Weighted sum rate maximization in the MIMO Interference Channel

Negro, Francesco; Shenoy, Shakti Prasad; Ghauri, Irfan; Slock, Dirk

doi:10.1109/pimrc.2010.5671658

Cited by 21 publications

(18 citation statements)

References 8 publications

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“…This same method was directly applied to multicell MIMO systems in [7], [27], but it was not until [12] that a rigorous connection to the multicell weighted sum rate problem was presented. An earlier work is [6], where the weighted MMSE optimization problem was solved using the same technique, but without explicitly providing the rigorous connection to the weighted sum rate problem.…”

Section: A Related Workmentioning

confidence: 99%

Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems

Brandt

Bengtsson

2016

IEEE Trans. Veh. Technol.

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PostprintThis is the accepted version of a paper published in IEEE Transactions on Vehicular Technology. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.Citation for the original published paper (version of record):Brandt, R., Bengtsson, M. (2015) Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems. Abstract-Several distributed coordinated precoding methods exist in the downlink multicell MIMO literature, many of which assume perfect knowledge of received signal covariance and local effective channels. In this work, we let the notion of channel state information (CSI) encompass this knowledge of covariances and effective channels. We analyze what local CSI is required in the WMMSE algorithm for distributed coordinated precoding, and study how this required CSI can be obtained in a distributed fashion. Based on pilot-assisted channel estimation, we propose three CSI acquisition methods with different tradeoffs between feedback and signaling, backhaul use, and computational complexity. One of the proposed methods is fully distributed, meaning that it only depends on over-the-air signaling but requires no backhaul, and results in a fully distributed joint system when coupled with the WMMSE algorithm. Naïvely applying the WMMSE algorithm together with the fully distributed CSI acquisition results in catastrophic performance however, and therefore we propose a robustified WMMSE algorithm based on the well known diagonal loading framework. By enforcing properties of the WMMSE solutions with perfect CSI onto the problem with imperfect CSI, the resulting diagonally loaded spatial filters are shown to perform significantly better than the naïve filters. The proposed robust and distributed system is evaluated using numerical simulations, and shown to perform well compared with benchmarks. Under centralized CSI acquisition, the proposed algorithm performs on par with other existing centralized robust WMMSE algorithms. When evaluated in a large scale fading environment, the performance of the proposed system is promising. IEEE Transactions on Vehicular Technology

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Section: A Related Workmentioning

confidence: 99%

Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems

Brandt

Bengtsson

2016

IEEE Trans. Veh. Technol.

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“…Moreover, they do not account for QoS guarantees in their optimization. In [9] and [10], the authors consider maximizing the weighted sum rate objective function subject to power thresholds. This problem is however non-convex (similar to our original problem without approximation) and the authors devise a joint optimization strategy to optimize the linear beam vectors across coordinated cells and independently-modulated resource slots that address the frequency diversity in OFDMA systems.…”

Section: Introductionmentioning

confidence: 99%

Mitigating macro-cell outage in LTE-Advanced deployments

Sivaraj

Broustis

Shankaranarayanan

et al. 2015

2015 IEEE Conference on Computer Communications (INFOCOM)

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Abstract-LTE network service reliability is highly dependent on the wireless coverage that is provided by cell towers (eNB). Therefore, the network operator's response to outage scenarios needs to be fast and efficient, in order to minimize any degradation in the Quality of Service (QoS). In this paper, we propose an outage mitigation framework for LTE-Advanced (LTE-A) wireless networks. Our framework exploits the inherent design features of LTE-A; it performs a dual optimization of the transmission power and beamforming weight parameters at each neighbor cell sector of the outage eNBs, while taking into account both the channel characteristics and residual eNB resources, after serving its current traffic load. Assuming statistical Channel State Information about the users at the eNBs, we show that this problem is theoretically NP-hard; thus we relax it as a convex optimization problem and solve for the optimal points using an iterative algorithm. Contrary to previously-proposed power control studies, our framework is specifically designed to alleviate the effects of sudden LTE-A eNB outages, where a large number of mobile users need to be efficiently offloaded to nearby towers. We present the detailed analytical design of our framework, and we assess its efficacy via extensive NS-3 simulations on an LTE-A topology. Our simulations demonstrate that our framework provides adequate coverage and QoS across all examined outage scenarios.

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“…Examples are the MIMO broadcast channel with linear precoding [4] and the MIMO interference channel [5], where one is interested in the achievable rate region or the optimized weighted sum rate [6]. The maximization of secrecy rates or secret key rates in MIMO systems also leads to nonconvex programming problems [7].…”

Section: Introductionmentioning

confidence: 99%

“…Let be a random variable with values in and assume to be defined on a probability space with probability measure . We say that has a uniform distribution on if (6) holds and that has a uniform distribution on if (7) holds for all . In (6) denotes the -dimensional volume of an arbitrary set and in (7) denotes the -dimensional volume of an arbitrary set .…”

Section: Introductionmentioning

confidence: 99%

Sampling Uniformly From the Set of Positive Definite Matrices With Trace Constraint

Mittelbach

Matthiesen

Jorswieck

2012

IEEE Trans. Signal Process.

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We derive a parameterization of positive definite matrices using the Cholesky decomposition in combination with hyperspherical coordinates. Based on the parameterization we develop a simple and efficient method to randomly generate positive definite matrices with constant or bounded trace according to a uniform distribution. Further, we present an efficient implementation using the inversion method and either rejection sampling or transforming a beta distribution. The matrix parameterization might be of independent interest, whereas the random sampling algorithm finds applications in Monte Carlo simulations, testing of algorithms, and performance studies. With the help of an abstract example we describe how the sampling method can be used to approximate the optimum in a difficult, e.g., nonconvex, optimization problem for which no solution or efficient global optimization algorithm is known. In this paper we consider real as well as complex matrices.Index Terms-Matrix parameterization, random covariance matrix, random matrix generation, random positive definite matrix, uniform distribution.

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Weighted sum rate maximization in the MIMO Interference Channel

Cited by 21 publications

References 8 publications

Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems

Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems

Mitigating macro-cell outage in LTE-Advanced deployments

Sampling Uniformly From the Set of Positive Definite Matrices With Trace Constraint

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