because they require more spatial degrees of freedom (DoF) to align the inter-small-cell interference. To overcome this issue, we conduct clustering small-cells and aligning intersmall-cell interference only within each cluster, which reduces the number of required spatial DoF at each small BS. The effects of clustering small-cells are evaluated through the simulations and it is found that the achievable rate per transmit antenna increases by clustering small-cells.

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On Feasibility of Interference Alignment in MIMO Interference Networks

Abstract: Abstract-

Cited by 658 publications

References 28 publications

The feasibility conditions of interference alignment for MIMO interference networks

The feasibility conditions of interference alignment for MIMO interference networks

Cognitive Interference Alignment for Spectral Coexistence

Clustering small cells in heterogeneous networks with interference alignment

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