12,197 research outputs found
Large deviations sum-queue optimality of a radial sum-rate monotone opportunistic scheduler
A centralized wireless system is considered that is serving a fixed set of
users with time varying channel capacities. An opportunistic scheduling rule in
this context selects a user (or users) to serve based on the current channel
state and user queues. Unless the user traffic is symmetric and/or the
underlying capacity region a polymatroid, little is known concerning how
performance optimal schedulers should tradeoff "maximizing current service
rate" (being opportunistic) versus "balancing unequal queues" (enhancing
user-diversity to enable future high service rate opportunities). By contrast
with currently proposed opportunistic schedulers, e.g., MaxWeight and Exp Rule,
a radial sum-rate monotone (RSM) scheduler de-emphasizes queue-balancing in
favor of greedily maximizing the system service rate as the queue-lengths are
scaled up linearly. In this paper it is shown that an RSM opportunistic
scheduler, p-Log Rule, is not only throughput-optimal, but also maximizes the
asymptotic exponential decay rate of the sum-queue distribution for a two-queue
system. The result complements existing optimality results for opportunistic
scheduling and point to RSM schedulers as a good design choice given the need
for robustness in wireless systems with both heterogeneity and high degree of
uncertainty.Comment: Revised version. Major changes include addition of
details/intermediate steps in various proofs, a summary of technical steps in
Table 1, and correction of typos
Flocking with Obstacle Avoidance
In this paper, we provide a dynamic graph theoretical framework for flocking in presence of multiple obstacles. In particular, we give formal definitions of nets and flocks as spatially induced graphs. We provide models of nets and flocks and discuss the realization/embedding issues related to structural nets and flocks. This allows task representation and execution for a network of agents called alpha-agents. We also consider flocking in the presence of multiple obstacles. This task is achieved by introducing two other types of agents called beta-agents and gamma-agents. This framework enables us to address split/rejoin and squeezing maneuvers for nets/flocks of dynamic agents that communicate with each other. The problems arising from switching topology of these networks of mobile agents make the analysis and design of the decision-making protocols for such networks rather challenging. We provide simulation results that demonstrate the effectiveness of our theoretical and computational tools
Equilibrium Free Energies from Nonequilibrium Processes
A recent result, relating the (irreversible) work performed on a system
during a non-quasistatic process, to the Helmholtz free energy difference
between two equilibrium states of the system, is discussed. A proof of this
result is given for the special case when the evolution of the system in
question is modelled by a Langevin equation in configuration space.Comment: Conference talk in Zakopane, Poland; 11 pages + 3 figure
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
A deterministic algorithm for experimental design applied to tomographic and microseismic monitoring surveys
SUMMARY
Most general experimental design algorithms are either: (i) stochastic and hence give different
designs each time they are run with finite computing power, or (ii) deterministic but converge
to results that depend on an initial or reference design, taking little or no account of the range
of all other possible designs. In this paper we introduce an approximation to standard measures
of experimental design quality that enables a new algorithm to be used. The algorithm
is simple, deterministic and the resulting experimental design is influenced by the full range
of possible designs, thus addressing problems (i) and (ii) above. Although the designs produced
are not guaranteed to be globally optimal, they significantly increase the magnitude of
small eigenvalues in the model–data relationship (without requiring that these eigenvalues be
calculated). This reduces the model uncertainties expected post-experiment. We illustrate the
method on simple tomographic and microseismic location examples with varying degrees of
seismic attenuation
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