12 research outputs found
Bounds on the Capacity of the Relay Channel with Noncausal State Information 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 in
this setup is caused by the relay's not knowing the channel state. In the
discrete memoryless (DM) case, we establish lower bounds on channel capacity.
For the Gaussian case, we derive lower and upper bounds on the channel
capacity. The upper bound is strictly better than the cut-set upper bound. We
show that one of the developed lower bounds comes close to the upper bound,
asymptotically, for certain ranges of rates.Comment: 5 pages, submitted to 2010 IEEE International Symposium on
Information Theor
Multiaccess Channels with State Known to One Encoder: Another Case of Degraded Message Sets
We consider a two-user state-dependent multiaccess channel in which only one
of the encoders is informed, non-causally, of the channel states. Two
independent messages are transmitted: a common message transmitted by both the
informed and uninformed encoders, and an individual message transmitted by only
the uninformed encoder. We derive inner and outer bounds on the capacity region
of this model in the discrete memoryless case as well as the Gaussian case.
Further, we show that the bounds for the Gaussian case are tight in some
special cases.Comment: 5 pages, Proc. of IEEE International Symposium on Information theory,
ISIT 2009, Seoul, Kore
Cooperative Relaying with State Available at the Relay
We consider a state-dependent full-duplex relay channel with the state of the
channel non-causally available at only the relay. In the framework of
cooperative wireless networks, some specific terminals can be equipped with
cognition capabilities, i.e, the relay in our model. In the discrete memoryless
(DM) case, we derive lower and upper bounds on channel capacity. The lower
bound is obtained by a coding scheme at the relay that consists in a
combination of codeword splitting, Gel'fand-Pinsker binning, and a
decode-and-forward scheme. The upper bound is better than that obtained by
assuming that the channel state is available at the source and the destination
as well. For the Gaussian case, we also derive lower and upper bounds on
channel capacity. The lower bound is obtained by a coding scheme which is based
on a combination of codeword splitting and Generalized dirty paper coding. The
upper bound is also better than that obtained by assuming that the channel
state is available at the source, the relay, and the destination. The two
bounds meet, and so give the capacity, in some special cases for the degraded
Gaussian case.Comment: Corrected typos and added references w.r.t. the first version. Paper
also published in proc. of IEEE Information Theory Workshop 2008 (6 pages, 3
figures
Cooperative Relaying with State Available Non-Causally at the Relay
We consider a three-terminal state-dependent relay channel with the channel
state noncausally available at only the relay. Such a model may be useful for
designing cooperative wireless networks with some terminals equipped with
cognition capabilities, i.e., the relay in our setup. In the discrete
memoryless (DM) case, we establish lower and upper bounds on channel capacity.
The lower bound is obtained by a coding scheme at the relay that uses a
combination of codeword splitting, Gel'fand-Pinsker binning, and
decode-and-forward relaying. The upper bound improves upon that obtained by
assuming that the channel state is available at the source, the relay, and the
destination. For the Gaussian case, we also derive lower and upper bounds on
the capacity. The lower bound is obtained by a coding scheme at the relay that
uses a combination of codeword splitting, generalized dirty paper coding, and
decode-and-forward relaying; the upper bound is also better than that obtained
by assuming that the channel state is available at the source, the relay, and
the destination. In the case of degraded Gaussian channels, the lower bound
meets with the upper bound for some special cases, and, so, the capacity is
obtained for these cases. Furthermore, in the Gaussian case, we also extend the
results to the case in which the relay operates in a half-duplex mode.Comment: 62 pages. To appear in IEEE Transactions on Information Theor
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
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