Meng-Che Chang

Staff Member at Mediatek

Accepted

1. S.-Y. Wang, M.-C. Chang, and M. R. Bloch, “Covert Joint Communication and Sensing Under Variational Distance Constraint.” accepted to 58th Annual Conference on Information Sciences and Systems, Jan. 2024.

   @misc{Wang2024Covert, author = {Wang, Shi-Yuan and Chang, Meng-Che and Bloch, Matthieu R.}, howpublished = {accepted to \emph{58th Annual Conference on Information Sciences and Systems}}, month = jan, title = {Covert Joint Communication and Sensing Under Variational Distance Constraint}, year = {2024}, groups = {NSF1910859, NSF2148400} }

Articles

1. M.-C. Chang, S.-Y. Wang, T. Erdoğan, and M. R. Bloch, “Rate and Detection-Error Exponent Tradeoff for Joint Communication and Sensing of Fixed Channel States,” IEEE Journal on Selected Areas in Information Theory, vol. 4, pp. 245–259, May 2023.

   We study the information-theoretic limits of joint communication and sensing when the sensing task is modeled as the estimation of a discrete channel state fixed during the transmission of an entire codeword. This setting captures scenarios in which the time scale over which sensing happens is significantly slower than the time scale over which symbol transmission occurs. The tradeoff between communication and sensing then takes the form of a tradeoff region between the rate of reliable communication and the state detection-error exponent. We investigate such tradeoffs for both mono-static and bi-static scenarios, in which the sensing task is performed at the transmitter or receiver, respectively. In the mono-static case, we develop an exact characterization of the tradeoff in open-loop, when the sensing is not used to assist the communication. We also show the strict improvement brought by a closed-loop operation, in which the sensing informs the communication. In the bi-static case, we develop an achievable tradeoff region that highlights the fundamentally different nature of the bi-static scenario. Specifically, the rate of communication plays a key role in the characterization of the tradeoff and we show how joint strategies, which simultaneously estimate message and state, outperform successive strategies, which only estimate the state after decoding the transmitted message.

   @article{Chang2022Ratea, author = {Chang, Meng-Che and Wang, Shi-Yuan and Erdo\u{g}an, Tuna and Bloch, Matthieu R.}, journal = {IEEE Journal on Selected Areas in Information Theory}, title = {Rate and Detection-Error Exponent Tradeoff for Joint Communication and Sensing of Fixed Channel States}, year = {2023}, month = may, pages = {245-259}, volume = {4}, doi = {10.1109/JSAIT.2023.3275877}, eprint = {2210.07963}, groups = {NSF2148400, NSF1955401}, howpublished = {accepted to \emph{IEEE Journal on Selected Areas in Information Theory}} }

2. M.-C. Chang and M. R. Bloch, “Evasive Active Hypothesis Testing,” IEEE Journal on Selected Areas in Information Theory, vol. 2, no. 2, pp. 735–746, Jun. 2021.

   We consider a situation in which a decision maker takes sequential and adaptive sensing actions to collect measurements and estimate an unknown parameter taking finitely many values, in the presence of an adversary who also collects measurements whenever a sensing action is taken. This situation can be viewed as an abstraction in which to analyze the mitigation of information leakage inherent to control actions in systems with feedback, such as cyber-physical systems. Specifically, we formulate an evasive active hypothesis problem in which the objective is for the decision maker to control the risk of its test while minimizing the detection ability of the adversary, measured in terms of the asymptotic error exponent ratio between the adversary and the decision maker. We develop bounds on the exponent ratio that offer insight into optimal strategies that the decision maker can deploy to evade the adversary’s detection. We illustrate the results with a numerical example corresponding to the detection of a wireless transmission.

   @article{Chang2020a, author = {Chang, Meng-Che and Bloch, Matthieu R.}, journal = {IEEE Journal on Selected Areas in Information Theory}, title = {Evasive Active Hypothesis Testing}, year = {2021}, month = jun, number = {2}, pages = {735-746}, volume = {2}, doi = {10.1109/JSAIT.2021.3074156}, file = {:2021-Chang-IEEEJSAIT-Evasive Active Hypothesis Testing.pdf:PDF}, groups = {NSF1955401}, howpublished = {accepted to \emph{IEEE Journal of Selected Areas in Information Theory}} }

Conference proceedings

1. M.-C. Chang and M. R. Bloch, “Distributed Stochastic Bandits with Corrupted and Defective Input Commands,” in Proc. of IEEE International Symposium on Information Theory, Taipei, Taiwan, Jun. 2023, pp. 1318–1323.

   We analyze a distributed stochastic bandit model in which an agent controls multiple independent stochastic bandit machines. At each time step, the agent selects several machines for parallel exploitation but the arm pulled by each machine may differ from the command received either randomly (defective command) or adversarially (corrupted command). Machines that faithfully execute commands are called honest. We study situations in which the number of honest machines is either known or unknown and define appropriate notions of regret. With at least one honest machine and a known number of honest bandits, we provide a simple algorithm that achieves \tilde O\left( n^1/2 \right) regrets when commands are corrupted. Lower bounds on regret established by drawing connections to the problem of "low probability of detection," show the near optimality of the regret achieved by the algorithms.

   @inproceedings{Chang2023Distributed, author = {Chang, Meng-Che and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE International Symposium on Information Theory}, title = {Distributed Stochastic Bandits with Corrupted and Defective Input Commands}, year = {2023}, address = {Taipei, Taiwan}, month = jun, pages = {1318-1323}, doi = {10.1109/ISIT54713.2023.10206787}, file = {:2023-Chang-ISIT-Distributed Stochastic Bandits with Corrupted and Defective Input Commands.pdf:PDF}, groups = {NSF1955401}, howpublished = {accepted to \emph{2023 IEEE International Symposium on Information Theory}} }

2. M.-C. Chang, S.-Y. Wang, and M. R. Bloch, “Sequential Joint Communication and Sensing of Fixed Channel States,” in Proc. of IEEE Information Theory Workshop, Saint-Malo, France, Apr. 2023, pp. 462–467.

   We consider a communication model in which a transmitter attempts to communicate with a receiver over a state-dependent channel and simultaneously estimates the state using strictly causal noisy state observations. The state is assumed to remain constant over the duration of the transmission. We analyze the trade-off between the state-error exponent and the communication rate in the sequential setting, in which the transmitter determines what and how many symbols to transmit in an online manner.

   @inproceedings{Chang2023Sequential, author = {Chang, Meng-Che and Wang, Shi-Yuan and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE Information Theory Workshop}, title = {Sequential Joint Communication and Sensing of Fixed Channel States}, year = {2023}, address = {Saint-Malo, France}, month = apr, pages = {462--467}, doi = {10.1109/ITW55543.2023.10161688}, file = {:2023-Chang-ITW-Sequential Joint Communication and Sensing of Fixed Channel States.pdf:PDF}, groups = {NSF2148400}, howpublished = {accepted to \emph{IEEE Information Theory Workshop}} }

3. M.-C. Chang, S.-Y. Wang, and M. R. Bloch, “Controlled Sensing with Corrupted Commands,” in Proc. of 58th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, Sep. 2022.

   We consider a non-adaptive controlled sensing sce-nario in which the actions of the decision maker are corrupted by an adversary. The objective of the decision maker is to either detect the presence of the corruption or make a correct decision. Accordingly, the performance of a controlled sensing strategy is measured in terms of the error probability when there is no adversary, denoted PE,0 , and the error probability when an adversary is present, denoted PE,1 . Our main result is Stein-lemma like characterization of the optimal achievable error exponent of PE,0 subject to a constraint on PE,1 . We also illustrate the result with numerical examples.

   @inproceedings{Chang2022Controlled, author = {Chang, Meng-Che and Wang, Shi-Yuan and Bloch, Matthieu R.}, booktitle = {Proc. of 58th Annual Allerton Conference on Communication, Control, and Computing}, title = {Controlled Sensing with Corrupted Commands}, year = {2022}, address = {Monticello, IL}, month = sep, doi = {10.1109/Allerton49937.2022.9929364}, file = {:2022-Chang-Allerton-Controlled Sensing with Corrupted Commands.pdf:PDF}, groups = {NSF1955401, NSF1910859}, howpublished = {accepted to \emph{Allerton conference}} }

4. M.-C. Chang and M. R. Bloch, “Covert Best Arm Identification of Stochastic Bandits,” in Proc. of IEEE International Symposium on Information Theory, Helsinki, Finland, Jun. 2022, pp. 324–329.

   We study the covert best arm identification problem in which an agent tries to identify the best arm while escaping detection from an adversary. Specifically, the agent should identify the best arm of the bandit with accuracy higher than a predefined requirement as soon as possible and, simultaneously, the adversary’s observations induced by pulling effective arms should remain indistinguishable from the observations obtained when no effective arm is pulled. Our main result is the characterization of the exponent γ, which captures the asymptotic exponential decrease of the confidence level with the square-root of the averaged stopping time.

   @inproceedings{Chang2022Covert, author = {Chang, Meng-Che and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE International Symposium on Information Theory}, title = {Covert Best Arm Identification of Stochastic Bandits}, year = {2022}, address = {Helsinki, Finland}, month = jun, pages = {324-329}, doi = {10.1109/ISIT50566.2022.9834559}, file = {:2022-Chang-ISIT-Covert Best Arm Identification of Stochastic Bandits.pdf:PDF}, groups = {NSF1955401}, howpublished = {accepted to \emph{IEEE International Symposium on Information Theory}} }

5. M.-C. Chang, T. Erdoğan, S.-Y. Wang, and M. R. Bloch, “Rate and Detection Error-Exponent Tradeoffs of Joint Communication and Sensing,” in Proc. of IEEE International Symposium on Joint Communications & Sensing, Vienna, Austria, Mar. 2022, pp. 1–6.

   We consider a communication model in which a transmitter attempts to communicate with a receiver over a state-dependent channel and simultaneously estimate the state using strictly causal noisy state observations. Motivated by joint communication and sensing scenarios in which the physical phenomenon of interest for sensing evolves at a much slower rate than the rate of communication, the state is assumed to remain constant over the duration of the transmission. We derive a complete characterization of the optimal asymptotic trade-off between communication rate and detection-error exponent when coding strategies are open loop. We also show that closed-loop strategies result in strict improvements of the trade-offs.

   @inproceedings{Chang2022Rate, author = {Chang, Meng-Che and Erdo\u{g}an, Tuna and Wang, Shi-Yuan and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE International Symposium on Joint Communications \& Sensing}, title = {Rate and Detection Error-Exponent Tradeoffs of Joint Communication and Sensing}, year = {2022}, address = {Vienna, Austria}, month = mar, pages = {1--6}, doi = {10.1109/JCS54387.2022.9743498}, file = {:2022-Chang-ISJCS-Rate and Detection Error-Exponent Tradeoffs of Joint Communication and Sensing.pdf:PDF}, groups = {Joint communication and sensing, NSF1955401, NSF1910859}, howpublished = {accepted to the \emph{IEEE International Hybrid Symposium on Joint Communications \& Sensing}} }

6. M.-C. Chang and M. R. Bloch, “Covert Sequential Hypothesis Testing,” in Proc. of IEEE Information Theory Workshop, Oct. 2021, pp. 1–6.

   @inproceedings{Chang2021a, author = {Chang, Meng-Che and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE Information Theory Workshop}, title = {Covert Sequential Hypothesis Testing}, year = {2021}, month = oct, pages = {1-6}, doi = {10.1109/ITW48936.2021.9611391}, file = {:2021-Chang-ITW-Covert sequential hypothesis testing.pdf:PDF}, groups = {NSF1955401}, howpublished = {accepted to \emph{IEEE Information Theory Workshop}} }

7. M.-C. Chang and M. R. Bloch, “Covert Authentication Against a Myopic Adversary,” in Proc. of IEEE International Symposium on Information Theory, Jul. 2021, pp. 196–201.

   We consider the problem of authenticating communication over a Myopic Binary Adversarial Channel (MBAC) while maintaining covertness with respect to the myopic adversary. When the main channel between legitimate parties is degraded with respect to the adversary’s channel, we show the existence of an integrated scheme that simultaneously exploits secret keys to ensure covertness and authentication. The main technical challenge we address is showing that authentication may be ensured against myopic attacks when using the low-weight codewords mandated by covert communication.

   @inproceedings{Chang2021, author = {Chang, Meng-Che and Bloch, Matthieu R.}, booktitle = {Proc. of IEEE International Symposium on Information Theory}, title = {Covert Authentication Against a Myopic Adversary}, year = {2021}, month = jul, pages = {196-201}, doi = {10.1109/ISIT45174.2021.9518165}, file = {:2021-Chang-ISIT-Covert Authentication Against a Myopic Adversary.pdf:PDF}, groups = {NSF1955401}, howpublished = {accepted to \emph{IEEE International Symposium on Information Theory}} }

8. M.-C. Chang and M. Bloch, “Evasive Active Hypothesis Testing,” in Proc. of IEEE International Symposium on Information Theory, Los Angeles, CA, Jun. 2020, pp. 1248–1253.

   We consider an active hypothesis testing scenario in which an adversary obtains observations while legitimate parties engage in a sequential adaptive control policy to estimate an unknown parameter. The objective is for the legitimate parties to evade the adversary by controlling the risk of their test while minimizing the detection ability of the adversary, measured in terms of its error exponent. We develop bounds on the adversary’s error exponent that offer insight into how legitimate adversaries can best evade the adversary’s detection. We illustrate the results in a wireless transmission detection example.

   @inproceedings{Chang2020, author = {Chang, Meng-Che and Bloch, Matthieu}, booktitle = {Proc. of IEEE International Symposium on Information Theory}, title = {Evasive Active Hypothesis Testing}, year = {2020}, address = {Los Angeles, CA}, month = jun, pages = {1248-1253}, doi = {10.1109/ISIT44484.2020.9174021}, howpublished = {accepted to \emph{IEEE International Symposium on Information Theory}} }