It is implied from Figures 2, 3, 4, and 5 that our proposed approaches equip network operators with different design options each of which presents a different tradeoff between throughput and fairness for the users.
For cellular systems, two performance metrics namely average cell throughput and user throughput at the cell edges are vital.
Besides, by manipulating the amount of budget available for each user, the SABG can enjoy a good trade-off between throughput and spectrum fairness.
In this game, each user controls its own input rate so as to optimize a desired tradeoff between throughput and delay.
Thus, an interaction exists plausibly between throughput and communication.
In addition, under the full buffer model, the gradient scheduler exhibits a trade-off between average user throughput and the user throughput at 5% outage.
With the full buffer model, a gradient scheduling algorithm exhibits a trade-off between average user throughput and the user throughput at 5% outage.
The results also show that with the full buffer model a gradient scheduler exhibits a trade-off between average user throughput and the user throughput at 5% outage, but it does not when the more realistic finite buffer is used.
Then, the results show that under the full buffer traffic model there exists a trade-off between the average user throughput and the user throughput at 5% outage, but under the finite buffer model this trade-off does not exist because the user throughput at 5% outage presents an optimum performance in the range α ≈ [0.75-1].
Nash bargaining solution (NBS) fairness and proportional fairness (PF) are two suitable candidates for fairness consideration, and both can provide attractive trade-offs between total throughput and each user's capacity.
