1,239 research outputs found
Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity under Fading Channels in Cognitive Radio Networks
This paper studies optimal bandwidth and power allocation in a cognitive
radio network where multiple secondary users (SUs) share the licensed spectrum
of a primary user (PU) under fading channels using the frequency division
multiple access scheme. The sum ergodic capacity of all the SUs is taken as the
performance metric of the network. Besides all combinations of the peak/average
transmit power constraints at the SUs and the peak/average interference power
constraint imposed by the PU, total bandwidth constraint of the licensed
spectrum is also taken into account. Optimal bandwidth allocation is derived in
closed-form for any given power allocation. The structures of optimal power
allocations are also derived under all possible combinations of the
aforementioned power constraints. These structures indicate the possible
numbers of users that transmit at nonzero power but below their corresponding
peak powers, and show that other users do not transmit or transmit at their
corresponding peak power. Based on these structures, efficient algorithms are
developed for finding the optimal power allocations.Comment: 28 pages, 6 figures, submitted to the IEEE Trans. Signal Processing
in June 201
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
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
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