An O(log k) Approximate Min-Cut Max-Flow Theorem and Approximation Algorithm
SIAM Journal on Computing
Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Capacity bounds for ad hoc and hybrid wireless networks
ACM SIGCOMM Computer Communication Review
Capacity scaling in delay tolerant networks with heterogeneous mobile nodes
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Multicast capacity of wireless ad hoc networks
IEEE/ACM Transactions on Networking (TON)
Capacity of large-scale CSMA wireless networks
Proceedings of the 15th annual international conference on Mobile computing and networking
Capacity scaling of wireless networks with inhomogeneous node density: upper bounds
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Throughput, delay, and mobility in wireless ad hoc networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
The capacity of heterogeneous wireless networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Multicast capacity of wireless ad hoc networks under Gaussian channel model
IEEE/ACM Transactions on Networking (TON)
Scaling laws for overlaid wireless networks: a cognitive radio network versus a primary network
IEEE/ACM Transactions on Networking (TON)
The capacity of wireless networks
IEEE Transactions on Information Theory
Optimal throughput-delay scaling in wireless networks - part I: the fluid model
IEEE Transactions on Information Theory
Optimal Throughput–Delay Scaling in Wireless Networks—Part II: Constant-Size Packets
IEEE Transactions on Information Theory
Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
IEEE Transactions on Information Theory
Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network
IEEE Transactions on Information Theory
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There has been recent interest within the networking research community to understand how performance scales in cognitive networks with overlapping n primary nodes and m secondary nodes. Two important metrics, i.e., throughput and delay, are studied in this paper. We first propose a simple and extendable decision model, i.e., the hybrid protocol model, for the secondary nodes to exploit spatial gap among primary transmissions for frequency reuse. Then, a framework for general cognitive networks is established based on the hybrid protocol model to analyze the occurrence of transmission opportunities for secondary nodes. We show that if the primary network operates in a generalized TDMA fashion, or employs a routing scheme such that traffic flows choose relays independently, then the hybrid protocol model suffices to guide the secondary network to achieve the same throughput and delay scaling as a standalone network without harming the performance of the primary network, as long as the secondary transmission range is smaller than the primary range in order. Our approach is general in the sense that we only make a few weak assumptions on both networks, and therefore it obtains a wide variety of results. We show secondary networks can obtain the same order of throughput and delay as standalone networks when primary networks are classic static networks, networks with random walk mobility, hybrid networks, multicast networks, CSMA networks, networks with general mobility, or clustered networks. Our work presents a relatively complete picture of the performance scaling of cognitive networks and provides fundamental insight on the design of them.