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Maximal Packing with Interference Constraints

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TLDR
This work proposes a semi-definite (SDP) relaxation for the NP hard problem and discusses the algorithm and the quality of the relaxation by providing approximation ratios for the relaxation.
Abstract
In this work, we analyze the maximum number of wireless transmitters (nodes) that can be scheduled subject to interference constraints across the nodes. Given a set of nodes, the problem reduces to finding the maximum cardinality of a subset that can concurrently transmit without violating interference constraints. The resulting packing problem is a binary optimization problem, which is NP hard. We propose a semi-definite (SDP) relaxation for the NP hard problem and discuss the algorithm and the quality of the relaxation by providing approximation ratios for the relaxation.

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References
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Journal ArticleDOI

The capacity of wireless networks

TL;DR: When n identical randomly located nodes, each capable of transmitting at W bits per second and using a fixed range, form a wireless network, the throughput /spl lambda/(n) obtainable by each node for a randomly chosen destination is /spl Theta/(W//spl radic/(nlogn)) bits persecond under a noninterference protocol.
Journal ArticleDOI

Semidefinite Relaxation of Quadratic Optimization Problems

TL;DR: This article has provided general, comprehensive coverage of the SDR technique, from its practical deployments and scope of applicability to key theoretical results, and showcased several representative applications, namely MIMO detection, B¿ shimming in MRI, and sensor network localization.
Journal ArticleDOI

Sensor Selection via Convex Optimization

TL;DR: This paper describes a heuristic, based on convex optimization, that gives a subset selection as well as a bound on the best performance that can be achieved by any selection of k sensor measurements.
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Complexity in geometric SINR

TL;DR: The first NP-completeness proofs in the geometric SINR model, which explicitly uses the fact that nodes are distributed in the Euclidean plane, are presented, which proves two problems to be NP-complete: Scheduling and One-Shot Scheduling.
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The Complexity of Connectivity in Wireless Networks

TL;DR: This paper presents a novel scheduling algorithm that successfully schedules a strongly connected set of links in time O(logn) even in arbitrary worst-case networks, and proves that the scheduling complexity of connectivity grows only polylogarithmically in the number of nodes.
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