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Author

Lang Tong

Bio: Lang Tong is an academic researcher from Cornell University. The author has contributed to research in topics: Communication channel & Wireless sensor network. The author has an hindex of 73, co-authored 573 publications receiving 23870 citations. Previous affiliations of Lang Tong include West Virginia University & University of Notre Dame.


Papers
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Journal ArticleDOI
TL;DR: An analytical framework for opportunistic spectrum access based on the theory of partially observable Markov decision process (POMDP) is developed and cognitive MAC protocols that optimize the performance of secondary users while limiting the interference perceived by primary users are proposed.
Abstract: We propose decentralized cognitive MAC protocols that allow secondary users to independently search for spectrum opportunities without a central coordinator or a dedicated communication channel. Recognizing hardware and energy constraints, we assume that a secondary user may not be able to perform full-spectrum sensing or may not be willing to monitor the spectrum when it has no data to transmit. We develop an analytical framework for opportunistic spectrum access based on the theory of partially observable Markov decision process (POMDP). This decision-theoretic approach integrates the design of spectrum access protocols at the MAC layer with spectrum sensing at the physical layer and traffic statistics determined by the application layer of the primary network. It also allows easy incorporation of spectrum sensing error and constraint on the probability of colliding with the primary users. Under this POMDP framework, we propose cognitive MAC protocols that optimize the performance of secondary users while limiting the interference perceived by primary users. A suboptimal strategy with reduced complexity yet comparable performance is developed. Without additional control message exchange between the secondary transmitter and receiver, the proposed decentralized protocols ensure synchronous hopping in the spectrum between the transmitter and the receiver in the presence of collisions and spectrum sensing errors

1,709 citations

Journal ArticleDOI
TL;DR: Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel, which may achieve equalization with fewer symbols than most techniques based only on higher-order statistics.
Abstract: A new blind channel identification and equalization method is proposed that exploits the cyclostationarity of oversampled communication signals to achieve identification and equalization of possibly nonminimum phase (multipath) channels without using training signals. Unlike most adaptive blind equalization methods for which the convergence properties are often problematic, the channel estimation algorithm proposed here is asymptotically ex-set. Moreover, since it is based on second-order statistics, the new approach may achieve equalization with fewer symbols than most techniques based only on higher-order statistics. Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel. >

1,123 citations

Journal ArticleDOI
TL;DR: A new blind identification algorithm based solely on the system outputs is proposed and necessary and sufficient identifiability conditions in terms of the multichannel systems and the deterministic input signal are presented.
Abstract: Conventional blind channel identification algorithms are based on channel outputs and knowledge of the probabilistic model of channel input. In some practical applications, however, the input statistical model may not be known, or there may not be sufficient data to obtain accurate enough estimates of certain statistics. In this paper, we consider the system input to be an unknown deterministic signal and study the problem of blind identification of multichannel FIR systems without requiring the knowledge of the input statistical model. A new blind identification algorithm based solely on the system outputs is proposed. Necessary and sufficient identifiability conditions in terms of the multichannel systems and the deterministic input signal are also presented.

830 citations

Journal ArticleDOI
TL;DR: Malicious attacks against power systems are investigated, in which an adversary controls a set of meters and is able to alter the measurements from those meters, and an optimal attack based on minimum energy leakage is proposed.
Abstract: Malicious attacks against power systems are investigated, in which an adversary controls a set of meters and is able to alter the measurements from those meters. Two regimes of attacks are considered. The strong attack regime is where the adversary attacks a sufficient number of meters so that the network state becomes unobservable by the control center. For attacks in this regime, the smallest set of attacked meters capable of causing network unobservability is characterized using a graph theoretic approach. By casting the problem as one of minimizing a supermodular graph functional, the problem of identifying the smallest set of vulnerable meters is shown to have polynomial complexity. For the weak attack regime where the adversary controls only a small number of meters, the problem is examined from a decision theoretic perspective for both the control center and the adversary. For the control center, a generalized likelihood ratio detector is proposed that incorporates historical data. For the adversary, the trade-off between maximizing estimation error at the control center and minimizing detection probability of the launched attack is examined. An optimal attack based on minimum energy leakage is proposed.

770 citations

Journal ArticleDOI
TL;DR: In this article, a mathematical structure from which the acceptable indeterminacy is represented by an equivalence relation is formulated, and two identifiable cases are shown along with blind identification algorithms, FOBI (fourth-order blind identification), EFOBI (extended FOBI), and AMUSE algorithm.
Abstract: Blind identification of source signals is studied from both theoretical and algorithmic aspects. A mathematical structure is formulated from which the acceptable indeterminacy is represented by an equivalence relation. The concept of identifiability is then defined. Two identifiable cases are shown along with blind identification algorithms. The performance of FOBI (fourth-order blind identification), EFOBI (extended FOBI), and AMUSE algorithms is evaluated by some heuristic arguments and simulation results. It is shown that EFOBI outperforms the FOBI algorithm, and the AMUSE algorithm performs better than EFOBI in the case of nonwhite source signals. AMUSE is applied to a speech extraction problem and shown to have promising results. >

660 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Book
01 Jan 2005

9,038 citations

Journal ArticleDOI
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).

8,522 citations

Book
16 Mar 2001

7,058 citations

Journal ArticleDOI
TL;DR: The novel functionalities and current research challenges of the xG networks are explained in detail, and a brief overview of the cognitive radio technology is provided and the xg network architecture is introduced.

6,608 citations