4,319 research outputs found
Joint power and admission control via p norm minimization deflation
In an interference network, joint power and admission control aims to support
a maximum number of links at their specified signal to interference plus noise
ratio (SINR) targets while using a minimum total transmission power. In our
previous work, we formulated the joint control problem as a sparse
-minimization problem and relaxed it to a -minimization
problem. In this work, we propose to approximate the -optimization
problem to a p norm minimization problem where , since intuitively p
norm will approximate 0 norm better than 1 norm. We first show that the
-minimization problem is strongly NP-hard and then derive a
reformulation of it such that the well developed interior-point algorithms can
be applied to solve it. The solution to the -minimization problem can
efficiently guide the link's removals (deflation). Numerical simulations show
the proposed heuristic outperforms the existing algorithms.Comment: 2013 IEEE International Conference on Acoustics, Speech, and Signal
Processin
Time and Location Aware Mobile Data Pricing
Mobile users' correlated mobility and data consumption patterns often lead to
severe cellular network congestion in peak hours and hot spots. This paper
presents an optimal design of time and location aware mobile data pricing,
which incentivizes users to smooth traffic and reduce network congestion. We
derive the optimal pricing scheme through analyzing a two-stage decision
process, where the operator determines the time and location aware prices by
minimizing his total cost in Stage I, and each mobile user schedules his mobile
traffic by maximizing his payoff (i.e., utility minus payment) in Stage II. We
formulate the two-stage decision problem as a bilevel optimization problem, and
propose a derivative-free algorithm to solve the problem for any increasing
concave user utility functions. We further develop low complexity algorithms
for the commonly used logarithmic and linear utility functions. The optimal
pricing scheme ensures a win-win situation for the operator and users.
Simulations show that the operator can reduce the cost by up to 97.52% in the
logarithmic utility case and 98.70% in the linear utility case, and users can
increase their payoff by up to 79.69% and 106.10% for the two types of
utilities, respectively, comparing with a time and location independent pricing
benchmark. Our study suggests that the operator should provide price discounts
at less crowded time slots and locations, and the discounts need to be
significant when the operator's cost of provisioning excessive traffic is high
or users' willingness to delay traffic is low.Comment: This manuscript serves as the online technical report of the article
accepted by IEEE Transactions on Mobile Computin
- β¦