73,773 research outputs found
Adaptive Channel Recommendation For Opportunistic Spectrum Access
We propose a dynamic spectrum access scheme where secondary users recommend
"good" channels to each other and access accordingly. We formulate the problem
as an average reward based Markov decision process. We show the existence of
the optimal stationary spectrum access policy, and explore its structure
properties in two asymptotic cases. Since the action space of the Markov
decision process is continuous, it is difficult to find the optimal policy by
simply discretizing the action space and use the policy iteration, value
iteration, or Q-learning methods. Instead, we propose a new algorithm based on
the Model Reference Adaptive Search method, and prove its convergence to the
optimal policy. Numerical results show that the proposed algorithms achieve up
to 18% and 100% performance improvement than the static channel recommendation
scheme in homogeneous and heterogeneous channel environments, respectively, and
is more robust to channel dynamics
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
General analytical framework for cooperative sensing and access trade-off optimization
In this paper, we investigate the joint cooperative spectrum sensing and
access design problem for multi-channel cognitive radio networks. A general
heterogeneous setting is considered where the probabilities that different
channels are available, SNRs of the signals received at secondary users (SUs)
due to transmissions from primary users (PUs) for different users and channels
can be different. We assume a cooperative sensing strategy with a general
a-out-of-b aggregation rule and design a synchronized MAC protocol so that SUs
can exploit available channels. We analyze the sensing performance and the
throughput achieved by the joint sensing and access design. Based on this
analysis, we develop algorithms to find optimal parameters for the sensing and
access protocols and to determine channel assignment for SUs to maximize the
system throughput. Finally, numerical results are presented to verify the
effectiveness of our design and demonstrate the relative performance of our
proposed algorithms and the optimal ones.Comment: arXiv admin note: text overlap with arXiv:1404.167
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