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Integrating time-frequency resource conversion (TFRC), a new network resourceallocation strategy, with call admission control can not only increase the cellcapacity but also reduce network congestion effectively. However, the optimalsetting of TFRC-oriented call admission control suffers from the curse ofdimensionality, due to Markov chain-based optimization in a high-dimensionalspace. To address the scalability issue of TFRC, in [1] we extend the study ofTFRC into the area of scheduling. Specifically, we study downlink schedulingbased on TFRC for an LTE-type cellular network, to maximize service delivery.The service scheduling of interest is formulated as a joint request, channeland slot allocation problem which is NP-hard. An offline deflation andsequential fixing based algorithm (named DSFRB) with only polynomial-timecomplexity is proposed to solve the problem. For practical onlineimplementation, two TFRC-enabled low-complexity algorithms, modified Smithratio algorithm (named MSR) and modified exponential capacity algorithm (namedMEC), are proposed as well. In this report, we present detailed numericalresults of the proposed offline and online algorithms, which not only show theeffectiveness of the proposed algorithms but also corroborate the advantages ofthe proposed TFRC-based schedule techniques in terms of quality-of-service(QoS) provisioning for each user and revenue improvement for a serviceoperator.

Simulation Results of User Behavior-Aware Scheduling Based on Time-Frequency Resource Conversion