Robust Linear Transceiver Design in MIMO Ad Hoc Cognitive Radio Networks with Imperfect Channel State Information

Gharavol, Ebrahim A.; Liang, Ying-Chang; Mouthaan, Koen

doi:10.1109/twc.2011.030911.100337

Cited by 38 publications

(36 citation statements)

References 15 publications

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“…This contribution generalizes the method employed in [25] in which the authors assumed that each MSE constraint is only affected by one single uncertainty source.…”

Section: B Contributionsmentioning

confidence: 97%

“…For example in [15]- [19] the transmitters for the MISO broadcast channel (BC) were optimized using different design criteria including MSE, sum-MSE and signal-to-interference-plus-noise ratio (SINR) subject to different power constraints in different setups including CR networks. There are also many papers that robustly design similar systems with multiple antennas at both ends (i.e., the MIMO case) [20]- [25] in single-user or multi-user networks. All these problems are such that each semi-infinite constraint includes only one uncertainty variable, and they mostly resort to the complex-valued version of the sign-definiteness lemma published in [26] to resolve the semi-infiniteness of the constraints.…”

Section: A Related Recent Workmentioning

confidence: 99%

“…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%

See 2 more Smart Citations

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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“…This contribution generalizes the method employed in [25] in which the authors assumed that each MSE constraint is only affected by one single uncertainty source.…”

Section: B Contributionsmentioning

confidence: 97%

Section: A Related Recent Workmentioning

confidence: 99%

Section: System Model and Problem Formulationsmentioning

confidence: 99%

See 1 more Smart Citation

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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“…Usually, this problem is tackled by either worst-case optimization [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] or stochastic optimization [24,28]. In worst-case optimization (or maximin optimization), the uncertain parameters can take some given set of possible values, but without any known distribution.…”

Section: Introductionmentioning

confidence: 99%

“…Then the optimization variables are designed in such a way that an objective value is maximized while guaranteeing the feasibility of the constraints over the given set of possible values of the parameters. This method has been applied to design the robust beamforming vectors for underlay CRNs in [20][21][22][23][24][25][26], where the channel errors are either norm bounded or bounded by ellipsoids. With the exception of [24] and [26], most of the abovementioned work consider a CRN where a single secondary transmitter (TX) co-exists with a primary network.…”

Section: Introductionmentioning

confidence: 99%

A robust beamformer design for underlay cognitive radio networks using worst case optimization

Wijewardhana

Codreanu

2014

J Wireless Com Network

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We propose a robust beamforming design for underlay cognitive radio networks where multiple secondary transmitters communicate with corresponding secondary receivers and coexist with a primary network. We consider a scenario where all transmitters have multiple antennas and all primary and secondary receivers are equipped with a single antenna. The main focus is to design the optimal transmit beamforming vectors for secondary transmitters that maximize the minimum of the received signal-to-interference-plus-noise ratios of the cognitive users. The interference powers to the primary receivers are kept below a threshold to guarantee that the performance of the primary network does not degrade due to the secondary network. Imperfect channel state information (CSI) in all relevant channels are considered, and a bounded ellipsoidal uncertainty model is used to model the CSI errors. We recast the problem in the form of semidefinite program and an iterative algorithm based on the bisection method is proposed to achieve the optimal solution. Further, we propose upper and lower bounds for the optimal value of the considered problem, which provides better initialization for the algorithm. Numerical simulations are conducted to show the effectiveness of the proposed method against the non-robust design.

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References

2012

Cognitive Radio Communications and Networking

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Robust Linear Transceiver Design in MIMO Ad Hoc Cognitive Radio Networks with Imperfect Channel State Information

Cited by 38 publications

References 15 publications

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

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

A robust beamformer design for underlay cognitive radio networks using worst case optimization

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