Adaptive modulation allocation algorithm in elastic optical networks

Bandiri, Sabi Y. M.; Pimenta, Tales Cleber; Durand, Fábio Renan; Spadoti, Danilo H.

doi:10.1002/dac.4581

Cited by 2 publications

(2 citation statements)

References 30 publications

(38 reference statements)

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“…Bandiri et al introduced a new way to allocate the modulation format and improve the energy efficiency in elastic optical networks. The energy efficiency was improved by up to 27%, the used bandwidth available was reduced by up to 60%, and the blocking probability was decreased by 30% using the proposed adaptive algorithm 4 . However, if more spectrum resources cannot be obtained, it is challenging to exceed a transmission rate of 10 GB/s, even though the multiple‐input multiple‐output (MIMO) method is used.…”

Section: Introductionmentioning

confidence: 99%

“…The energy efficiency was improved by up to 27%, the used bandwidth available was reduced by up to 60%, and the blocking probability was decreased by 30% using the proposed adaptive algorithm. 4 However, if more spectrum resources cannot be obtained, it is challenging to exceed a transmission rate of 10 GB/s, even though the multiple-input multiple-output (MIMO) method is used. Therefore, it is necessary to use a higher carrier frequency, that is, the terahertz (THz) frequency that increases the channel bandwidth and provides sufficient transmission capacity.…”

Section: Introduction 1| Backgroundmentioning

confidence: 99%

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A novel method to reduce indoor signal power fluctuation using multiple adaptive terahertz sources

Liang

Jing

Zhong

2022

Int J Communication

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Summary The indoor terahertz sources cause power fluctuation at various locations due to obstacles, which can be avoided by deploying multiple sources, but will lead to high energy consumption. In this paper, the reverse ray‐tracing method is used to establish a terahertz indoor channel. The free path loss, atmospheric absorption, and reflection loss are considered. Adaptive algorithms are adopted to solve the large energy consumption of deploying multiple sources. A weight vector coefficient is used based on the location and received user signal to adjust the transmission power of each terahertz source dynamically. The results show that the adaptive power control of multiple terahertz sources substantially reduces the energy consumption and the signal power fluctuations. For static users, the energy consumption can be reduced by 5 and 9 dB, and the maximum data transmission rate can be increased by one to two times using four and nine sources, respectively. Moreover, energy consumption can be reduced by more than 6 dB for several indoor users. For dynamic users with a changing channel environment, the adaptive algorithm can adjust the source power in real time and improve signal efficiency. However, the efficiency improvement of the algorithm is limited by the distribution of the multiple sources. The energy consumption of four sources with the adaptive algorithm operating in the center of the room is greater than that of nine sources without the adaptive algorithm. Nevertheless, the efficiency of the nine sources with the adaptive algorithm is much higher than that of the four sources.

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Section: Introductionmentioning

confidence: 99%

Section: Introduction 1| Backgroundmentioning

confidence: 99%