Where, P max and P min represent the maximum and minimum power constraints on information decoding, respectively.
The optimization problem in (6) aims at maximizing the energy efficiency subject to the minimum throughput requirement of the femtocells C1 and the maximum power constraint C3.
It is used to find the minimum overall power and minimum power under the constraint that the dose response function is bounded from below by a linear response function.
(iii) We have shown that the original problem is convex and therefore the objective function has a global minima under the power constraint which can be achieved by Algorithm 1.
The optimal transmission power per user, Pmin*, i.e., the minimum power which meets this constraint on outage probability, satisfies the equation Φ o, th − Φ o P m * = 0. (11).
In this section, a brief description of the adopted LPP metric is first given, then the optimization problem (OP) for minimum power consumption under EGP constraint satisfaction is introduced.
We keep the discussion to a minimum as we believe this power constraint to be unrealistic and impractical.
In our study, we focus on the maximization of the average throughput of the secondary system within K time slots under the maximum transmission power constraint, the minimum throughput constraint of SUs, and the interference power constraint defined by PU.
The authors propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO-NOMA system with total transmit power constraint and minimum rate constraint of the weak user.
The main contribution of this article is a method that provides an upper bound to the following OFDMA-SDMA RA problem for mixed RT and nRT traffic: for a given time slot, find the user selection and beamforming vectors that maximize a linear function of the users rates, given a total transmit power constraint and minimum rate constraints for RT users.
