Research Areas

  1. Low-Delay Error Correction Codes
  2. Smart Meter Privacy in Electric Grids
  3. Source Coding for Real-Time Streaming
  4. Secure MIMO Communication
  5. Physical-Layer Secret-Key Generation
  6. Broadcasting over Packet Erasure Channels
  7. Distributed Interference Cancellation

Below we list a few topics that the research lab is actively pursuing with the relevant references.

 MiDAS Codes for Real-Time Streaming Communications
Applications such as live-video streaming, web conferencing, and cloud computing are expected to see a dramatic growth over the next few years.  Unlike classical systems, these applications require strict end-to-end delay constraints, real-time processing, and in-order delivery of data packets. Traditional error correction techniques are not designed for such constraints, and can lead to severe playback interruptions due to bursty packet losses over wireless channels. We illustrate such a streaming application in the figure below.


Streaming Server
 

Classical information theory does not account for the streaming nature of applications. It provides little design guidelines. For example:
We have developed a new class of error correction codes  --- MiDAS Codes that have several novel properties:

References
  1. A. Badr, P. Patil, A. Khisti, W. Tan and J. Apostolopoulos Layered Construction for Low-Delay Streaming Codes  IEEE Trans. Inf. Theory, Dec 2016


Smart Meter Privacy in Electric Grids

Smart meters report real-time information of user's energy usage to utility providers. This can leak sensitiv information about the devices being used. For example see the figure below.



Streaming Server
 

We consider the use of a rechargeable battery at user's home to mask information leaked to the utility providers. By determine the optimal charging and discharging policies of the rechargeable battery to mimimize information leakage.


Source Coding for Real-Time Streaming

Practical techniques for compression of streaming sources must satisfy two key requirements:

As one would expect these requirements are conflicting in nature. At one extreme, methods such as predictive coding achieve a high compression efficiency, but are sensitive to packet losses. At the other extreme, methods such as still-image coding are not affected by packet losses but do not achieve high compression ratios. We present an information theoretic formulation for characterizing this tradeoff and present a class of coding schemes that achieve a near-optimal tradeoff in certain cases.

References

F. Etezadi, A. Khisti and M. Trott, Zero-Delay Sequential Transmission of Markov Sources over Burst Erasure Channels, IEEE Trans. Inform. Theory, vol. 60, no. 8, pp. 4584-4613, Aug. 2014


Physical Layer Security with Multiple Antennas 

While multiple antennas have been traditionally used in wireless systems to enhance throughput and reliability at the physical layer, in this project we examine their role in enhancing secrecy against an external eavesdroppersWhen the transmitter uses a multiple antenna array, it can exploit the directionality of the channel vectors to create a strong signal gain at the intended receiver, and a weak signal at other undesired locations. It can achieve further improvement by sending noise in the null-space of the intended receiver's channel. This technique is called artificial noise transmission.

Consider the  transmission of a confidential message to a large number of legitimate receivers. In such a multicast setup, we cannot  use artificial noise transmission. This is because when the number of receivers exceeds the number of transmit antennas, we cannot find a null-space simultaneously for all the channel vectors. We have developed a novel scheme - artificial noise alignment, where we use an idea from the interference alignment literature to align noise at the legitimate receivers.

Interference Alignment 

As shown in the above figure the multiantenna transmitter (with Nt antennas)  transmits a superposition of noise and information symbols, such that:

The above scheme does not require the knowledge of the eavesdropper's channel for noise alignment, just as in the original artificial noise transmission scheme. For further information, please refer to the following papers:

References

  1. A. Khisti,  and D. Zhang, Artificial-Noise Alignment for Secure Multicast using Multiple Antennas  IEEE Comm. Letters, Aug. 2013
  2. A. Khisti, Interference Alignment for the Multi-Antenna Compound Wiretap Channel IEEE. Trans. Inf. Theory, Special Issue on Interference Networks, March 2011
  3. A. Khisti and G. W. Wornell, Secure Transmission with Multiple Antennas-II: The MIMOME Wiretap Channel, IEEE. Trans. Inf. Theory, Vol. 56, No. 11, pp. 5515-5532, Nov. 2010
  4. A. Khisti and G. W. Wornell, Secure Transmission with Multiple Antennas-I: The MISOME Wiretap Channel, IEEE Trans. Inf. Theory, Vol. 56, No. 7, pp. 3088-3104, July 2011
 
Secret-Key Generation over Fading Channels

Properties of wireless channels such as channel reciprocity and fading can be used to establish a common secret-key between two or more remote terminals. This has become a very active area of research in many different disciplines. Our project focuses on the information theoretic capacity limits of secret-key generation over reciprocal fading channels. Consider the following model:

  • Two-way block fading channel
  • Reciprocity over the main channel
  • Non-Coherent Channel Gains

We have developed a new secret-key generation scheme for such a system that provides considerable gains over a training-only scheme. Our method consists of two-phase where the first phase is a short training period while the second phase is source-emulation. We further establish the optimality of our scheme in the high SNR regime.

 developed a new upper bound on the secret-key capacity (under public discussion) and established that it is tight in the high SNR regime. Using this result we show that the training-only schemes widely used in the literature are far from optimal and

There are however very few results on the information theoretic capacity of secret-key generation over wireless fading channels. Such results are important as they provide a theoretical benchmark for the practical systems being developed. However establishing such capacity results can be highly challenging. One should consider a non- coherent channel 

To the best of our  knowledge this is the only capacity result on two-way secret-key generation. It should have impact both on the theoretical research, as well as on the practical implementations of physical layer secret-key generation.

 sec_key
Figure: Comparison of secret-key generation schemes as a function of SNR from reference [1] below. The training-only schemes is far from optimal for a wide-range of SNR values.

References
  1. A. Khisti Secret-Key Agreement over Non-Coherent Block Fading Channels with Public Discussion  Submitted, IEEE Trans. Inf. Theory, August 2013
  2. A. Khisti, Interactive Secret-Key agreement over Fading Channels, Allerton Conference, 2012
  3. M. Andersson, A. Khisti and M. Skoglund, Secure-Key Agreement over Reciprocal Fading Channels at Low SNR SPAWC 2013

 Broadcasting over Erasure Channels

Broadcast and multicast to devices with different processing capabilities, storage capacities, and screen resolutions is becoming increasingly prevalent in many streaming applications. In point-to-point scenarios, the sender can adjust its transmission/coding rate to avoid packet losses and retransmit lost packets according to the feedback from the receiver through very efficient physical-layer schemes such as HARQ. In contrast, in broadcast/multicast applications, it is costly for the sender to collect and respond to individual receiver feedbacks, and thus HARQ schemes are disabled and packet losses are inevitable. Forward error correction coding provides a natural solution in such applications and is already being standardized in applications such as LTE eMBMS.

In the special case where each receiver must recover all the source packets, rateless codes provide a near optimal solution.  However when each receiver is only interested in recovering a certain fraction of source packets they are well known to be sub-optimal. The construction optimal codes in such cases remains an open problem. We have developed a  class of practical coding schemes for this setup, inspired by a connection to the joint-source channel coding problem in information theory. Our proposed codes are both simple, yet based on an information theoretic foundation. They can be a promising candidate in future implementations of broadcast/multicast applications.

References
Y. Li, L. Tan, A. Khisti and E. Soljanin , Successive Segmentation-based Coding for Broadcasting over Erasure Channels International Symposium on Information Theory, Jun 2014, Honolulu, Hawaii
 L. Tan, Y. Li, A. Khisti, E. Soljanin, Successive Segmentation-based Coding for Broadcasting over Erasure Channels  Submitted, IEEE Trans. Inform. Theory, Aug. 2014

Dirty Interference Cancellation

We have considered distributed interference cancellation based on dirty paper coding. The basic setup is shown in the figure below.

Dirty Interference Cancellation


The the interference signal is not known to the transmitter, but known to an external helper.  The helper knows the state and wishes to cancel it, but does not known the message. The encoder knows the message but not the state. Interestingly it can be shown that even in such a setup, if the power of the helper exceeds a certain threshold the capacity of this system is same as if the interference did not exist at all. Such a setup is very relevant in current wireless systems.  We believe that it can provide an practical alternative to techniques classical coding schemes for the interference channel such as the Han-Koboyashi scheme.

R. Duan, Y. Liang, A. Khisti and S. Shamai (Shitz), “State-Dependent Parallel Gaussian Channelswith a Common Helper in High Power Regime,” International Symposium on Information Theory, Jun 2014, Honolulu, Hawaii

R. Duan, Y. Liang, A. Khisti and S. Shamai (Shitz), “State Dependent Gaussian Z-Channel withMismatched Side Information and Interference,” Information Theory Workshop (ITW), Sep. 2013, Seville, Spain