3,743 research outputs found
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
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Maximizing System Throughput Using Cooperative Sensing in Multi-Channel Cognitive Radio Networks
In Cognitive Radio Networks (CRNs), unlicensed users are allowed to access
the licensed spectrum when it is not currently being used by primary users
(PUs). In this paper, we study the throughput maximization problem for a
multi-channel CRN where each SU can only sense a limited number of channels. We
show that this problem is strongly NP-hard, and propose an approximation
algorithm with a factor at least where is a system
parameter reflecting the sensing capability of SUs across channels and their
sensing budgets. This performance guarantee is achieved by exploiting a nice
structural property of the objective function and constructing a particular
matching. Our numerical results demonstrate the advantage of our algorithm
compared with both a random and a greedy sensing assignment algorithm
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