We experimentally achieve a 19% capacity gain per Watt of electrical supply power in a 12-span link by eliminating gain flattening filters and optimizing launch powers using deep neural networks in
We consider the problem of scheduling data in overloaded networks. We wish to maximize the total profit of data that is served.
We study a model of controlled queueing network, which operates and makes control decisions in discrete time.
We study a model of controlled queueing network, which operates and makes control decisions in discrete time.
A transmission scheme is developed for the downlink frame of cellular networks.
The capacity of the multiple access channel (MAC) has been extensively studied previously.
We present an efficient, semi-optimum data-processing scheme for detecting a deterministic signal in white Gaussian noise and a random transient disturbance which occurs unpredictably and infrequen
In cognitive radio networks, the secondary (unlicensed) users need to find idle channels via spectrum sensing for their transmission.
Viral marketing campaigns seek to recruit the most influential individuals to cover the largest target audience. This can be modeled as the well-studied maximum coverage problem.
Maximum entropy criterion for estimating an unknown probability density function from its moments has been applied to evaluation of average error probability in digital communications.
