On the achievability of interference alignment in the K-user constant MIMO interference channel

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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“…For instance, in [5], all Rx have 2 antennas. In [6], all nodes have (K + 1) antennas. And in [7], there are only 2 Rxs in the network.…”

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%

“…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]. More specifically, the downlink of orthogonal frequency division multiple access (OFDMA) cellular network with clustered multicell processing is considered in [15], where IA is employed to suppress intracluster interference while intercluster interference has to be tolerated as noise.…”

Section: Classification Of Ia Techniquesmentioning

confidence: 99%

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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“…One must note that, by considering that the channel coefficients in H jk are identically and independently distributed, the existence of a solution for the above IA problem solely depends on the dimensions of the problem (|S|,N t ,N r ) as discussed in [12]. For instance, when the target multiplexing gain d i at the FUE is equal to one, a solution to the system (3) exists for the interference channel composed by |S| − 1 interfering transmissions plus the useful signal if and only if…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, to find the precoding and interference suppression matrices one can use existing iterative algorithms such as in [13,Algorithm 1], [12]. Therefore, the interference from members of the same coalition can be suppressed, yielding, after projection, the following signal at receiver k:…”

Section: Introductionmentioning

confidence: 99%

Cooperative Interference Alignment in Femtocell Networks

Pantisano¹,

Bennis²,

Saad

et al. 2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Abstract-Underlay femtocells have recently emerged as a key technology that can significantly improve the coverage and performance of next-generation wireless networks. In this paper, we propose a novel approach for interference management that enables a number of femtocells to cooperate and improve their downlink rate, by sharing spectral resources and suppressing intra-tier interference using interference alignment. We formulate a coalitional game in partition form among the femtocells and propose a distributed algorithm for coalition formation. Using our approach, the femtocell access points can make individual decisions on whether to cooperate or not, while maximizing a utility function that captures the cooperative gains and the costs in terms of transmit power for information exchange. We show that, using the proposed coalition formation algorithm, the femtocells can self-organize into a network partition composed of disjoint femtocell coalitions, which constitutes the recursive core of the game. Simulation results show significant gains in terms of average payoff per femtocell, reaching up to 30% relative to the non-cooperative scheme.

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On the achievability of interference alignment in the K-user constant MIMO interference channel

Cited by 114 publications

References 5 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

Cooperative Interference Alignment in Femtocell Networks

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