35 research outputs found
Multiple Access Channel with States Known Noncausally at One Encoder and Only Strictly Causally at the Other Encoder
We consider a two-user state-dependent multiaccess channel in which the
states of the channel are known non-causally to one of the encoders and only
strictly causally to the other encoder. Both encoders transmit a common message
and, in addition, the encoder that knows the states non-causally transmits an
individual message. We study the capacity region of this communication model.
In the discrete memoryless case, we establish inner and outer bounds on the
capacity region. Although the encoder that sends both messages knows the states
fully, we show that the strictly causal knowledge of these states at the other
encoder can be beneficial for this encoder, and in general enlarges the
capacity region. Furthermore, we find an explicit characterization of the
capacity in the case in which the two encoders transmit only the common
message. In the Gaussian case, we characterize the capacity region for the
model with individual message as well. Our converse proof in this case shows
that, for this model, strictly causal knowledge of the state at one of the
encoders does not increase capacity if the other is informed non-causally, a
result which sheds more light on the utility of conveying a compressed version
of the state to the decoder in recent results by Lapidoth and Steinberg on a
multiacess model with only strictly causal state at both encoders and
independent messages.Comment: 5 pages, to appear in the 2011 IEEE International Symposium on
Information Theor
Wyner-Ziv Type Versus Noisy Network Coding For a State-Dependent MAC
We consider a two-user state-dependent multiaccess channel in which the
states of the channel are known non-causally to one of the encoders and only
strictly causally to the other encoder. Both encoders transmit a common message
and, in addition, the encoder that knows the states non-causally transmits an
individual message. We find explicit characterizations of the capacity region
of this communication model in both discrete memoryless and memoryless Gaussian
cases. The analysis also reveals optimal ways of exploiting the knowledge of
the state only strictly causally at the encoder that sends only the common
message when such a knowledge is beneficial. The encoders collaborate to convey
to the decoder a lossy version of the state, in addition to transmitting the
information messages through a generalized Gel'fand-Pinsker binning.
Particularly important in this problem are the questions of 1) optimal ways of
performing the state compression and 2) whether or not the compression indices
should be decoded uniquely. We show that both compression \`a-la noisy network
coding, i.e., with no binning, and compression using Wyner-Ziv binning are
optimal. The scheme that uses Wyner-Ziv binning shares elements with Cover and
El Gamal original compress-and-forward, but differs from it mainly in that
backward decoding is employed instead of forward decoding and the compression
indices are not decoded uniquely. Finally, by exploring the properties of our
outer bound, we show that, although not required in general, the compression
indices can in fact be decoded uniquely essentially without altering the
capacity region, but at the expense of larger alphabets sizes for the auxiliary
random variables.Comment: Submitted for publication to the 2012 IEEE International Symposium on
Information Theory, 5 pages, 1 figur
On Cooperative Multiple Access Channels with Delayed CSI at Transmitters
We consider a cooperative two-user multiaccess channel in which the
transmission is controlled by a random state. Both encoders transmit a common
message and, one of the encoders also transmits an individual message. We study
the capacity region of this communication model for different degrees of
availability of the states at the encoders, causally or strictly causally. In
the case in which the states are revealed causally to both encoders but not to
the decoder we find an explicit characterization of the capacity region in the
discrete memoryless case. In the case in which the states are revealed only
strictly causally to both encoders, we establish inner and outer bounds on the
capacity region. The outer bound is non-trivial, and has a relatively simple
form. It has the advantage of incorporating only one auxiliary random variable.
We then introduce a class of cooperative multiaccess channels with states known
strictly causally at both encoders for which the inner and outer bounds agree;
and so we characterize the capacity region for this class. In this class of
channels, the state can be obtained as a deterministic function of the channel
inputs and output. We also study the model in which the states are revealed,
strictly causally, in an asymmetric manner, to only one encoder. Throughout the
paper, we discuss a number of examples; and compute the capacity region of some
of these examples. The results shed more light on the utility of delayed
channel state information for increasing the capacity region of state-dependent
cooperative multiaccess channels; and tie with recent progress in this
framework.Comment: 54 pages. To appear in IEEE Transactions on Information Theory. arXiv
admin note: substantial text overlap with arXiv:1201.327
Bounds on the Capacity of the Relay Channel with Noncausal State at Source
We consider a three-terminal state-dependent relay channel with the channel
state available non-causally at only the source. Such a model may be of
interest for node cooperation in the framework of cognition, i.e.,
collaborative signal transmission involving cognitive and non-cognitive radios.
We study the capacity of this communication model. One principal problem is
caused by the relay's not knowing the channel state. For the discrete
memoryless (DM) model, we establish two lower bounds and an upper bound on
channel capacity. The first lower bound is obtained by a coding scheme in which
the source describes the state of the channel to the relay and destination,
which then exploit the gained description for a better communication of the
source's information message. The coding scheme for the second lower bound
remedies the relay's not knowing the states of the channel by first computing,
at the source, the appropriate input that the relay would send had the relay
known the states of the channel, and then transmitting this appropriate input
to the relay. The relay simply guesses the sent input and sends it in the next
block. The upper bound is non trivial and it accounts for not knowing the state
at the relay and destination. For the general Gaussian model, we derive lower
bounds on the channel capacity by exploiting ideas in the spirit of those we
use for the DM model; and we show that these bounds are optimal for small and
large noise at the relay irrespective to the strength of the interference.
Furthermore, we also consider a special case model in which the source input
has two components one of which is independent of the state. We establish a
better upper bound for both DM and Gaussian cases and we also characterize the
capacity in a number of special cases.Comment: Submitted to the IEEE Transactions on Information Theory, 54 pages, 6
figure
MAC with Action-Dependent State Information at One Encoder
Problems dealing with the ability to take an action that affects the states
of state-dependent communication channels are of timely interest and
importance. Therefore, we extend the study of action-dependent channels, which
until now focused on point-to-point models, to multiple-access channels (MAC).
In this paper, we consider a two-user, state-dependent MAC, in which one of the
encoders, called the informed encoder, is allowed to take an action that
affects the formation of the channel states. Two independent messages are to be
sent through the channel: a common message known to both encoders and a private
message known only to the informed encoder. In addition, the informed encoder
has access to the sequence of channel states in a non-causal manner. Our
framework generalizes previously evaluated settings of state dependent
point-to-point channels with actions and MACs with common messages. We derive a
single letter characterization of the capacity region for this setting. Using
this general result, we obtain and compute the capacity region for the Gaussian
action-dependent MAC. The unique methods used in solving the Gaussian case are
then applied to obtain the capacity of the Gaussian action-dependent
point-to-point channel; a problem was left open until this work. Finally, we
establish some dualities between action-dependent channel coding and source
coding problems. Specifically, we obtain a duality between the considered MAC
setting and the rate distortion model known as "Successive Refinement with
Actions". This is done by developing a set of simple duality principles that
enable us to successfully evaluate the outcome of one problem given the other.Comment: 1. Parts of this paper appeared in the IEEE International Symposium
on Information Theory (ISIT 2012),Cambridge, MA, US, July 2012 and at the
IEEE 27th Convention of Electrical and Electronics Engineers in Israel (IEEEI
2012), Nov. 2012. 2. This work has been supported by the CORNET Consortium
Israel Ministry for Industry and Commerc