521 research outputs found
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
Backlog and Delay Reasoning in HARQ Systems
Recently, hybrid-automatic-repeat-request (HARQ) systems have been favored in
particular state-of-the-art communications systems since they provide the
practicality of error detections and corrections aligned with repeat-requests
when needed at receivers. The queueing characteristics of these systems have
taken considerable focus since the current technology demands data
transmissions with a minimum delay provisioning. In this paper, we investigate
the effects of physical layer characteristics on data link layer performance in
a general class of HARQ systems. Constructing a state transition model that
combines queue activity at a transmitter and decoding efficiency at a receiver,
we identify the probability of clearing the queue at the transmitter and the
packet-loss probability at the receiver. We determine the effective capacity
that yields the maximum feasible data arrival rate at the queue under
quality-of-service constraints. In addition, we put forward non-asymptotic
backlog and delay bounds. Finally, regarding three different HARQ protocols,
namely Type-I HARQ, HARQ-chase combining (HARQ-CC) and HARQ-incremental
redundancy (HARQ-IR), we show the superiority of HARQ-IR in delay robustness
over the others. However, we further observe that the performance gap between
HARQ-CC and HARQ-IR is quite negligible in certain cases. The novelty of our
paper is a general cross-layer analysis of these systems, considering
encoding/decoding in the physical layer and delay aspects in the data-link
layer
Training Optimization for Gauss-Markov Rayleigh Fading Channels
In this paper, pilot-assisted transmission over Gauss-Markov Rayleigh fading
channels is considered. A simple scenario, where a single pilot signal is
transmitted every T symbols and T-1 data symbols are transmitted in between the
pilots, is studied. First, it is assumed that binary phase-shift keying (BPSK)
modulation is employed at the transmitter. With this assumption, the training
period, and data and training power allocation are jointly optimized by
maximizing an achievable rate expression. Achievable rates and energy-per-bit
requirements are computed using the optimal training parameters. Secondly, a
capacity lower bound is obtained by considering the error in the estimate as
another source of additive Gaussian noise, and the training parameters are
optimized by maximizing this lower bound.Comment: To appear in the Proc. of the 2007 IEEE International Conference on
Communication
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
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
Performance Analysis of Energy-Detection-Based Massive SIMO
Recently, communications systems that are both energy efficient and reliable
are under investigation. In this paper, we concentrate on an
energy-detection-based transmission scheme where a communication scenario
between a transmitter with one antenna and a receiver with significantly many
antennas is considered. We assume that the receiver initially calculates the
average energy across all antennas, and then decodes the transmitted data by
exploiting the average energy level. Then, we calculate the average symbol
error probability by means of a maximum a-posteriori probability detector at
the receiver. Following that, we provide the optimal decision regions.
Furthermore, we develop an iterative algorithm that reaches the optimal
constellation diagram under a given average transmit power constraint. Through
numerical analysis, we explore the system performance
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