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We study resource allocation with multi-unit demand, such as the allocation of courses to students.
In this paper, we study resource allocation in buffer-aided relay-assisted OFDMA networks.
We also conduct an analysis of the Traffic-to-Pilot (T2P) reverse traffic channel (RTC) MAC algorithm implemented in EV-DO Revision-A to study resource allocation for different traffic classes.
Zou et al. [26,27] study resource allocation problem at the PU side in NC-based cognitive cooperative networks, in which PUs assist in the transmission of SUs, and in exchange for this concession, PUs receive payments from SUs for the spectrum and cooperative transmit power being used in cooperation.
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Economics at its core studies resource allocation mechanisms.
Next, we validate and refine these insights by studying resource allocation for the Jakes model.
In this paper, we have studied resource allocation for relayed uplink transmission in OFDMA system.
Zhao et al. studied resource allocation problem in MIMO systems such as time allocation [29] and power allocation [30].
In recent years, there have been several works [7 12] that studied resource allocation in cognitive underlay networks with imperfect CSI.
Zhang et al. [6, 7] studied resource allocation to provide quality of service (QoS) for the users with minimum rate or maximum packet delay requirements.
Considering the network elements, an abstract formulation of the studied resource allocation problem can be given as follows: Fig. 2 Heterogeneous network scenario.
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