A Tractable Method for Chance-Constrained Power Control in Downlink Multiuser MISO Systems With Channel Uncertainty

Vučić, Nikola; Boche, Holger

doi:10.1109/lsp.2009.2016007

Cited by 40 publications

(26 citation statements)

References 10 publications

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“…Substituting (27) into leads to (28) Define and rearrange the terms, and we can obtain the following dual problem: (29) where is an real matrix, and the -th column of f and g are defined in (21) and after (23). (19) The problem (29) is a non-negative least-squares problem.…”

Section: The Dual Problemmentioning

confidence: 99%

Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization

Masouros

Zheng

2015

IEEE Trans. Signal Process.

317

482

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We propose a data-aided transmit beamforming scheme for the multi-user multiple-input-single-output (MISO) downlink channel. While conventional beamforming schemes aim at the minimization of the transmit power subject to suppressing interference to guarantee quality of service (QoS) constraints, here we use the knowledge of both data and channel state information (CSI) at the transmitter to exploit, rather than suppress, constructive interference. More specifically, we design a new precoding scheme for the MISO downlink that minimizes the transmit power for generic phase shift keying (PSK) modulated signals. The proposed precoder reduces the transmit power compared to conventional schemes, by adapting the QoS constraints to accommodate constructive interference as a source of useful signal power. By exploiting the power of constructively interfering symbols, the proposed scheme achieves the required QoS at lower transmit power. We extend this concept to the signal to interference plus noise ratio (SINR) balancing problem, where higher SINR values compared to the conventional SINR balancing optimization are achieved for given transmit power budgets. In addition, we derive equivalent virtual multicast formulations for both optimizations, both of which provide insights of the optimal solution and facilitate the design of a more efficient solver. Finally, we propose a robust beamforming technique to deal with imperfect CSI, that also reduces the transmit power over conventional techniques, while guaranteeing the required QoS. Our simulation and analysis show significant power savings for small scale MISO downlink channels with the proposed data-aided optimization compared to conventional beamforming optimization.

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Section: The Dual Problemmentioning

confidence: 99%

Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization

Masouros

Zheng

2015

IEEE Trans. Signal Process.

317

482

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“…For further details, kindly refer to the Appendix VII. Certain examples, where the interference function framework has been utilized are as follows: beamforming [11]- [13], CDMA [14], base station assignment, robust design [15], [16], transmitter optimization [17], [18] and characterization of the Pareto boundary [19]. The framework can be used to combine power control [20] and adaptive receiver strategies.…”

Section: B Interference Functionsmentioning

confidence: 99%

Universal pricing mechanism for utility maximization for interference coupled systems

Boche

Naik

Alpcan

2010

2010 European Wireless Conference (EW)

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Abstract-This paper investigates pricing mechanisms for utility maximization in interference coupled systems. An axiomatic framework of interference functions similar to the one proposed by Yates is utilized to capture interference coupling in wireless systems. Pricing mechanisms are used as a design tool to shift the solution outcome of a utility maximization problem to a desired point in the region. The paper explores the restrictions required on the class of utility functions and the restrictions on the class of interference functions such that a pricing mechanism can always guarantee the designer the ability of being able to shift the solution outcome to any desired point in the region, i.e. it is a universal pricing mechanism.

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“…In this study, the scenario is formulated as an optimization problem and conservative approaches that yield deterministic convex approximation for randomly perturbed second order cone constraints are used to guarantee the satisfaction of the probabilistic constraints. In a similar broadcast scenario, [19] studies power allocation strategies to satisfy QoS targets at user terminals in the presence of channel estimation error with Gaussian distribution. The authors in [19] use Vysochanskii-Petunin inequality in combination with the theory of interference functions to find conservative solutions to the problem.…”

mentioning

confidence: 99%

“…In a similar broadcast scenario, [19] studies power allocation strategies to satisfy QoS targets at user terminals in the presence of channel estimation error with Gaussian distribution. The authors in [19] use Vysochanskii-Petunin inequality in combination with the theory of interference functions to find conservative solutions to the problem. The majority of available algorithms mainly rely on deriving analytical convex upper bounds for the probabilistic constrains and only find a feasible worstcase solution without any optimality guarantee.…”

mentioning

confidence: 99%

“…In contrast to the methods that approximate the probabilistic constraints with their convex upperbounds and effectively find a feasible worst-case solution without any optimality guarantee (e.g., [15], [19]), the proposed approach directly characterizes the statistical behavior of the random error matrix with no approximation and obtains the optimal solutions. The optimality of the proposed approach is evidenced by a comparative inspection of the simulation results of our scheme and the scheme in [15].…”

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confidence: 99%

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Chance Constrained Robust Downlink Beamforming in Multicell Networks

Nasseri

Nakhai

Lê

2016

IEEE Trans. on Mobile Comput.

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Abstract-We introduce a downlink robust optimization approach that minimizes a combination of total transmit power by a multiple antenna base station (BS) within a cell and the resulting aggregate inter-cell interference (ICI) power on the users of the other cells. This optimization is constrained to assure that a set of signal-to-interference-plus-noise ratio (SINR) targets are met at user terminals with certain outage probabilities. The outages are due to the uncertainties that naturally emerge in the estimation of channel covariance matrices between a BS and its intra-cell local users as well as the other users of the other cells. We model these uncertainties using random matrices, analyze their statistical behaviour and formulate a tractable probabilistic approach to the design of optimal robust downlink beamforming vectors. The proposed approach reformulates the original intractable non-convex problem in a semidefinite programming (SDP) form with linear matrix inequality (LMI) constraints. The resulting SDP formulation is convex and numerically tractable under the standard rank relaxation. We compare the proposed chance-constrained approach against two different robust design schemes as well as the worst-case robustness. The simulation results confirm better power efficiency and higher resilience against channel uncertainties of the proposed approach in realistic scenarios.

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A Tractable Method for Chance-Constrained Power Control in Downlink Multiuser MISO Systems With Channel Uncertainty

Cited by 40 publications

References 10 publications

Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization

Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization

Universal pricing mechanism for utility maximization for interference coupled systems

Chance Constrained Robust Downlink Beamforming in Multicell Networks

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