Optimal linear precoding and postcoding for MIMO multi-sensor noisy observation problem

Liu, Yang; Li, Tiffany Jing; Lu, Xuanxuan; Yuen, Chau

doi:10.1109/icc.2014.6884213

Cited by 9 publications

(7 citation statements)

References 8 publications

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“…In the special case of K = J i = 1 (scalar source and scalar observation), μ i and f i can be obtained fully analytically without the need for numerical searches, and the eigenvalue decomposition is also unnecessary; Solving (P2 i ) therefore becomes extremely efficient. The details of the scalar case can be found in [11] 2 . In the general vector-source case, μ i can be numerically solved with high efficiency by a bisection search or by Newton's root finding method (e.g.…”

Section: Further Decoupling Of (P2 ) and Closed-form Solutionmentioning

confidence: 99%

“…Reference[11] solved an "approximated scalar-source version of problem (P2 i ), where a specific affine term of f i in the objective of (P2 i ) was approximated by its latest value. The technique of approximation is also discussed in Subsection 4.3 of this paper.…”

mentioning

confidence: 99%

“…The technique of approximation is also discussed in Subsection 4.3 of this paper. Additionally, a similar line of reasoning developed in[11] can be applied to obtain the exact scalar-form of (P2 i ).…”

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confidence: 99%

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Joint Transceiver Design for Linear MMSE Data Fusion in Coherent MAC Wireless Sensor Networks

Liu

2017

Information Fusion

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This paper considers the design of minimal mean square error (MMSE) transceivers in a wireless sensor network. The problem is nonconvex and challenging, and previous results (with partial solutions and/or with convergence unproved) left much to be desired. Here we propose several approaches-2 block coordinate descent (BCD), essentially cyclic multi-block method and its variants and distributive method to solve this problem. The proposed 2-BCD approach formulates the subproblem of joint beamformer optimization as a general second-order cone programming problem, which lends itself to standard numerical solvers and which requires no extra assumptions like previous works do. The proposed essentially cyclic multi-block approach further decomposes the joint beamformer design subproblem into multiple blocks, and rigorously solves each with semi-closed-form solution. The distributive algorithm optimizes transmitters in a decentralized manner and has never been considered in existing literature. The distributive algorithm has time complexity independent of number of sensors and is especially suitable for large-scale networks. All the previous BCD-based approaches left some singularity issue unattended as well as the convergence property unaddressed, our proposals are the first to provide a complete and provably-converging analytical solution. Extensive analysis and simulations demonstrate the merits of the novel approaches relative to existing alternatives.

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Section: Further Decoupling Of (P2 ) and Closed-form Solutionmentioning

confidence: 99%

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confidence: 99%

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Joint Transceiver Design for Linear MMSE Data Fusion in Coherent MAC Wireless Sensor Networks

Liu

2017

Information Fusion

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“…[5] studies solutions to several special but also rather meaningful cases including scalar channels, fading but noiseless channels and nonfading but noisy channels. [6] focuses on the scalar target source with nonscalar fading and noisy channels and obtains an approximate BCD algorithm with fully closed form solution for each step. The work [7], [8] develop variant BCD algorithms to tackle the most general case proposed in [5], with convergence and closed form solutions being examined in [8].…”

Section: Introductionmentioning

confidence: 99%

Transceiver Design for Clustered Wireless Sensor Networks --- Towards SNR Maximization

Liu,

Li,

2015

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This paper investigates the transceiver design problem in a noisy-sensing noisy-transmission multi-input multioutput (MIMO) wireless sensor network. Consider a clusterbased network, where multiple sensors scattering across several clusters will first send their noisy observations to their respective cluster-heads (CH), who will then forward the data to one common fusion center (FC). The cluster-heads and the fusion center collectively form a coherent-sum multiple access channel (MAC) that is affected by fading and additive noise. Our goal is to jointly design the linear transceivers at the CHs and the FC to maximize the signal-to-noise ratio (SNR) of the recovered signal. We develop three iterative block coordinated ascent (BCA) algorithms: 2-block BCA based on semidefinite relaxation (SDR) and rank reduction via randomization or solving linear equations, 2-block BCA based on iterative second-order cone programming (SOCP), and multi-block BCA that lends itself to efficient closedform solutions in specific but important scenarios. We show that all of these methods optimize SNR very well but each has different efficiency characteristics that are tailored for different network setups. Convergence analysis is carried out and extensive numerical results are presented to confirm our findings.

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“…Part of this work appeared in our conference paper[6], which discussed the cyclic multi-block approach in the special case of scalar source.…”

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MIMO Beamforming Design towards Maximizing Mutual Information in Wireless Sensor Network

Liu,

Li,

2014

Preprint

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This paper considers joint beamformer design towards maximizing the mutual information in a coherent wireless sensor network with noisy observation and multiple antennae. Leveraging the weighted minimum mean square error and block coordinate ascent (BCA) framework, we propose two new and efficient methods: batch-mode BCA and cyclic multi-block BCA. The existing batch-mode approaches require stringent conditions such as diagonal channel matrices and positive definite secondorder matrices, and are therefore inapplicable to our problem. Our match-mode BCA overcomes the previous limitations via a general second-order cone programming formation, and exhibits a strong convergence property which we have rigorously proven. The existing multi-block approaches rely on numerical solvers to handle the subproblems and some render good performance only at high signal-to-noise ratios. Exploiting the convexity of the trustregion subproblem for the convex case, our multi-block BCA significantly reduces the complexity and enhances the previous results by providing an analytical expression for the energypreserving optimal solution. Analysis and simulations confirm the advantages of the proposed methods.

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Optimal linear precoding and postcoding for MIMO multi-sensor noisy observation problem

Cited by 9 publications

References 8 publications

Joint Transceiver Design for Linear MMSE Data Fusion in Coherent MAC Wireless Sensor Networks

Joint Transceiver Design for Linear MMSE Data Fusion in Coherent MAC Wireless Sensor Networks

Transceiver Design for Clustered Wireless Sensor Networks --- Towards SNR Maximization

MIMO Beamforming Design towards Maximizing Mutual Information in Wireless Sensor Network

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