6,476 research outputs found
Coalition Formation Games for Collaborative Spectrum Sensing
Collaborative Spectrum Sensing (CSS) between secondary users (SUs) in
cognitive networks exhibits an inherent tradeoff between minimizing the
probability of missing the detection of the primary user (PU) and maintaining a
reasonable false alarm probability (e.g., for maintaining a good spectrum
utilization). In this paper, we study the impact of this tradeoff on the
network structure and the cooperative incentives of the SUs that seek to
cooperate for improving their detection performance. We model the CSS problem
as a non-transferable coalitional game, and we propose distributed algorithms
for coalition formation. First, we construct a distributed coalition formation
(CF) algorithm that allows the SUs to self-organize into disjoint coalitions
while accounting for the CSS tradeoff. Then, the CF algorithm is complemented
with a coalitional voting game for enabling distributed coalition formation
with detection probability guarantees (CF-PD) when required by the PU. The
CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e.,
coalitions that achieve the target detection probability with minimal costs.
For both algorithms, we study and prove various properties pertaining to
network structure, adaptation to mobility and stability. Simulation results
show that CF reduces the average probability of miss per SU up to 88.45%
relative to the non-cooperative case, while maintaining a desired false alarm.
For CF-PD, the results show that up to 87.25% of the SUs achieve the required
detection probability through MWCComment: IEEE Transactions on Vehicular Technology, to appea
Byzantine Attack and Defense in Cognitive Radio Networks: A Survey
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the
spectrum sensing data falsification (SSDF) attack in the literature, is one of
the key adversaries to the success of cognitive radio networks (CRNs). In the
past couple of years, the research on the Byzantine attack and defense
strategies has gained worldwide increasing attention. In this paper, we provide
a comprehensive survey and tutorial on the recent advances in the Byzantine
attack and defense for CSS in CRNs. Specifically, we first briefly present the
preliminaries of CSS for general readers, including signal detection
techniques, hypothesis testing, and data fusion. Second, we analyze the spear
and shield relation between Byzantine attack and defense from three aspects:
the vulnerability of CSS to attack, the obstacles in CSS to defense, and the
games between attack and defense. Then, we propose a taxonomy of the existing
Byzantine attack behaviors and elaborate on the corresponding attack
parameters, which determine where, who, how, and when to launch attacks. Next,
from the perspectives of homogeneous or heterogeneous scenarios, we classify
the existing defense algorithms, and provide an in-depth tutorial on the
state-of-the-art Byzantine defense schemes, commonly known as robust or secure
CSS in the literature. Furthermore, we highlight the unsolved research
challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral
Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks
In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones
Sensing Throughput Optimization in Fading Cognitive Multiple Access Channels With Energy Harvesting Secondary Transmitters
The paper investigates the problem of maximizing expected sum throughput in a
fading multiple access cognitive radio network when secondary user (SU)
transmitters have energy harvesting capability, and perform cooperative
spectrum sensing. We formulate the problem as maximization of sum-capacity of
the cognitive multiple access network over a finite time horizon subject to a
time averaged interference constraint at the primary user (PU) and almost sure
energy causality constraints at the SUs. The problem is a mixed integer
non-linear program with respect to two decision variables namely spectrum
access decision and spectrum sensing decision, and the continuous variables
sensing time and transmission power. In general, this problem is known to be NP
hard. For optimization over these two decision variables, we use an exhaustive
search policy when the length of the time horizon is small, and a heuristic
policy for longer horizons. For given values of the decision variables, the
problem simplifies into a joint optimization on SU \textit{transmission power}
and \textit{sensing time}, which is non-convex in nature. We solve the
resulting optimization problem as an alternating convex optimization problem
for both non-causal and causal channel state information and harvested energy
information patterns at the SU base station (SBS) or fusion center (FC). We
present an analytic solution for the non-causal scenario with infinite battery
capacity for a general finite horizon problem.We formulate the problem with
causal information and finite battery capacity as a stochastic control problem
and solve it using the technique of dynamic programming. Numerical results are
presented to illustrate the performance of the various algorithms
Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel Cognitive Radio Networks
In this paper, we propose a semi-distributed cooperative spectrum sen sing
(SDCSS) and channel access framework for multi-channel cognitive radio networks
(CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs)
perform sensing and exchange sensing outcomes with ea ch other to locate
spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive
MAC protocol integrating the SDCSS to enable efficient spectrum sharing among
SUs. We then perform throughput analysis and develop an algorithm to determine
the spectrum sensing and access parameters to maximize the throughput for a
given allocation of channel sensing sets. Moreover, we consider the spectrum
sensing set optimization problem for SUs to maxim ize the overall system
throughput. We present both exhaustive search and low-complexity greedy
algorithms to determine the sensing sets for SUs and analyze their complexity.
We also show how our design and analysis can be extended to consider reporting
errors. Finally, extensive numerical results are presented to demonstrate the
sig nificant performance gain of our optimized design framework with respect to
non-optimized designs as well as the imp acts of different protocol parameters
on the throughput performance.Comment: accepted for publication EURASIP Journal on Wireless Communications
and Networking, 201
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