26,977 research outputs found
Pilot Aided Transmissions Technique to Achieve Optimal Effective Capacity Over Imperfect Channel Estimation in Cognitive Radio Networks
In cognitive radio networks, a secondary user (SU) can share the same frequency band with the primary user (PU) as long as the interference introduced to the later is below a predefined threshold. In this paper, the transmission performance in cognitive radio networks is studied assuming imperfect channel estimation, and taking quality of service (QoS) constraints into consideration. It is assumed that the cognitive transmitter can perform channel estimation and send the data at two different rates and power levels depending on the activity of the primary users. The existence of the primary user can be detected by channel sensing. A two-state Markov chain process is used to model the existence of the primary users. The cognitive transmission is also configured as a state transition model depending on whether the rates are higher or lower than the instantaneous rates values. This paper studies the maximum capacity of the cognitive user under the delay constraint. We use the new metric concept of effective capacity of the channel and introduce an optimization problem for rate and power allocation under interference power constraints. An numerical example illustrates the average effective capacity optimization and the impact of other system parameters. 
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
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
Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing
This paper studies the symbol error rate performance of cognitive radio
transmissions in the presence of imperfect sensing decisions. Two different
transmission schemes, namely sensing-based spectrum sharing (SSS) and
opportunistic spectrum access (OSA), are considered. In both schemes, secondary
users first perform channel sensing, albeit with possible errors. In SSS,
depending on the sensing decisions, they adapt the transmission power level and
coexist with primary users in the channel. On the other hand, in OSA, secondary
users are allowed to transmit only when the primary user activity is not
detected. Initially, for both transmission schemes, general formulations for
the optimal decision rule and error probabilities are provided for arbitrary
modulation schemes under the assumptions that the receiver is equipped with the
sensing decision and perfect knowledge of the channel fading, and the primary
user's received faded signals at the secondary receiver has a Gaussian mixture
distribution. Subsequently, the general approach is specialized to rectangular
quadrature amplitude modulation (QAM). More specifically, optimal decision rule
is characterized for rectangular QAM, and closed-form expressions for the
average symbol error probability attained with the optimal detector are derived
under both transmit power and interference constraints. The effects of
imperfect channel sensing decisions, interference from the primary user and its
Gaussian mixture model, and the transmit power and interference constraints on
the error rate performance of cognitive transmissions are analyzed
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