@article{kaiser_et_al_neuro-fuzzy_2017,
	title = {Neuro-fuzzy selection algorithm for optimal relaying in {OFDM} systems},
	volume = {10},
	issn = {1754-8632},
	url = {https://doi.org/10.1504/IJAACS.2017.084713},
	doi = {10.1504/IJAACS.2017.084713},
	abstract = {Next generation wireless networks will support cooperative communication, where relay nodes receive transmission from a source node and forward it to its destination node. The best relay selection is one of the key concerns to improve the overall performance of the cooperative networks. This paper presents a neuro-fuzzy NF selection algorithm for optimal relaying in OFDM-based cooperative networks. The aim is to select relays based on instantaneous signal-to-noise ratio SNR, link delay propagation and queuing delay and energy saving due to the cooperative diversity. This paper also provides the end-to-end outage probability analysis. The NF-based relay selection algorithm is compared with the blind search, informed search, fuzzy-based search and selection amplify-and-forward AF with power allocation algorithms. The simulation results and complexity analysis show that the proposed algorithm provides substantial performance improvement over the conventional algorithms.},
	number = {2},
	urldate = {2021-03-22},
	journal = {International Journal of Autonomous and Adaptive Communications Systems},
	author = {Kaiser et al., M Shamim},
	year = {2017},
	pages = {213--235},
}

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