262,313 research outputs found
Correlated Sources In Distributed Networks - Data Transmission, Common Information Characterization and Inferencing
Correlation is often present among observations in a distributed system. This thesis deals with various design issues when correlated data are observed at distributed terminals, including: communicating correlated sources over interference channels, characterizing the common information among dependent random variables, and testing the presence of dependence among observations.
It is well known that separated source and channel coding is optimal for point-to-point communication. However, this is not the case for multi-terminal communications. In this thesis, we study the problem of communicating correlated sources over interference channels (IC), for both the lossless and the lossy case. For lossless case, a sufficient condition is found using the technique of random source partition and correlation preserving codeword generation. The sufficient condition reduces to the Han-Kobayashi achievable rate region for IC with independent observations. Moreover, the proposed coding scheme is optimal for transmitting a special correlated sources over a class of deterministic interference channels. We then study the general case of lossy transmission of two correlated sources over a two-user discrete memoryless interference channel (DMIC). An achievable distortion region is obtained and Gaussian examples are studied.
The second topic is the generalization of Wyner\u27s definition of common information of a pair of random variables to that of N random variables. Coding theorems are obtained to show that the same operational meanings for the common information of two random variables apply to that of N random variables. We establish a monotone property of Wyner\u27s common information which is in contrast to other notions of the common information, specifically Shannon\u27s mutual information and G\u27{a}cs and K {o}rner\u27s common randomness. Later, we extend Wyner\u27s common information to that of continuous random variables and provide an operational meaning using the Gray-Wyner network with lossy source coding. We show that Wyner\u27s common information equals the smallest common message rate when the total rate is arbitrarily close to the rate-distortion function with joint decoding.
Finally, we consider the problem of distributed test of statistical independence under communication constraints. Focusing on the Gaussian case because of its tractability, we study in this thesis the characteristics of optimal scalar quantizers for distributed test of independence where the optimality is both in the finite sample regime and in the asymptotic regime
A new achievable rate region for interference channels with common information
In this paper, a new achievable rate region for general interference channels with common information is presented. Our result improves upon [1] by applying simultaneous superposition coding over sequential superposition coding. A detailed computation and comparison of the achievable rate region for the Gaussian case is conducted. The proposed achievable rate region is shown to coincide with the capacity region of the strong interference case [2]
Accessible Capacity of Secondary Users
A new problem formulation is presented for the Gaussian interference channels
(GIFC) with two pairs of users, which are distinguished as primary users and
secondary users, respectively. The primary users employ a pair of encoder and
decoder that were originally designed to satisfy a given error performance
requirement under the assumption that no interference exists from other users.
In the scenario when the secondary users attempt to access the same medium, we
are interested in the maximum transmission rate (defined as {\em accessible
capacity}) at which secondary users can communicate reliably without affecting
the error performance requirement by the primary users under the constraint
that the primary encoder (not the decoder) is kept unchanged. By modeling the
primary encoder as a generalized trellis code (GTC), we are then able to treat
the secondary link and the cross link from the secondary transmitter to the
primary receiver as finite state channels (FSCs). Based on this, upper and
lower bounds on the accessible capacity are derived. The impact of the error
performance requirement by the primary users on the accessible capacity is
analyzed by using the concept of interference margin. In the case of
non-trivial interference margin, the secondary message is split into common and
private parts and then encoded by superposition coding, which delivers a lower
bound on the accessible capacity. For some special cases, these bounds can be
computed numerically by using the BCJR algorithm. Numerical results are also
provided to gain insight into the impacts of the GTC and the error performance
requirement on the accessible capacity.Comment: 42 pages, 12 figures, 2 tables; Submitted to IEEE Transactions on
Information Theory on December, 2010, Revised on November, 201
Secret-key Agreement with Channel State Information at the Transmitter
We study the capacity of secret-key agreement over a wiretap channel with
state parameters. The transmitter communicates to the legitimate receiver and
the eavesdropper over a discrete memoryless wiretap channel with a memoryless
state sequence. The transmitter and the legitimate receiver generate a shared
secret key, that remains secret from the eavesdropper. No public discussion
channel is available. The state sequence is known noncausally to the
transmitter. We derive lower and upper bounds on the secret-key capacity. The
lower bound involves constructing a common state reconstruction sequence at the
legitimate terminals and binning the set of reconstruction sequences to obtain
the secret-key. For the special case of Gaussian channels with additive
interference (secret-keys from dirty paper channel) our bounds differ by 0.5
bit/symbol and coincide in the high signal-to-noise-ratio and high
interference-to-noise-ratio regimes. For the case when the legitimate receiver
is also revealed the state sequence, we establish that our lower bound achieves
the the secret-key capacity. In addition, for this special case, we also
propose another scheme that attains the capacity and requires only causal side
information at the transmitter and the receiver.Comment: 10 Pages, Submitted to IEEE Transactions on Information Forensics and
Security, Special Issue on Using the Physical Layer for Securing the Next
Generation of Communication System
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