11,260 research outputs found
Wireless Node Cooperation with Resource Availability Constraints
Base station cooperation is a promising scheme to improve network performance
for next generation cellular networks. Up to this point research has focused on
station grouping criteria based solely on geographic proximity. However, for
the cooperation to be meaningful, each station participating in a group should
have sufficient available resources to share with others. In this work we
consider an alternative grouping criterion based on a distance that considers
both geographic proximity and available resources of the stations. When the
network is modelled by a Poisson Point Process, we derive analytical formulas
on the proportion of cooperative pairs or single stations, and the expected sum
interference from each of the groups. The results illustrate that cooperation
gains strongly depend on the distribution of available resources over the
network.Comment: submitted, 12 pages, double-column, 7 figures, 8 sub-figures in tota
Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness
This paper addresses coordinated downlink beamforming optimization in
multicell time-division duplex (TDD) systems where a small number of parameters
are exchanged between cells but with no data sharing. With the goal to reach
the point on the Pareto boundary with max-min rate fairness, we first develop a
two-step centralized optimization algorithm to design the joint beamforming
vectors. This algorithm can achieve a further sum-rate improvement over the
max-min optimal performance, and is shown to guarantee max-min Pareto
optimality for scenarios with two base stations (BSs) each serving a single
user. To realize a distributed solution with limited intercell communication,
we then propose an iterative algorithm by exploiting an approximate
uplink-downlink duality, in which only a small number of positive scalars are
shared between cells in each iteration. Simulation results show that the
proposed distributed solution achieves a fairness rate performance close to the
centralized algorithm while it has a better sum-rate performance, and
demonstrates a better tradeoff between sum-rate and fairness than the Nash
Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201
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