The feasibility conditions of interference alignment for MIMO interference networks

Ruan, Liangzhong; Lau, V.K.N.; Win, Moe Z.

doi:10.1109/isit.2012.6283963

Cited by 39 publications

(110 citation statements)

References 15 publications

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“…Rank of a semidefinite symmetric matrix is equal to the number of its non-zero singular values and nuclear norm of this matrix is sum of the all singular values. In fact, by using the nuclear norm function in (6) it is wished that minimizing the sum of the singular values leads to decrease singular values and consequently, lower rank matrices are obtained. Both small and large positive singular values have equal effect on the rank of positive semidefinite matrices but, the l 1 norm approximation (nuclear norm) sets high emphasis on small singular values.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…In this section, we use l 2 norm approximation to solve RCRM problem (6). In comparison with l 1 norm approximation, large singular values get higher weights in l 2 norm approximation; consequently, l 2 norm approximation yields fewer large singular values than l 1 norm approximation [9].…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The presence of uncoordinated interference degrades the performance of the coordinated part and cannot be ignored [5]. Furthermore, perfect IA is not feasible for such a network [6].…”

mentioning

confidence: 99%

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Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels

Mollaebrahim

Ghari

Fazel

et al. 2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

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Abstract-Interference is a key bottleneck in wireless communication systems. Interference alignment is a management technique that align interference from other transmitters in the least possibly dimension subspace at each receiver and provides the remaining dimensions for free interference signal. An uncoordinated interference is an example of interference which cannot be aligned coordinately with interference from coordinated part; consequently, the performance of interference alignment approaches are degraded. In this paper, we propose a rank minimization method to enhance the performance of interference alignment in the presence of uncoordinated interference sources. Firstly, to obtain higher multiplexing gain, a new rank minimization based optimization problem is proposed; then, a new class of convex relaxation is introduced which can reduce the optimal value of the problem and obtain lower rank solutions by expanding the feasibility set. Simulation results show that our proposed method can obtain considerably higher multiplexing gain and sum rate than other approaches in the interference alignment framework.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Proposed Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels

Mollaebrahim

Ghari

Fazel

et al. 2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

View full text Add to dashboard Cite

show abstract

“…In [8], the authors proposed designing the precoding matrices by minimizing the chordal distances of interfering subspaces. Apart from the above schemes, the feasibility conditions for IA in an interference channel were investigated in [10][11][12] whereby a rapid convergent IA scheme for wireless sensor networks was proposed.…”

Section: Introductionmentioning

confidence: 99%

Interference Alignment Based on Rank Constraint in MIMO Cognitive Radio Networks

Diao

Dong

et al. 2017

Symmetry

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Abstract:In this paper, we focus on the interference management in the cognitive radio (CR) network comprised of multiple primary users (PUs) and multiple secondary users (SUs). Firstly, two interference alignment (IA) schemes are proposed to mitigate the interference among PUs. The first one is an interference rank minimization (IRM) scheme, which aims to minimize the rank of the joint interference matrix via alternating between the forward and reverse communication links. Considering the overhead of information exchanged between the transmitters and receivers in the IRM scheme, we further develop an interference subspace distance minimization (ISDM) scheme which runs at the transmitters only. The ISDM scheme focuses on aligning the subspaces spanned by interference with an aligned subspace introduced in this paper. For the secondary network, though IRM and ISDM mitigate the received interference at secondary receivers, they make no attempt to eliminate the interference from SUs to PUs. To address this, we improve the IRM and ISDM schemes by putting a rank constraint into their optimizations, where the rank constraint forces the ranks of the interference matrices from SUs to PUs to be zero. Simulation results validate the effectiveness of the proposed schemes in terms of the average sum rate.

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“…The proper condition was proved to be sufficient for two cases: 1) M = N in [16] and 2) either M or N is divisible by the number of data streams per user d [17]. The study in [8] investigated the sufficient conditions of linear IA feasibility for the asymmetric 1 The configurations are summarized in Table II. MIMO-IC. In [9], the authors developed a polynomial complexity test that allows a complete characterization of the achievable DoF region by the linear IA for the symmetric MIMO-IC with arbitrary antenna configuration.…”

mentioning

confidence: 99%

Genie Tree and Degrees of Freedom of the Symmetric MIMO Interfering Broadcast Channel

Liu

Yang

2016

IEEE Trans. Signal Process.

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Abstract-In this paper, we study the information theoretic maximal degrees of freedom (DoF) for the symmetric multiinput-multi-output (MIMO) interfering broadcast channel (IBC) with arbitrary antenna configurations. For the G-cell K-user M × N MIMO-IBC network, we find that the information theoretic maximal DoF per user are related to three DoF bounds: 1) the decomposition DoF bound d Specifically, for most configurations in Region I, the information theoretic maximal DoF are the decomposition DoF bound and can be achieved by the asymptotic IA. For all configurations in Region II, the information theoretic maximal DoF are the quantity DoF bound and can be achieved by the linear IA.To obtain the tight upper-bound, we propose a unified way to construct genies, where the genies help each base station or user resolve the maximal number of interference. According to the feature that the designed genies with the same dimension can derive identical DoF upper-bound, we convert the information theoretic DoF upper-bound problem into a linear algebra problem and obtain the closed-form DoF upper-bound expression. Moreover, we develop a non-iterative linear IA transceiver to achieve the DoF upper-bound for the networks with antenna configurations in Region II, which means that the derived DoF upper-bound is tightest. The basic principles to derive the DoF upper-bound and design the linear IA transceiver to achieve the DoF upper-bound can be extended into general asymmetric networks.Index Terms-Interference alignment (IA), interfering broadcast channel (IBC), degrees of freedom (DoF), genie tree, irresolvable and resolvable inter-cell interferences (ICIs)

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The feasibility conditions of interference alignment for MIMO interference networks

Cited by 39 publications

References 15 publications

Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels

Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels

Interference Alignment Based on Rank Constraint in MIMO Cognitive Radio Networks

Genie Tree and Degrees of Freedom of the Symmetric MIMO Interfering Broadcast Channel

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