2,486 research outputs found
Broadcast Channels with Cooperating Decoders
We consider the problem of communicating over the general discrete memoryless
broadcast channel (BC) with partially cooperating receivers. In our setup,
receivers are able to exchange messages over noiseless conference links of
finite capacities, prior to decoding the messages sent from the transmitter. In
this paper we formulate the general problem of broadcast with cooperation. We
first find the capacity region for the case where the BC is physically
degraded. Then, we give achievability results for the general broadcast
channel, for both the two independent messages case and the single common
message case.Comment: Final version, to appear in the IEEE Transactions on Information
Theory -- contains (very) minor changes based on the last round of review
Gaussian Broadcast Channels with an Orthogonal and Bidirectional Cooperation Link
This paper considers a system where one transmitter broadcasts a single
common message to two receivers linked by a bidirectional cooperation channel,
which is assumed to be orthogonal to the downlink channel. Assuming a
simplified setup where, in particular, scalar relaying protocols are used and
channel coding is not exploited, we want to provide elements of response to
several questions of practical interest. Here are the main underlying issues:
1. The way of recombining the signals at the receivers; 2. The optimal number
of cooperation rounds; 3. The way of cooperating (symmetrically or
asymmetrically; which receiver should start cooperating in the latter case); 4.
The influence of spectral resources. These issues are considered by studying
the performance of the assumed system through analytical results when they are
derivable and through simulation results. For the particular choices we made,
the results sometimes do not coincide with those available for the discrete
counterpart of the studied channel
Relaying Simultaneous Multicast Messages
The problem of multicasting multiple messages with the help of a relay, which
may also have an independent message of its own to multicast, is considered. As
a first step to address this general model, referred to as the compound
multiple access channel with a relay (cMACr), the capacity region of the
multiple access channel with a "cognitive" relay is characterized, including
the cases of partial and rate-limited cognition. Achievable rate regions for
the cMACr model are then presented based on decode-and-forward (DF) and
compress-and-forward (CF) relaying strategies. Moreover, an outer bound is
derived for the special case in which each transmitter has a direct link to one
of the receivers while the connection to the other receiver is enabled only
through the relay terminal. Numerical results for the Gaussian channel are also
provided.Comment: This paper was presented at the IEEE Information Theory Workshop,
Volos, Greece, June 200
Cooperative Compute-and-Forward
We examine the benefits of user cooperation under compute-and-forward. Much
like in network coding, receivers in a compute-and-forward network recover
finite-field linear combinations of transmitters' messages. Recovery is enabled
by linear codes: transmitters map messages to a linear codebook, and receivers
attempt to decode the incoming superposition of signals to an integer
combination of codewords. However, the achievable computation rates are low if
channel gains do not correspond to a suitable linear combination. In response
to this challenge, we propose a cooperative approach to compute-and-forward. We
devise a lattice-coding approach to block Markov encoding with which we
construct a decode-and-forward style computation strategy. Transmitters
broadcast lattice codewords, decode each other's messages, and then
cooperatively transmit resolution information to aid receivers in decoding the
integer combinations. Using our strategy, we show that cooperation offers a
significant improvement both in the achievable computation rate and in the
diversity-multiplexing tradeoff.Comment: submitted to IEEE Transactions on Information Theor
Effective Capacity in Cognitive Radio Broadcast Channels
In this paper, we investigate effective capacity by modeling a cognitive
radio broadcast channel with one secondary transmitter (ST) and two secondary
receivers (SRs) under quality-of-service constraints and interference power
limitations. We initially describe three different cooperative channel sensing
strategies with different hard-decision combining algorithms at the ST, namely
OR, Majority, and AND rules. Since the channel sensing occurs with possible
errors, we consider a combined interference power constraint by which the
transmission power of the secondary users (SUs) is bounded when the channel is
sensed as both busy and idle. Furthermore, regarding the channel sensing
decision and its correctness, there exist possibly four different transmission
scenarios. We provide the instantaneous ergodic capacities of the channel
between the ST and each SR in all of these scenarios. Granting that
transmission outage arises when the instantaneous transmission rate is greater
than the instantaneous ergodic capacity, we establish two different
transmission rate policies for the SUs when the channel is sensed as idle. One
of these policies features a greedy approach disregarding a possible
transmission outage, and the other favors a precautious manner to prevent this
outage. Subsequently, we determine the effective capacity region of this
channel model, and we attain the power allocation policies that maximize this
region. Finally, we present the numerical results. We first show the
superiority of Majority rule when the channel sensing results are good. Then,
we illustrate that a greedy transmission rate approach is more beneficial for
the SUs under strict interference power constraints, whereas sending with lower
rates will be more advantageous under loose interference constraints.Comment: Submitted and Accepted to IEEE Globecom 201
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