Dynamic Bandwidth Allocation for OFDMA-PONs Using Hidden Markov Model

Lim, Wansu; Kourtessis, Pandelis; Senior, John M.; Na, Yongsoo; Allawi, Yazan M.; Jeon, Seong-Bae; Chung, Hae

doi:10.1109/access.2017.2657549

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…Advantages of using PON include large coverage area, reduced fiber deployment, multicast and broadcast capabilities, reduced cost of maintenance, and ease of upgrades to higher bit rate [2]. However, with the rapid development of network technology and digital services, to better support the high quality of service (QoS) requirements of access networks, PON needs a higher data access rate [3][4][5]. The wavelength division multiplexing passive optical network (WDM-PON) has been proposed as a candidate solution, which provides a logic end-to-end wavelength connection for each user [1].…”

Section: Introductionmentioning

confidence: 99%

“…However, the spectrum efficiency of OCDMA-PON is lower because it is based on the spread-spectrum technique. Hence, the orthogonal frequency division multiple access passive optical network (OFDMA-PON) that enables the sharing of sub-wavelength resources in the frequency domain is proposed to address the effective bandwidth allocation [1,3,5,[8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Many solutions have been proposed to reduce the cost of OFDMA-PON [1,3,5,[10][11][17][18][19][20][21]. In media access control (MAC) layer, a DSA algorithm was proposed in [1] to schedule the ONU upstream transmission based on its instantaneous bandwidth requirements and the existing traffic conditions.…”

Section: Introductionmentioning

confidence: 99%

“…A fair-aware DSA algorithm in a distance adaptive OFDMA-PON was proposed in [21]. 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].…”

Section: Introductionmentioning

confidence: 99%

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

Zhu

Chen

et al. 2022

IEEE Photonics J.

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Orthogonal Frequency Division Multiplexing Access Passive Optical Networks (OFDMA-PONs), a solution for the next-generation optical access network, allows multiple optical network units (ONUs) to dynamically share subcarriers (SCs) to support efficient bandwidth allocation. In uplink transmission, multiple ONUs can share orthogonal low bit rate SCs to transmit data at different time slots (TSs) during the transmission cycle. In this paper, the dynamic subcarrier allocation (DSA) scheme based on deep reinforcement learning (DRL) is proposed for various ONU bandwidth requests. The novel scheme jointly allocates time slots, subcarriers, and modulation formats in a dynamic and flexible manner. The ONU can save transmit power by using a lower order modulation format while meeting the delay requirement. The simulation part demonstrates how the proposed DRL-based DSA scheme can be adapted to various situations, including 1) variation in the size of ONU bandwidth requests, and 2) variation in the weight of different indicators. The extensive simulation results show that, for the first time, the proposed DRL-based DSA algorithm achieves optimal traffic latency with substantial power saving, compared with the traditional two-dimensional DSA algorithms.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Zhu

Chen

et al. 2022

IEEE Photonics J.

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“…Based on the HMM, he designed an LQG optimal controller to assure system stability. W. Lim, et al [11], the authors proposed a dynamic bandwidth allocation strategy for orthogonal frequency division Bulletin of Electr Eng & Inf ISSN: 2302-9285  Optimal resource allocation in networked control systems using viterbi algorithm (Gökhan Çetin)…”

Section: Introductionmentioning

confidence: 99%

Optimal resource allocation in networked control systems using viterbi algorithm

Cetin

Fadali

2021

Bulletin EEI

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This paper presents an optimal bandwidth allocation method for a networked control system (NCS) which includes time-driven sensor, event-driven controller and random channels. A hidden markov model (HMM) with a discretized state space is formulated for the random traffic to predict the network states using a suitable data window. Network bandwidth is allocated based on the predicted traffic state subject to bounds on the deterministic traffic that guarantee acceptable NCS performance and do not exceed hardware limitations. Bandwidth allocation uses minimization of unmet bandwidth demand. A stability condition is derived for a variable but bounded sampling period interval. Computer simulation results show the effect of varying the number of discrete states for the HMM and the window width on bandwidth allocation. The results compare favorably with a published approach based on fuzzy logic.

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A Prediction Approach to End-to-End Traffic in Space Information Networks

Jiang

Huo

2019

Mobile Netw Appl

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Dynamic Bandwidth Allocation for OFDMA-PONs Using Hidden Markov Model

Cited by 9 publications

References 5 publications

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

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

Optimal resource allocation in networked control systems using viterbi algorithm

A Prediction Approach to End-to-End Traffic in Space Information Networks

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