Performance Evaluation of XG-PON Based Mobile Front-Haul Transport in Cloud-RAN Architecture

Traffic-Estimation-Based Low-Latency XGS-PON Mobile Front-Haul for Small-Cell C-RAN Based on an Adaptive Learning Neural Network

“…Within this 4 ms, BBU requires around 2.3~2.6 ms [13] to finish preparing and sending the downlink ACK/NACK back to UE in such a way that when it receives the uplink data from UE in sub-frame n, it will send ACK/NACK to the UE in sub-frame n+4. In [8] we have shown that giving the grants to the ONUs based on their buffer occupancy reports, while adjusting the pre-determined limits for congested or heavily-loaded ONUs in the network, can efficiently accommodate the traffic variation of LTE/LTE advance networks (i.e., the actual RRUs traffic load) and attains a considerable delay performance improvement. As a continuation of this work, here we propose predicting the amount of ONU's buffer occupancy in advance based on historical buffer occupancy reports collected during BBU processing time.…”

“…In the C-RAN architecture depicted in Figure 1, the function we are trying to approximate does change over time. This is due to the fact that mobile front-haul traffic transmits via XGS-PON system exhibits a high degree of temporal variation [8]. In order to make our FANN network capable of approximating the changing behavior of this function, we introduce an adaptive learning approach to train the FANN network.…”

“…After receiving the set of predicted ONU reports from the prediction phase, these reports are used to compute and assign the grants for the ONUs in the network. In order to improve the utilization of the XGS-PON upstream bandwidth while optimizing the upstream transmission latency, we propose utilizing our previous grant assignment method, which we refer to as the Optimized-RR DBA algorithm [8], to compute and assign the grants for ONUs. However, instead of using actual or instantaneous ONU reports as inputs to the algorithm, as in [8], we utilize the predicated ONU's reports from the prediction phase as inputs to the algorithm.…”

“…The only works that are fully compatible with XG-PON standard are: (1) Group-Assured Giga-PON Access Network DBA (gGIANT DBA) introduced in [7], which has been proposed to optimize XG-PON average upstream delay to support mobile backhaul; however, the delay requirement for mobile front-haul is much lower than in backhaul case; (2) Our pervious proposal, Optimized Round Robin DBA (Optimized-RR DBA), was introduced in [8] to optimize XG-PON to transport MAC-PHY split-based front-haul traffic in small-cell C-RAN architecture. In [8], a front-haul latency as low as 300 µs was achieved with Optimized-RR DBA; however, taking into account the new emerging 5G QS requirements, front-haul transmission latency should not exceed 250 µs, as recommended by the Next-Generation Mobile Networks Alliance (NGMA) in [9]. Motivated by the above facts, to achieve front-haul transmission latency similar to that recommended by NGMA without modifying current the TDM-PONs and BBU systems' processing and protocols, this paper proposes a traffic-estimation-based low-latency XGS-PON mobile front-haul to support small-cell-based cloud radio access network architecture.…”

“…In XGS-PON standard, the DBA engine at OLT assigns the transmission grants to the ONUs/RRUs based on their buffer occupancy reports or their transmission containers, which are also known as T-CONTs (note: in this paper we assume that the ONU has only one T-CONT, as in [7]; therefore, in this paper we will use the term ONU instead of T-CONT). In [8] we have shown that giving the grants to the ONUs based on their buffer occupancy reports, while adjusting the pre-determined limits for congested or heavily-loaded ONUs in the network, can efficiently accommodate the traffic variation of LTE/LTE advance networks (i.e., the actual RRUs traffic load) and attains a considerable delay performance improvement. As a continuation of this work, here we propose predicting the amount of ONU's buffer occupancy in advance based on historical buffer occupancy reports collected during BBU processing time.…”