A Convergent Version of the Max SINR Algorithm for the MIMO Interference Channel

Wilson, Craig; Veeravalli, Venugopal V.

doi:10.1109/twc.2013.041913.121289

Cited by 34 publications

(16 citation statements)

References 18 publications

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“…For example, [26] establishes its optimality within the class of linear beamforming algorithms at high SNR and [27] shows that it achieves better throughput than sum rate gradient algorithms at low-to-intermediate SNRs. Its convergence behaviour has also been analysed in [28]. However, most prior works are for the IC in a perfect CSI scenario.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of IA Techniques in the MIMO IBC With Imperfect CSI

Aquilina

Ratnarajah

2015

IEEE Trans. Commun.

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In this work we consider the multiple-input multiple-output (MIMO) interference broadcast channel (IBC) and analyse the performance of interference alignment (IA) under imperfect channel state information (CSI), where the variance of the CSI error depends on the signal-to-noise ratio (SNR). First, we derive an upper bound on asymptotic mean loss in sum rate compared to the perfect CSI case and then we quantify the achievable degrees of freedom (DoF) with imperfect CSI. Both sum rate loss and achievable DoF are found to be dependent on the number of cells in the system and the amount of users per cell, in addition to the CSI error parameters themselves. Results show that when error variance is inversely proportional to SNR, full DoF are achievable and the asymptotic sum rate loss is bounded by a derived value. Additionally if the CSI imperfection does not disappear for asymptotically high SNR, then the full DoF gain promised by IA cannot be achieved; we quantify this loss in relation to the CSI mismatch itself. The analytically derived bounds are validated via system simulation, with the cellular counterparts of the maximum signal-to-interference-plus-noise ratio (Max-SINR) and the minimum weighted leakage interference (Min-WLI) algorithms being the IA techniques of choice. Secondly, inspiredby the CSI mismatch model used to derive the bounds, we present a novel Max-SINR algorithm with stochastic CSI error knowledge (Max-SINR-SCEK) for the MIMO IBC. Simulations show that the proposed algorithm improves performance over the standard one under imperfect CSI conditions, without any additional computational costs.Index Terms-Degrees of freedom, imperfect CSI, interference alignment, MIMO interference broadcast channel.

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Section: Introductionmentioning

confidence: 99%

Performance Analysis of IA Techniques in the MIMO IBC With Imperfect CSI

Aquilina

Ratnarajah

2015

IEEE Trans. Commun.

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“…Therefore, power saving is not the primary concern of our proposed algorithm. By directly following the steps in [2], the standard interference function for our problem is given as [3,4]…”

Section: A Preliminariesmentioning

confidence: 99%

“…The proposed algorithm has two basic features. The power control law, the first feature, used in the algorithm is a straightforward extension of standard interference functions introduced in [2] as was also applied in [3,4]. The linear search, the second feature, used in the algorithm finds feasible SINR targets for the substreams, thus convergence of the algorithm is guaranteed.…”

Section: Introductionmentioning

confidence: 99%

Balancing Weighted Substreams in MIMO Interference Channels

Yetis

Zeng

Anand

et al. 2014

IEEE Wireless Commun. Lett.

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Substreams refer to the streams of each user in a system. Substream weighting, where the weights determine the prioritization order, can be important in multiple-input multiple-output interference channels. In this letter, a distributed algorithm is proposed for the problem of power minimization subject to weighted SINR constraint. The algorithm is based on two basic features, the well known distributed power control algorithm by Yates in 1995 and a simple linear search to find feasible SINR targets. The power control law used in the proposed algorithm is proven to linearly converge to a unique fixed-point.Comment: To be published at IEEE Wireless Commun. Letter

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“…For example, it has been established that Max-SINR is optimal within the class of linear beamformers at high SNRs [15], and it has been further shown that Max-SINR achieves better throughput than sum-rate gradient algorithms at low-to-intermediate SNRs [8]. Its convergence has been also addressed in [16].…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of MAX-SINR algorithm under CSI mismatch

Razavi

Ratnarajah

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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With interference alignment (IA), the achievable degrees of freedom (DoF) in wireless networks can be linearly scaled up with the number of users. However, to attain full DoF, the availability of perfect network channel state information (CSI) is mandatory, which impedes the practical deployment of IA since only partial network CSI may be accessible. In this paper, we investigate the effect of CSI mismatch on the performance of maximum signal-to-interference-plusnoise ratio (Max-SINR) algorithm. We show that while with perfect CSI, Max-SINR outperforms interference leakage minimization algorithms, with the presence of CSI mismatch, its comparative improvement becomes negligible. We then propose an adaptive Max-SINR which can notably improve the performance of original Max-SINR under CSI mismatch.Index Terms-CSI mismatch, interference alignment, K-user constant MIMO interference channels, Max-SINR.

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A Convergent Version of the Max SINR Algorithm for the MIMO Interference Channel

Cited by 34 publications

References 18 publications

Performance Analysis of IA Techniques in the MIMO IBC With Imperfect CSI

Performance Analysis of IA Techniques in the MIMO IBC With Imperfect CSI

Balancing Weighted Substreams in MIMO Interference Channels

Performance analysis of MAX-SINR algorithm under CSI mismatch

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