57 research outputs found
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
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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
Capacity of a Class of State-Dependent Orthogonal Relay Channels
The class of orthogonal relay channels in which the orthogonal channels
connecting the source terminal to the relay and the destination, and the relay
to the destination, depend on a state sequence, is considered. It is assumed
that the state sequence is fully known at the destination while it is not known
at the source or the relay. The capacity of this class of relay channels is
characterized, and shown to be achieved by the partial
decode-compress-and-forward (pDCF) scheme. Then the capacity of certain binary
and Gaussian state-dependent orthogonal relay channels are studied in detail,
and it is shown that the compress-and-forward (CF) and
partial-decode-and-forward (pDF) schemes are suboptimal in general. To the best
of our knowledge, this is the first single relay channel model for which the
capacity is achieved by pDCF, while pDF and CF schemes are both suboptimal.
Furthermore, it is shown that the capacity of the considered class of
state-dependent orthogonal relay channels is in general below the cut-set
bound. The conditions under which pDF or CF suffices to meet the cut-set bound,
and hence, achieve the capacity, are also derived.Comment: This paper has been accepted by IEEE Transactions on Information
Theor
On the Capacity of the Two-user Gaussian Causal Cognitive Interference Channel
This paper considers the two-user Gaussian Causal Cognitive Interference
Channel (GCCIC), which consists of two source-destination pairs that share the
same channel and where one full-duplex cognitive source can causally learn the
message of the primary source through a noisy link. The GCCIC is an
interference channel with unilateral source cooperation that better models
practical cognitive radio networks than the commonly used model which assumes
that one source has perfect non-causal knowledge of the other source's message.
First the sum-capacity of the symmetric GCCIC is determined to within a
constant gap. Then, the insights gained from the derivation of the symmetric
sum-capacity are extended to characterize the whole capacity region to within a
constant gap for more general cases. In particular, the capacity is determined
(a) to within 2 bits for the fully connected GCCIC when, roughly speaking, the
interference is not weak at both receivers, (b) to within 2 bits for the
Z-channel, i.e., when there is no interference from the primary user, and (c)
to within 2 bits for the S-channel, i.e., when there is no interference from
the secondary user. The parameter regimes where the GCCIC is equivalent, in
terms of generalized degrees-of-freedom, to the noncooperative interference
channel (i.e., unilateral causal cooperation is not useful), to the non-causal
cognitive interference channel (i.e., causal cooperation attains the ultimate
limit of cognitive radio technology), and to bilateral source cooperation are
identified. These comparisons shed lights into the parameter regimes and
network topologies that in practice might provide an unbounded throughput gain
compared to currently available (non cognitive) technologies.Comment: Under second round review in IEEE Transactions in Information Theory
- Submitted September 201
Inner and Outer Bounds for the Gaussian Cognitive Interference Channel and New Capacity Results
The capacity of the Gaussian cognitive interference channel, a variation of
the classical two-user interference channel where one of the transmitters
(referred to as cognitive) has knowledge of both messages, is known in several
parameter regimes but remains unknown in general. In this paper we provide a
comparative overview of this channel model as we proceed through our
contributions: we present a new outer bound based on the idea of a broadcast
channel with degraded message sets, and another series of outer bounds obtained
by transforming the cognitive channel into channels with known capacity. We
specialize the largest known inner bound derived for the discrete memoryless
channel to the Gaussian noise channel and present several simplified schemes
evaluated for Gaussian inputs in closed form which we use to prove a number of
results. These include a new set of capacity results for the a) "primary
decodes cognitive" regime, a subset of the "strong interference" regime that is
not included in the "very strong interference" regime for which capacity was
known, and for the b) "S-channel" in which the primary transmitter does not
interfere with the cognitive receiver. Next, for a general Gaussian cognitive
interference channel, we determine the capacity to within one bit/s/Hz and to
within a factor two regardless of channel parameters, thus establishing rate
performance guarantees at high and low SNR, respectively. We also show how
different simplified transmission schemes achieve a constant gap between inner
and outer bound for specific channels. Finally, we numerically evaluate and
compare the various simplified achievable rate regions and outer bounds in
parameter regimes where capacity is unknown, leading to further insight on the
capacity region of the Gaussian cognitive interference channel.Comment: submitted to IEEE transaction of Information Theor
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