2,747 research outputs found
Effective Capacity in Multiple Access Channels with Arbitrary Inputs
In this paper, we consider a two-user multiple access fading channel under
quality-of-service (QoS) constraints. We initially formulate the transmission
rates for both transmitters, where the transmitters have arbitrarily
distributed input signals. We assume that the receiver performs successive
decoding with a certain order. Then, we establish the effective capacity region
that provides the maximum allowable sustainable arrival rate region at the
transmitters' buffers under QoS guarantees. Assuming limited transmission power
budgets at the transmitters, we attain the power allocation policies that
maximize the effective capacity region. As for the decoding order at the
receiver, we characterize the optimal decoding order regions in the plane of
channel fading parameters for given power allocation policies. In order to
accomplish the aforementioned objectives, we make use of the relationship
between the minimum mean square error and the first derivative of the mutual
information with respect to the power allocation policies. Through numerical
results, we display the impact of input signal distributions on the effective
capacity region performance of this two-user multiple access fading channel
Performance Analysis of Cognitive Radio Systems under QoS Constraints and Channel Uncertainty
In this paper, performance of cognitive transmission over time-selective flat
fading channels is studied under quality of service (QoS) constraints and
channel uncertainty. Cognitive secondary users (SUs) are assumed to initially
perform channel sensing to detect the activities of the primary users, and then
attempt to estimate the channel fading coefficients through training. Energy
detection is employed for channel sensing, and different minimum
mean-square-error (MMSE) estimation methods are considered for channel
estimation. In both channel sensing and estimation, erroneous decisions can be
made, and hence, channel uncertainty is not completely eliminated. In this
setting, performance is studied and interactions between channel sensing and
estimation are investigated.
Following the channel sensing and estimation tasks, SUs engage in data
transmission. Transmitter, being unaware of the channel fading coefficients, is
assumed to send the data at fixed power and rate levels that depend on the
channel sensing results. Under these assumptions, a state-transition model is
constructed by considering the reliability of the transmissions, channel
sensing decisions and their correctness, and the evolution of primary user
activity which is modeled as a two-state Markov process. In the data
transmission phase, an average power constraint on the secondary users is
considered to limit the interference to the primary users, and statistical
limitations on the buffer lengths are imposed to take into account the QoS
constraints of the secondary traffic. The maximum throughput under these
statistical QoS constraints is identified by finding the effective capacity of
the cognitive radio channel. Numerical results are provided for the power and
rate policies
Security in Cognitive Radio Networks
In this paper, we investigate the information-theoretic security by modeling
a cognitive radio wiretap channel under quality-of-service (QoS) constraints
and interference power limitations inflicted on primary users (PUs). We
initially define four different transmission scenarios regarding channel
sensing results and their correctness. We provide effective secure transmission
rates at which a secondary eavesdropper is refrained from listening to a
secondary transmitter (ST). Then, we construct a channel state transition
diagram that characterizes this channel model. We obtain the effective secure
capacity which describes the maximum constant buffer arrival rate under given
QoS constraints. We find out the optimal transmission power policies that
maximize the effective secure capacity, and then, we propose an algorithm that,
in general, converges quickly to these optimal policy values. Finally, we show
the performance levels and gains obtained under different channel conditions
and scenarios. And, we emphasize, in particular, the significant effect of
hidden-terminal problem on information-theoretic security in cognitive radios.Comment: Submitted to CISS 201
Effective Capacity in Broadcast Channels with Arbitrary Inputs
We consider a broadcast scenario where one transmitter communicates with two
receivers under quality-of-service constraints. The transmitter initially
employs superposition coding strategies with arbitrarily distributed signals
and sends data to both receivers. Regarding the channel state conditions, the
receivers perform successive interference cancellation to decode their own
data. We express the effective capacity region that provides the maximum
allowable sustainable data arrival rate region at the transmitter buffer or
buffers. Given an average transmission power limit, we provide a two-step
approach to obtain the optimal power allocation policies that maximize the
effective capacity region. Then, we characterize the optimal decoding regions
at the receivers in the space spanned by the channel fading power values. We
finally substantiate our results with numerical presentations.Comment: This paper will appear in 14th International Conference on
Wired&Wireless Internet Communications (WWIC
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