In the HetNet, the problem of RB allocation and uplink power control of all users is formulated as a weighted sum rate maximization problem.
Multiple antenna systems with finite-rate CSI feedback were formulated as a generalized fixed-rate vector quantization problem in [19] and analyzed by adapting tools from high resolution quantization theory.
By employing the general framework described in Section 2, the finite-rate quantized MISO beamforming system can be formulated as a general fixed-rate vector quantization problem by adopting a direct mapping between CSI and source variables, given by.
The gradual rate shift in a covarion context can be formulated as a Markov model of rate switching between different rate classes, usually eight or less.
It is worth noting that the radio resource allocation problem is generally formulated as a weighted sum-rate maximization (WSRMax) problem, which has attracted a lot of attentions recently.
Specifically, the channel quantization was formulated as a general finite-rate vector quantization problem with attributes tailored to meet the general issues that arise in feedback based communication systems, including encoder side information, source vectors with constrained parameterizations, and general non-mean-squared distortion functions.
The total damage growth rate has been formulated as a function of the current stress state and the rate of martensitic transformation such that the magnitude of recoverable transformation strain and the complete or partial nature of the transformation cycles impact the total cyclic life as per experimental observations.
The overall resource allocation problem is formulated as a Utility-based uplink Power and Rate Allocation game in Multi-Service two-tier Femtocell networks (UPRA-MSF), where each user aims selfishly at maximizing his utility-based performance.
With the introduced pricing function, which uses the occupied spectrum to describe the cost in data transmission, rate allocation is formulated as a concave optimization problem and the explicit solution has been obtained.
For instance, in [14], the power control problem for rate maximization is formulated as a convex problem and its solution is found via geometric programming (GP) for wireless networks.
By disseminating the so-called "virtual buffers" throughout the nodes of a hybrid wired and code division multiple access (CDMA) wireless cellular network with a distributed algorithm, joint transmission power and rate optimization is formulated as a network utility maximization problem which can be solved by the congestion control algorithms of TCP [39].
