@article{liao_shi_yu_yi_wang_xiang_2019, title={An Alternating Direction Method of Multipliers Based Approach for PMU Data Recovery}, volume={10}, ISSN={["1949-3061"]}, DOI={10.1109/TSG.2018.2864176}, abstractNote={This paper presents a novel algorithm for recovering missing phasor measurement unit (PMU) data. Due to the low-rank property of PMU data, missing measurement recovery can be formulated as a low-rank matrix-completion problem. Based on maximum-margin matrix factorization, we propose an efficient algorithm, alternating direction method of multipliers (ADMM), for solving the matrix completion problem. Compared to existing approaches, the proposed ADMM based algorithm does not need to estimate the rank of the target data matrix and provides better performance in computation complexity. Since PMU data are transferred through insecure and delayed communications, we consider the case of measurements missing from all PMU channels in several sampling instants and provide the strategies of reshaping the matrix composed by the received PMU data for the recovery. Numerical results using real PMU measurements from State Grid Jiangsu Electric Power Company illustrate the effectiveness and efficiency of the proposed approaches.}, number={4}, journal={IEEE TRANSACTIONS ON SMART GRID}, author={Liao, Mang and Shi, Di and Yu, Zhe and Yi, Zhehan and Wang, Zhiwei and Xiang, Yingmeng}, year={2019}, month={Jul}, pages={4554–4565} }
 @inproceedings{liao_chakrabortty_2016, title={A Round-robin ADMM algorithm for identifying data-manipulators in power system estimation}, DOI={10.1109/acc.2016.7525462}, abstractNote={In this paper we develop an algorithm that can detect the identity of false data-injection attackers in distributed optimization loops for estimating oscillation modes in large power system models. The fundamental set-up for this distributed optimization is based on Alternating Direction Multiplier Method (ADMM). The power system is divided into multiple non-overlapping areas, each equipped with a local estimator. These local estimators use local sensor measurements to carry out a local regression algorithm for generating a local estimate for the characteristic polynomial for the system transfer function, and, thereafter, communicate this estimate to a central supervisor. The supervisor computes the average of all estimates, and broadcasts this average or consensus variable back to each local estimator to be used in the next round of regression. However, if one of the local estimators is compromised by a malicious attacker that may send corrupted values of its local estimate to the central supervisor, then it is difficult to detect the identity of this attacked estimator from the algorithm stated above. In this paper we propose an alternative algorithm where the central supervisor, instead of computing the average, employs a Round-Robin technique to generate the consensus variable, and show that by tracking the evolution of this consensus variable it is possible to identify which estimator is malicious. We analyze the convergence properties of this modified ADMM algorithm, and illustrate its effectiveness using simulation results.}, booktitle={2016 american control conference (acc)}, author={Liao, M. and Chakrabortty, Aranya}, year={2016}, pages={3539–3544} }
 @inproceedings{liao_chakrabortty_2016, title={Identifying covert data-manipulators in power system estimation loops}, DOI={10.1109/cdc.2016.7798441}, abstractNote={We develop a set of algorithms for identifying covert data manipulators in distributed optimization loops for estimating oscillation modes in power systems. The fundamental set-up for the optimization is based on Alternating Direction Multiplier Method (ADMM), implemented via message passing between a set of local estimators and a central coordinator. Some of these local estimators are assumed to be compromised by malicious attackers that send incorrect values of their local estimates to the coordinator. Even a small amount of such bias can easily destabilize the ADMM loop. In our first algorithm, we catch the identity of these attackers by employing the standard ADMM but adjusting the value of the penalty factor used in the update of the primal variable. We show that this adjustment can amplify the attack signature, and help in identification, especially when the attack magnitude is small. In our second algorithm, we employ a Round-Robbin variant of ADMM, and catch the manipulators by simply observing the evolution of the dual variable. We illustrate the results using simulations of the IEEE 68-bus power system model.}, booktitle={2016 ieee 55th conference on decision and control (cdc)}, author={Liao, M. and Chakrabortty, Aranya}, year={2016}, pages={1273–1278} }
 @article{liao_zhang_xiong_2016, title={The diversity of STF-coded MIMO-OFDM systems with a general correlation model}, ISSN={["1687-1499"]}, DOI={10.1186/s13638-016-0527-2}, abstractNote={Owing to insufficient antenna spaces, mobile scenarios, and multipaths in practice, transmission correlations in space, time, and frequency domains are inevitable in wireless communications. This paper studies the effect of general spatial, temporal, and frequency/path correlations on the performance of space-time-frequency (STF)-coded multiple-input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems over frequency-selective block-fading channels. Specifically, we first derive an upper bound on the maximum achievable diversity by Hadamard and tensor products and analyze the effect of general spatial, temporal, and frequency/path correlations on it using rank properties of block matrices. We then address STF code designs and give two examples, one traditional STF code and another quasi-SF code, to show that our upper bound on the maximum diversity is achievable. The decoding complexity is considered in the MIMO system with arbitrary correlated fading channels using the traditional STF code. We also identify the newly developed statistical channel models for MIMO LTE and 802.11n as special cases of our STF-coded MIMO-OFDM system by showing that our theoretical diversity results match those simulated from these statistical channel models. Finally, we show that our general diversity result recovers various maximum diversity gains for different special correlation scenarios that have appeared in the literature.}, journal={EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING}, author={Liao, Mang and Zhang, Youguang and Xiong, Zixiang}, year={2016}, month={Feb} }