Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Tight approximation algorithms for maximum general assignment problems
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Stackelberg game for utility-based cooperative cognitiveradio networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
IEEE Journal on Selected Areas in Communications - Special issue on broadband access networks: Architectures and protocols
Queue-aware subchannel and power allocation for downlink OFDM-based cognitive radio networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Capacity of Interference Channels With Partial Transmitter Cooperation
IEEE Transactions on Information Theory
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
Fair Allocation of Subcarrier and Power in an OFDMA Wireless Mesh Network
IEEE Journal on Selected Areas in Communications
Joint optimization of relay strategies and resource allocations in cooperative cellular networks
IEEE Journal on Selected Areas in Communications
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
Wireless Personal Communications: An International Journal
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Recently, a cooperative paradigm for single-channel cognitive radio networks has been advocated, where primary users can leverage secondary users to relay their traffic. However, it is not clear how such cooperation can be exploited in multi-channel networks effectively. Conventional cooperation entails that data on one channel has to be relayed on exactly the same channel, which is inefficient in multi-channel networks with channel and user diversity. Moreover, the selfishness of users complicates the critical resource allocation problem, as both parties target at maximizing their own utility. This work represents the first attempt to address these challenges. We propose FLEC, a novel design of flexible channel cooperation. It allows secondary users to freely optimize the use of channels for transmitting primary data along with their own data, in order to maximize performance. Further, we formulate a unifying optimization framework based on Nash Bargaining Solutions to fairly and efficiently address resource allocation between primary and secondary networks, in both decentralized and centralized settings. We present an optimal distributed algorithm and sub-optimal centralized heuristics, and verify their effectiveness via realistic simulations.