Dynamic TWDM-PON for Mobile Radio Access Networks

Iida, Daisuke; Kuwano, Shigeru; Kani, Jun‐ichi; Tanida, Jun

doi:10.1364/oe.21.026209

Cited by 60 publications

(23 citation statements)

References 3 publications

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“…The processing delays in the OLT and ONU are not considered. The P-ONUs are given a fixed bandwidth allocation (FBA) and the S-ONUs are given a typical dynamic bandwidth allocation (DBA) [9]. In the MAC-PHY split, it is assumed that the signal is packetized in the Ethernet frame.…”

Section: Proposed Systemmentioning

confidence: 99%

Numerical analysis on accommodation of TDD-based fronthaul and secondary services in a TDM-PON

Hisano

Shimada

et al. 2017

IEICE ComEX

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We propose a bandwidth allocation technique for accommodating a time division duplex mobile base station (TDD-BS) and a secondary system in a TDM-PON. Operating availability is confirmed with essential three types of TDD configuration taken from the seven types described by the Third Generation Partnership Project (3GPP) standardization group. We evaluate the latency of the TDD-BS and the throughput of the secondary system. We report that the TDD-BS signal is forwarded in less than about 50 µs and is unaffected by the secondary system. The throughput of the secondary system is improved compared with that of the conventional technique. Keywords: TDM-PON, bandwidth allocation, mobile fronthaul, 5G Classification: Fiber-Optic Transmission for Communications References[1] NTT DOCOMO, "DOCOMO 5G white paper, 5G radio access: requirements, concept and technologies," White Paper, Jul. 2014.

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Section: Proposed Systemmentioning

confidence: 99%

Numerical analysis on accommodation of TDD-based fronthaul and secondary services in a TDM-PON

Hisano

Shimada

et al. 2017

IEICE ComEX

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“…Authors in [31] propose a dynamic resource allocation scheme to maintaining the call quality through the resource constraint expedited forwarding queue of the digital subscriber line access multiplexers (DSLAMs). Whereas in [32] and [35], fibre-based dynamic multiplexing is used to distribute mobile fronthaul/backhaul capacity according to the changing radio traffic demand. Dynamic self-backhauling in a mmWave transport network is studied in [33], which requires that the routeing metric of a given link be dependent on other links' status (due to interference).…”

Section: A Dynamic and Adaptive Routeingmentioning

confidence: 99%

A Distributed SON-Based User-Centric Backhaul Provisioning Scheme

et al. 2016

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5G definition and standardization projects are well underway, and governing characteristics and major challenges have been identified. A critical network element impacting the potential performance of 5G networks is the backhaul, which is expected to expand in length and breadth to cater to the exponential growth of small cells while offering high throughput in the order of gigabit per second and less than 1 ms latency with high resilience and energy efficiency. Such performance may only be possible with direct optical fiber connections that are often not available country-wide and are cumbersome and expensive to deploy. On the other hand, a prime 5G characteristic is diversity, which describes the radio access network, the backhaul, and also the types of user applications and devices. Thus, we propose a novel, distributed, selfoptimized, end-to-end user-cell-backhaul association scheme that intelligently associates users with candidate cells based on corresponding dynamic radio and backhaul conditions while abiding by users' requirements. Radio cells broadcast multiple bias factors, each reflecting a dynamic performance indicator (DPI) of the end-to-end network performance such as capacity, latency, resilience, energy consumption, and so on. A given user would employ these factors to derive a user-centric cell ranking that motivates it to select the cell with radio and backhaul performance that conforms to the user requirements. Reinforcement learning is used at the radio cells to optimise the bias factors for each DPI in a way that maximise the system throughput while minimising the gap between the users' achievable and required end-to-end quality of experience (QoE). Preliminary results show considerable improvement in users' QoE and cumulative system throughput when compared with the state-of-the-art user-cell association schemes.INDEX TERMS Backhaul, fronthaul, user-centric, user-cell association, SON, reinforcement learning, multiple attribute decision making.

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“…Recently, large-scale deployment of PONs significantly releases the capacity pressure of the access network [32,33]. TWDM-PON is emerging as a potential candidate to transfer data between centralized BBUs and distributed RRUs with strong ability of transmission [34]. As shown in Fig.…”

Section: Inlp Model Formulation For Comp-oriented Fronthaulmentioning

confidence: 99%

Efficient resource allocation for passive optical fronthaul-based coordinated multipoint transmission

Wang

et al. 2016

J Wireless Com Network

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The centralized processing in cloud radio access network enables cooperation between baseband processing units (BBUs) like inter-cell interference (ICI) cancellation on the basis of coordinated multipoint (CoMP). Large amounts of the sharing data will be transmitted through fronthaul transport network. In the paper, both integer non-linear programming (INLP) optimization model and adaptive genetic algorithm (GA) are explored to release the capacity pressure of the fronthaul transport network when CoMP is introduced. We also consider the resource allocation problem of the passive optical fronthaul network. The proposed algorithm tries to reduce the downlink bandwidth and improve the optical resource allocation efficiency of the optical fronthaul with minimal influence on the fronthaul topology. During the simulations, three critical factors are considered: (1) the number of cell edge users, (2) the average traffic demand of cell edge users, (3) the size of cell cluster used to enable the CoMP. The simulation results show that the most efficient bandwidth saving and optical resource allocation can be achieved with INLP, while the proposed adaptive GA nearly has the same performance with low computational complexity and fast convergence, which is more applicable for the large-scale fronthaul network. Furthermore, the load difference of the fronthaul transport network can be further reduced.

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Dynamic TWDM-PON for Mobile Radio Access Networks

Cited by 60 publications

References 3 publications

Numerical analysis on accommodation of TDD-based fronthaul and secondary services in a TDM-PON

Numerical analysis on accommodation of TDD-based fronthaul and secondary services in a TDM-PON

A Distributed SON-Based User-Centric Backhaul Provisioning Scheme

Efficient resource allocation for passive optical fronthaul-based coordinated multipoint transmission

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