Dynamic Bandwidth Allocation in Heterogeneous OFDMA-PONs Featuring Intelligent LTE-A Traffic Queuing

Abstract

This work was supported by the ACCORDANCE project, through the 7th ICT Framework ProgrammeA heterogeneous, optical/wireless dynamic bandwidth allocation framework is presented, exhibiting intelligent traffic queuing for practically controlling the quality-of-service (QoS) of mobile traffic, backhauled via orthogonal frequency division multiple access???PON (OFDMA-PON) networks. A converged data link layer is presented between long term evolution-advanced (LTE-A) and next-generation passive optical network (NGPON) topologies, extending beyond NGPON2. This is achieved by incorporating in a new protocol design, consistent mapping of LTE-A QCIs and OFDMA-PON queues. Novel inter-ONU algorithms have been developed, based on the distribution of weights to allocate subcarriers to both enhanced node B/optical network units (eNB/ONUs) and residential ONUs, sharing the same infrastructure. A weighted, intra-ONU scheduling mechanism is also introduced to control further the QoS across the network load. The inter and intra-ONU algorithms are both dynamic and adaptive, providing customized solutions to bandwidth allocation for different priority queues at different network traffic loads exhibiting practical fairness in bandwidth distribution. Therefore, middle and low priority packets are not unjustifiably deprived in favor of high priority packets at low network traffic loads. Still the protocol adaptability allows the high priority queues to automatically over perform when the traffic load has increased and the available bandwidth needs to be rationally redistributed. Computer simulations have confirmed that following the application of adaptive weights the fairness index of the new scheme (representing the achieved throughput for each queue), has improved across the traffic load to above 0.9. Packet delay reduction of more than 40ms has been recorded as a result for the low priority queues, while high priories still achieve sufficiently low packet delays in the range of 20 to 30m

The max–min fair approach on dynamic bandwidth allocation for XG‐PONs

“…In contrast to E-PONs, which have received significant research attention [9][10][11][12][13], a very limited number of XG-PON-oriented DBA algorithms have been presented in the literature [14][15][16][17][18]. In addition, some significant research has been performed over long reach PONs and the adaptation of orthogonal frequency division multiplexing (OFDM) to PONs [19][20][21][22][23]. The authors in [15] propose a DBA algorithm for nested-PONs (G-PON is nested to XG-PON to coexist) that achieves high bandwidth utilisation, user fairness and guaranteed multi-service quality of service (QoS).…”

Dynamic Subcarrier Assignment in OFDMA-PONs Based on Deep Reinforcement Learning

“…In [5], a novel DSA algorithm is proposed that combines traffic prediction technology to reduce latency. A DSA framework based on weight distribution in heterogeneous OFDMA-PON was proposed in [22]. However, in all existing related works, neither the flexible configuration of the SC modulation format nor the ONU transmission power optimization was considered.…”