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A ConstantFactor Approximation for Wireless Capacity Maximization with Power Control in the SINR Model
 In Proc. of the 22nd annual ACMSIAM symposium on Discrete algorithms (SODA
, 2011
"... In modern wireless networks devices are able to set the power for each transmission carried out. Experimental but also theoretical results indicate that such power control can improve the network capacity significantly. We study this problem in the physical interference model using SINR constraints. ..."
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Cited by 49 (9 self)
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In modern wireless networks devices are able to set the power for each transmission carried out. Experimental but also theoretical results indicate that such power control can improve the network capacity significantly. We study this problem in the physical interference model using SINR constraints. In the SINR capacity maximization problem, we are given n pairs of senders and receivers, located in a metric space (usually a socalled fading metric). The algorithm shall select a subset of these pairs and choose a power level for each of them with the objective of maximizing the number of simultaneous communications. This is, the selected pairs have to satisfy the SINR constraints with respect to the chosen powers. We present the first algorithm achieving a constantfactor approximation in fading metrics. The best previous results depend on further network parameters such as the ratio of the maximum and the minimum distance between a sender and its receiver. Expressed only in terms of n, they are (trivial) Ω(n) approximations. Our algorithm still achieves an O(log n) approximation if we only assume to have a general metric space rather than a fading metric. Furthermore, existing approaches work well together with the algorithm allowing it to be used in singlehop and multihop scheduling scenarios. Here, we also get polylog n approximations. 1
A fast distributed approximation algorithm for minimum spanning trees
 IN PROCEEDINGS OF THE 20TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING (DISC
, 2006
"... We present a distributed algorithm that constructs an O(log n)approximate minimum spanning tree (MST) in any arbitrary network. This algorithm runs in time Õ(D(G) + L(G, w)) where L(G, w) is a parameter called the local shortest path diameter and D(G) is the (unweighted) diameter of the graph. Our ..."
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Cited by 36 (8 self)
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We present a distributed algorithm that constructs an O(log n)approximate minimum spanning tree (MST) in any arbitrary network. This algorithm runs in time Õ(D(G) + L(G, w)) where L(G, w) is a parameter called the local shortest path diameter and D(G) is the (unweighted) diameter of the graph. Our algorithm is existentially optimal (up to polylogarithmic factors), i.e., there exists graphs which need Ω(D(G) + L(G, w)) time to compute an Happroximation to the MST for any H ∈ [1, Θ(log n)]. Our result also shows that there can be a significant time gap between exact and approximate MST computation: there exists graphs in which the running time of our approximation algorithm is exponentially faster than the timeoptimal distributed algorithm that computes the MST. Finally, we show that our algorithm can be used to find an approximate MST in wireless networks and in random weighted networks in almost optimal Õ(D(G)) time.
Wireless Capacity with Oblivious Power in General Metrics
"... The capacity of a wireless network is the maximum possible amount of simultaneous communication, taking interference into account. Formally, we treat the following problem. Given is a set of links, each a senderreceiver pair located in a metric space, and an assignment of power to the senders. We s ..."
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Cited by 27 (7 self)
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The capacity of a wireless network is the maximum possible amount of simultaneous communication, taking interference into account. Formally, we treat the following problem. Given is a set of links, each a senderreceiver pair located in a metric space, and an assignment of power to the senders. We seek a maximum subset of links that are feasible in the SINR model: namely, the signal received on each link should be larger than the sum of the interferences from the other links. We give a constantfactor approximation that holds for any lengthmonotone, sublinear power assignment and any distance metric. We use this to give essentially tight characterizations of capacity maximization under power control using oblivious power assignments. Specifically, we show that the mean
Approximation algorithms for secondary spectrum auctions
 In Proc. 23rd Symp. Parallelism in Algorithms and Architectures (SPAA
, 2011
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Nearly optimal bounds for distributed wireless scheduling in the sinr model. Arxiv preprint arXiv:1104.5200
, 2011
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Secondary spectrum auctions for symmetric and submodular bidders
 In Proc. 13th Conf. Electronic Commerce (EC
, 2012
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Wireless Connectivity and Capacity
"... Given n wireless transceivers located in a plane, a fundamental problem in wireless communications is to construct a strongly connected digraph on them such that the constituent links can be scheduled in fewest possible time slots, assuming the SINR model of interference. In this paper, we provide a ..."
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Cited by 11 (4 self)
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Given n wireless transceivers located in a plane, a fundamental problem in wireless communications is to construct a strongly connected digraph on them such that the constituent links can be scheduled in fewest possible time slots, assuming the SINR model of interference. In this paper, we provide an algorithm that connects an arbitrary point set in O(log n) slots, improving on the previous best bound of O(log 2 n) due to Moscibroda. This is complemented with a superconstant lower bound on our approach to connectivity. An important feature is that the algorithms allow for bidirectional (halfduplex) communication. One implication of this result is an improved bound of Ω(1 / log n) on the worstcase capacity of wireless networks, matching the best bound known for the extensively studied averagecase. We explore the utility of oblivious power assignments, and show that essentially all such assignments result in a worst case bound of Ω(n) slots for connectivity. This rules out a recent claim of a O(log n) bound using oblivious power. On the other hand, using our result we show that O(min(log ∆, log n · (log n + log log ∆))) slots suffice, where ∆ is the ratio between the largest and the smallest links in a minimum spanning tree of the points. Our results extend to the related problem of minimum latency aggregation scheduling, where we show that aggregation scheduling with O(log n) latency is possible, improving upon the previous best known latency of O(log 3 n). We also initiate the study of network design problems in the SINR model beyond strong connectivity, obtaining similar bounds for biconnected and kedge connected structures. 1
Wireless capacity and admission control in cognitive radio
 IEEE INFOCOM
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The Power of NonUniform Wireless Power
, 2012
"... We study a fundamental measure for wireless interference in the SINR model when power control is available. This measure characterizes the effectiveness of using oblivious power — when the power used by a transmitter only depends on the distance to the receiver — as a mechanism for improving wireles ..."
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Cited by 7 (0 self)
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We study a fundamental measure for wireless interference in the SINR model when power control is available. This measure characterizes the effectiveness of using oblivious power — when the power used by a transmitter only depends on the distance to the receiver — as a mechanism for improving wireless capacity. We prove optimal bounds for this measure, implying a number of algorithmic applications. An algorithm is provided that achieves — due to existing lower bounds — capacity that is asymptotically best possible using oblivious power assignments. Improved approximation algorithms are provided for a number of problems for oblivious power and for power control, including distributed scheduling, secondary spectrum auctions, wireless connectivity, and dynamic packet scheduling.