A User-QoE Aware Scheduling Scheme in HetNets

Song, Xin; Qin, Lei; Ni, Yue; Xie, Zhigang

doi:10.1109/icmcce.2018.00131

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…The proposed demand-based user scheduling follows a very simple approach [55], which is detailed in Procedure (2). In particular, the users with larger queue size are scheduled with priority in an attempt to maintain queue stability.…”

Section: E Demand Based User Schedulingmentioning

confidence: 99%

Interference-Aware Demand-Based User Scheduling in Precoded High Throughput Satellite Systems

Honnaiah

Lagunas

Chatzinotas

et al. 2022

IEEE Open J. Veh. Technol.

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In recent years, dynamic traffic demand requisites have driven the satellite communication service providers to implement reconfigurable demand-driven features to align the delivered throughput with the temporal and geographical variations of the traffic demand. Also, in current interference-limited High Throughput Satellite (HTS) systems, the resulting inter-beam co-channel interference can be mitigated by carefully performing precoding and user scheduling. Unfortunately, the conventional user scheduling algorithms fail to provide demand satisfaction for dynamic traffic demand requisites. Hence, in this paper, we focus on the user scheduling design for precoded satellite systems where both co-channel interference and user demands are taken into account. In particular, we first classify the sectors in each beam according to the interference they may cause to neighboring beams. Next, we formulate the scheduling problem such as the activation of neighboring beam sectors is avoided while proportionally dwelling on the sectors based on their traffic demands. The supporting numerical results for different demand distribution profiles validate the effectiveness of proposed interference-aware demand-based user scheduling over conventional scheduling techniques.INDEX TERMS Multi-beam high throughput satellite systems, beam pattern, beam footprint, DVB-S2X, precoding.

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Section: E Demand Based User Schedulingmentioning

confidence: 99%