Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system

Bouchibane, Fatima Zohra; Bensebti, Messaoud

doi:10.1504/ijwmc.2018.095664

Cited by 5 publications

(3 citation statements)

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“…It is considered that a fitter feasible solution will encounter superior fitness and will thus draw more bees to feed at this food source 33 . Bouchibane et al 38 proposed an iterative bee colony algorithm that evaluates the food when it is received according to the present food. The generalized artificial bee colony foraging cycle has been demonstrated in Figure 4.…”

Section: Partial Transmit Sequence (Pts) Technique and Algorithm Bee Optimizermentioning

confidence: 99%

“…ABC is a very efficient optimization algorithm as it has fewer tuning parameters and excellent exploration ability as described in References 34‐37. Bouchibane et al in Reference 38 used ABC for the optimization of MIMO‐OFDM in terms of optimal antenna count at the transmitting end. Overall, it has been analyzed that various ABC versions have been employed for attaining different objectives.…”

Section: Introductionmentioning

confidence: 99%

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Peak to average power ratio alleviation by utilizing swarm intelligence along with machine learning for multiple input multiple output‐orthogonal frequency division multiplexing based underwater acoustic communication system

BanooriFarhad

ShiJinglun

ArshadJehangir

et al. 2021

Trans Emerging Tel Tech

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An underwater acoustic (UWA) network uses multiple input multiple output‐orthogonal frequency division multiplexing (MIMO‐OFDM) to achieve high data rate with high amplitude that results in terms of augmented peak to average power ratio (PAPR). This significant PAPR deemed as a stumbling block to degrade the performance of MIMO‐OFDM in UWA communication by causing nonlinear distortion within the high‐power amplifier (HPA). While PAPR mitigation techniques have been suggested for the single input single output UWA case, there has been limited research work on controlling the PAPR dilemma in the MIMO‐OFDM UWA case. To address this flaw, this article proposes a modified behavior of the artificial bee colony algorithm at the transmission end, which is further cross‐verified using machine learning techniques. The simulation results show that the proposed technique outperforms current state‐of‐the‐art PAPR diminishing methods, which is further enhanced in accordance with varying neuron counts and population size. Following that, we also analyzed and compared energy efficiency and performance gain of our proposed technique along with various advanced techniques. Furthermore, a desirable ratio between new and trained data was obtained to improve network efficiency by keeping PAPR values low.

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Section: Partial Transmit Sequence (Pts) Technique and Algorithm Bee Optimizermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Peak to average power ratio alleviation by utilizing swarm intelligence along with machine learning for multiple input multiple output‐orthogonal frequency division multiplexing based underwater acoustic communication system

BanooriFarhad

ShiJinglun

ArshadJehangir

et al. 2021

Trans Emerging Tel Tech

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“…BeeFitnessTable Table 2. shows the bee fitness table [21]. Algorithm 3 takes the node structure and finder node as input.…”

Section: Proposed Frameworkmentioning

confidence: 99%

An Energy Efficient Enhanced Hybrid Routing Protocol for MANET utilizing Artificial Bee Colony

Vandana¹,

Kaur²

2019

IJITEE

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Mobile Ad hoc Network (MANET) is a self-organized wireless network with no central control station or no rigid infrastructure. The main objective of the ad hoc network is that the nodes move arbitrarily that needs the routing protocols to rapidly counter the change of network topology. Limited energy resource availability is the core issue in MANET. For energy efficiency enhancement, this research has acquainted a hybrid routing algorithm which is an amalgamation of Ad hoc On-Demand Distance Vector Routing (AODV) and Temporally-Ordered Routing Algorithm (TORA) routing protocols for the route discovery process using Low Energy Adaptive Clustering Hierarchy (LEACH). Artificial Bee Colony (ABC) algorithm has been used for the optimization if some sort of distortion occurs within the network. The simulation has been executed in MATLAB simulation tool using QoS parameters, such as throughput, energy consumption, PDR and delay. Comparative analysis has been done to portray the proposed work effectiveness.

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A deep learning-based antenna selection approach in MIMO system

2023

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Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system

Cited by 5 publications

References 0 publications

Peak to average power ratio alleviation by utilizing swarm intelligence along with machine learning for multiple input multiple output‐orthogonal frequency division multiplexing based underwater acoustic communication system

Peak to average power ratio alleviation by utilizing swarm intelligence along with machine learning for multiple input multiple output‐orthogonal frequency division multiplexing based underwater acoustic communication system

An Energy Efficient Enhanced Hybrid Routing Protocol for MANET utilizing Artificial Bee Colony

A deep learning-based antenna selection approach in MIMO system

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