1,763 research outputs found
Optimal and Approximation Algorithms for Joint Routing and Scheduling in Millimeter-Wave Cellular Networks
Millimeter-wave (mmWave) communication is a promising technology to cope with
the exponential increase in 5G data traffic.
Such networks typically require a very dense deployment of base stations.
A subset of those, so-called macro base stations, feature high-bandwidth
connection to the core network, while relay base stations are connected
wirelessly.
To reduce cost and increase flexibility, wireless backhauling is needed to
connect both macro to relay as well as relay to relay base stations.
The characteristics of mmWave communication mandates new paradigms for
routing and scheduling.
The paper investigates scheduling algorithms under different interference
models.
To showcase the scheduling methods, we study the maximum throughput fair
scheduling problem. Yet the proposed algorithms can be easily extended to other
problems.
For a full-duplex network under the no interference model, we propose an
efficient polynomial-time scheduling method, the {\em schedule-oriented
optimization}. Further, we prove that the problem is NP-hard if we assume
pairwise link interference model or half-duplex radios.
Fractional weighted coloring based approximation algorithms are proposed for
these NP-hard cases.
Moreover, the approximation algorithm parallel data stream scheduling is
proposed for the case of half-duplex network under the no interference model.
It has better approximation ratio than the fractional weighted coloring based
algorithms and even attains the optimal solution for the special case of
uniform orthogonal backhaul networks.Comment: accepted for publish in the IEEE/ACM Transactions on Networkin
Efficiently Finding Simple Schedules in Gaussian Half-Duplex Relay Line Networks
The problem of operating a Gaussian Half-Duplex (HD) relay network optimally
is challenging due to the exponential number of listen/transmit network states
that need to be considered. Recent results have shown that, for the class of
Gaussian HD networks with N relays, there always exists a simple schedule,
i.e., with at most N +1 active states, that is sufficient for approximate
(i.e., up to a constant gap) capacity characterization. This paper investigates
how to efficiently find such a simple schedule over line networks. Towards this
end, a polynomial-time algorithm is designed and proved to output a simple
schedule that achieves the approximate capacity. The key ingredient of the
algorithm is to leverage similarities between network states in HD and edge
coloring in a graph. It is also shown that the algorithm allows to derive a
closed-form expression for the approximate capacity of the Gaussian line
network that can be evaluated distributively and in linear time. Additionally,
it is shown using this closed-form that the problem of Half-Duplex routing is
NP-Hard.Comment: A short version of this paper was submitted to ISIT 201
Multiflow Transmission in Delay Constrained Cooperative Wireless Networks
This paper considers the problem of energy-efficient transmission in
multi-flow multihop cooperative wireless networks. Although the performance
gains of cooperative approaches are well known, the combinatorial nature of
these schemes makes it difficult to design efficient polynomial-time algorithms
for joint routing, scheduling and power control. This becomes more so when
there is more than one flow in the network. It has been conjectured by many
authors, in the literature, that the multiflow problem in cooperative networks
is an NP-hard problem. In this paper, we formulate the problem, as a
combinatorial optimization problem, for a general setting of -flows, and
formally prove that the problem is not only NP-hard but it is
inapproxmiable. To our knowledge*, these results provide
the first such inapproxmiablity proof in the context of multiflow cooperative
wireless networks. We further prove that for a special case of k = 1 the
solution is a simple path, and devise a polynomial time algorithm for jointly
optimizing routing, scheduling and power control. We then use this algorithm to
establish analytical upper and lower bounds for the optimal performance for the
general case of flows. Furthermore, we propose a polynomial time heuristic
for calculating the solution for the general case and evaluate the performance
of this heuristic under different channel conditions and against the analytical
upper and lower bounds.Comment: 9 pages, 5 figure
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