4,041 research outputs found
On distributed scheduling in wireless networks exploiting broadcast and network coding
In this paper, we consider cross-layer optimization in wireless networks with wireless broadcast advantage, focusing on the problem of distributed scheduling of broadcast links. The wireless broadcast advantage is most useful in multicast scenarios. As such, we include network coding in our design to exploit the throughput gain brought in by network coding for multicasting. We derive a subgradient algorithm for joint rate control, network coding and scheduling, which however requires centralized link scheduling. Under the primary interference model, link scheduling problem is equivalent to a maximum weighted hypergraph matching problem that is NP-complete. To solve the scheduling problem distributedly, locally greedy and randomized approximation algorithms are proposed and shown to have bounded worst-case performance. With random network coding, we obtain a fully distributed cross-layer design. Numerical results show promising throughput gain using the proposed algorithms, and surprisingly, in some cases even with less complexity than cross-layer design without broadcast advantage
Wireless Network Control with Privacy Using Hybrid ARQ
We consider the problem of resource allocation in a wireless cellular
network, in which nodes have both open and private information to be
transmitted to the base station over block fading uplink channels. We develop a
cross-layer solution, based on hybrid ARQ transmission with incremental
redundancy. We provide a scheme that combines power control, flow control, and
scheduling in order to maximize a global utility function, subject to the
stability of the data queues, an average power constraint, and a constraint on
the privacy outage probability. Our scheme is based on the assumption that each
node has an estimate of its uplink channel gain at each block, while only the
distribution of the cross channel gains is available. We prove that our scheme
achieves a utility, arbitrarily close to the maximum achievable utility given
the available channel state information
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