Maximum Sum-Rate Interference Alignment Algorithms for MIMO Channels

Santamarı́a, Ignacio; González, Óscar; Heath, Robert W.; Peters, Steven W.

doi:10.1109/glocom.2010.5683919

Cited by 140 publications

(136 citation statements)

References 11 publications

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“…As a result, many recent IA works have considered IA solutions in the spatial domain, i.e., without symbol extensions [4]- [6]. However, these approaches are all based on the assumption of perfect channel state information at the transmitters (CSIT), which is hard to obtain in practice.…”

Section: A Prior Workmentioning

confidence: 99%

“…3, we consider a K = 4, N t = 3, N r = 2, d = 1 MIMO interference network. We vary the transmit SNR P and compare the throughput of different schemes under the following parameter settings: 6 The expectation of a log-normal distributed variable is E(ln N (u, δ 2 )) = e interference topology profile dynamics (| |, δ 2 ) = (0.7, 3), sum feedback bits B = 120 and B = 300. The reason that we have two B settings is to help illustrate how the throughput goes with SNR in different feedback bits regimes.…”

Section: B Throughput Comparison Wrt Transmit Snrmentioning

confidence: 99%

“…where {l ji } for different cross-links are assumed to be i.i.d., u is set to be − 1 2 δ 2 to normalize the mean 6 of large fading parameters l ji , ∀j, i = j to be 1.…”

Section: Definition 2 (Random Interference Topology Model)mentioning

confidence: 99%

See 2 more Smart Citations

Limited Feedback Design for Interference Alignment on MIMO Interference Networks With Heterogeneous Path Loss and Spatial Correlations

Rao

Ruan

Lau

2013

IEEE Trans. Signal Process.

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Interference alignment is degree of freedom optimal in K-user MIMO interference channels and many previous works have studied the transceiver designs. However, these works predominantly focus on networks with perfect channel state information at the transmitters and symmetrical interference topology. In this paper, we consider a limited feedback system with heterogeneous path loss and spatial correlations, and investigate how the dynamics of the interference topology can be exploited to improve the feedback efficiency. We propose a novel spatial codebook design, and perform dynamic quantization via bit allocations to adapt to the asymmetry of the interference topology. We bound the system throughput under the proposed dynamic scheme in terms of the transmit SNR, feedback bits and the interference topology parameters. It is shown that when the number of feedback bits scales with SNR as C s ·log SNR, the sum degrees of freedom of the network are preserved. Moreover, the value of scaling coefficient C s can be significantly reduced in networks with asymmetric interference topology.

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Section: A Prior Workmentioning

confidence: 99%

Section: B Throughput Comparison Wrt Transmit Snrmentioning

confidence: 99%

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Limited Feedback Design for Interference Alignment on MIMO Interference Networks With Heterogeneous Path Loss and Spatial Correlations

Rao

Ruan

Lau

2013

IEEE Trans. Signal Process.

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“…간섭채널과 3셀 이상의 셀룰러 네트워크에서 간 섭정렬을 위한 송수신벡터가 닫힌형태로 구해지지 않거나 구해지더라도 모든 채널 정보를 필요로 하 는 문제점을 해결하기 위해 반복 알고리즘들이 제 안되었다 [5][6][7][8][9][10][11][12] . 간섭채널상의 간섭정렬을 위한 반복 알고리즘으로 max-SINR (maximum signal-to-interference-plus-noise ratio) 알고리즘 [5,6] 과 MMSE-IA (minimum mean square error interference alignment) 알고리즘 [7] 이 대표적이며 이와 유사한 반복 알고리즘들이 제안되어 있다 [8][9][10] .…”

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“…간섭채널상의 간섭정렬을 위한 반복 알고리즘으로 max-SINR (maximum signal-to-interference-plus-noise ratio) 알고리즘 [5,6] 과 MMSE-IA (minimum mean square error interference alignment) 알고리즘 [7] 이 대표적이며 이와 유사한 반복 알고리즘들이 제안되어 있다 [8][9][10] . [11,12] .…”

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Iterative Algorithms for Interference Alignment in Cellular Network

Yeo¹,

Cho²

2012

The Journal of Korea Information and Communications Society

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In this paper, we propose iterative algorithms to obtain the transmit and the receive vectors for interference alignment in cellular network. Although the conventional interference alignment algorithms for interference channels can be applied to cellular network, the number of iterations required to achieve a high sum rate is very large. The key idea in the proposed algorithms is to ignore intra-cell interference in updating the transmit vector for uplink and the receive vector for downlink. Numerical results show that the proposed algorithms achieve higher sum rates than the conventional algorithms for given iteration numbers when multiple antennas and a single carrier are used for interference alignment. It is also shown that the proposed algorithms outperform the conventional algorithms when a single antenna and multiple subcarriers are used for interference alignment.

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A distributed interference alignment algorithm using min‐maxing strategy

El-Absi

El–Hadidy

Kaiser

2014

Trans. Emerging Tel. Tech.

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Interference alignment is a joint‐transmission strategy that significantly increases the sum rate of interference channels at high signal‐to‐noise ratios (SNRs). The recent iterative interference alignment approaches are incapable of guaranteeing the best sum‐rate performance with the increase of the SNR amongst different K‐user interference channels, especially at high SNR regime. In this paper, a new interference alignment algorithm is developed to improve the sum‐rate performance of K‐user multi‐input multi‐output (MIMO) and multi‐carrier interference channels by minimising the interference leakage and maximising the desired power concurrently, which is called by min‐maxing strategy. For a K‐user MIMO interference channel, we design transmit precoding matrices and receive decoding matrices through an efficient iterative algorithm based on min‐maxing strategy in a distributed way, in which each receiver maximises the desired signal power, whereas it preserves the minimum leakage interference as a constraint. This optimisation problem is reformulated and relaxed into a standard semidefinite programming form. The convergence of the proposed algorithm is proved as well. Furthermore, a simplified min‐maxing algorithm is proposed for rank‐deficient interference channels to achieve the targeted performance with less complexity. The numerical simulations show that the proposed algorithm proffers significant sum‐rate improvement in K‐user MIMO interference channels compared with the existing algorithms at high SNR regime. Moreover, the simplified algorithm matches the optimal performance in the systems of rank‐deficient channels. Finally, the developed min‐maxing algorithm has been extended to K‐user multi‐carrier interference channels, which outperform the previous approaches in terms of sum rate in several scenarios. Copyright © 2014 John Wiley & Sons, Ltd.

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Maximum Sum-Rate Interference Alignment Algorithms for MIMO Channels

Cited by 140 publications

References 11 publications

Limited Feedback Design for Interference Alignment on MIMO Interference Networks With Heterogeneous Path Loss and Spatial Correlations

Limited Feedback Design for Interference Alignment on MIMO Interference Networks With Heterogeneous Path Loss and Spatial Correlations

Iterative Algorithms for Interference Alignment in Cellular Network

A distributed interference alignment algorithm using min‐maxing strategy

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