Robust QoS-Constrained Optimization of Downlink Multiuser MISO Systems

Vučić, Nikola; Boche, Holger

doi:10.1109/tsp.2008.2008553

Cited by 177 publications

(134 citation statements)

References 33 publications

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“…Recently in [18], the optimal power allocation over fixed beamforming vectors was obtained in the presence of errors in CSI matrices. Most recently, efficient numerical solutions to find conservative robust beamforming for multiuser MISO systems with mean-square-error (MSE) and SINR constraints and different bounded CSI errors have been developed in [19], [20]. Moreover, SINR balancing optimizations have been proposed in [21] where the minimum achievable SINR is maximized, subject to a total transmit power constraint.…”

Section: Beamforming Optimizationmentioning

confidence: 99%

Exploiting Constructive Interference for Simultaneous Wireless Information and Power Transfer in Multiuser Downlink Systems

Timotheou

Zheng

Masouros

et al. 2016

IEEE J. Select. Areas Commun.

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Section: Beamforming Optimizationmentioning

confidence: 99%

Exploiting Constructive Interference for Simultaneous Wireless Information and Power Transfer in Multiuser Downlink Systems

Timotheou

Zheng

Masouros

et al. 2016

IEEE J. Select. Areas Commun.

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“…There are statistical approaches which assume the channel to be random but according to a certain statistic that is known. For example heuristics are developed for the multi-antenna downlink scenario from a signal processing point of view in [64,65]. These approaches are developed for conventional cellular systems, and it would be interesting for future work to analyze if these approaches can be extended to the case with unknown interference from other coexisting wireless networks.…”

Section: Discussionmentioning

confidence: 99%

Impact of Interference in Coexisting Wireless Networks with Applications to Arbitrarily Varying Bidirectional Broadcast Channels

Wyrembelski

Boche

2012

Entropy

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The paradigm shift from an exclusive allocation of frequency bands, one for each system, to a shared use of frequencies comes along with the need of new concepts since interference will be an ubiquitous phenomenon. In this paper, we use the concept of arbitrarily varying channels to model the impact of unknown interference caused by coexisting wireless systems which operate on the same frequencies. Within this framework, capacity can be zero if pre-specified encoders and decoders are used. This necessitates the use of more sophisticated coordination schemes where the choice of encoders and decoders is additionally coordinated based on common randomness. As an application we study the arbitrarily varying bidirectional broadcast channel and derive the capacity regions for different coordination strategies. This problem is motivated by decode-and-forward bidirectional or two-way relaying, where a relay establishes a bidirectional communication between two other nodes while sharing the resources with other coexisting wireless networks.Keywords: unknown interference; arbitrarily varying channel; bidirectional relaying; bidirectional broadcast channel; input and state constraints; capacity region; coexisting networks Entropy 2012, 14 NotationIn this paper we denote discrete random variables by non-italic capital letters and their corresponding realizations and ranges by lower case italic letters and script letters, e.g., X, x, and X , respectively; the notation X n stands for the sequence X 1 , X 2 , ..., X n of length n; N and R + denote the set of positive integers and non-negative real numbers; all logarithms, exponentials, and information quantities are taken to the basis 2; I(·; ·), H(·), and D(·∥·) are the mutual information, entropy, and Kullback-Leibler (information) divergence; E[·] and P{·} denote the expectation and probability; ⟨·, ·⟩ is the inner product and | · | + = max{·, 0}; P(·) is the set of all probability distributions and (·) c is the complement of a set; W ⊗n is the n-th memoryless extension of the stochastic matrix W ; lhs := rhs means the value of the right hand side (rhs) is assigned to the left hand side (lhs); lhs =: rhs is defined accordingly.

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“…The MSE is a well established measure for the type of problem we consider [15]- [17], [19]- [25], [27] and in general in the context of severely delay constrained applications that use short codes or even uncoded transmission, see for example [54]- [56]. Note also that short inner codes optimized with respect to MSE may be used as building blocks in communication systems that have an outer error-correcting code, in a similar spirit to the way space-time block codes based on signal-space diversity techniques can be used as inner codes in coded multiantenna transmissions.…”

Section: System Model and Problem Formulationsmentioning

confidence: 99%

The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems

Gharavol

Larsson

2013

IEEE Trans. Signal Process.

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We formally generalize the sign-definiteness lemma to the case of complex-valued matrices and multiple norm-bounded uncertainties. This lemma has found many applications in the study of the stability of control systems, and in the design and optimization of robust transceivers in communications. We then present three different novel applications of this lemma in the area of multi-user multiple-input multiple-output (MIMO) robust transceiver optimization. Specifically, the scenarios of interest are: (i) robust linear beamforming in an interfering adhoc network, (ii) robust design of a general relay network, including the two-way relay channel as a special case, and (iii) a half-duplex one-way relay system with multiple relays. For these networks, we formulate the design problems of minimizing the (sum) MSE of the symbol detection subject to different average power budget constraints. We show that these design problems are non-convex (with bilinear or trilinear constraints) and semiinfinite in multiple independent uncertainty matrix-valued variables. We propose a two-stage solution where in the first step the semi-infinite constraints are converted to linear matrix inequalities using the generalized signdefiniteness lemma, and in the second step, we use an iterative algorithm based on alternating convex search (ACS). Via simulations we evaluate the performance of the proposed scheme.

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Robust QoS-Constrained Optimization of Downlink Multiuser MISO Systems

Cited by 177 publications

References 33 publications

Exploiting Constructive Interference for Simultaneous Wireless Information and Power Transfer in Multiuser Downlink Systems

Exploiting Constructive Interference for Simultaneous Wireless Information and Power Transfer in Multiuser Downlink Systems

Impact of Interference in Coexisting Wireless Networks with Applications to Arbitrarily Varying Bidirectional Broadcast Channels

The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems

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