Probabilistic Stone’s Blind Source Separation with application to channel estimation and multi-node identification in MIMO IoT green communication and multimedia systems

Khosravy, Mahdi; Gupta, Neeraj; Patel, Nilesh; Dey, Nilanjan; Nitta, Naoko; Babaguchi, Noboru

doi:10.1016/j.comcom.2020.04.042

Cited by 30 publications

(16 citation statements)

References 29 publications

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“…However, ICA is a heavy-computational algorithm and the requirement of having an optimized system with a trade-of between complexity and eiciency is the motivation to replace ICA with a comparatively eicient and lower complex technique. PS-BSS [28] is the probabilistic version of Stone's BSS. It is irst illustrated briely and then suggested to be a replacement for ICA.…”

Section: Ps-bss Based Mimo Acoustic Ofdm Iout Networkmentioning

confidence: 99%

“…For the details of PS-BSS, see Ref. [28]. Table 3 presents the notations used in description of the PS-BSS.…”

Section: Ps-bss Ps-bss Is An Extension Of Stone's Bssmentioning

confidence: 99%

“…While ICA is a higher-order statistics Blind Source Separation (BSS) technique [19,20], a novel second-order statistics BSS called as Probabilistic Stone's BSS (PS-BSS) has been recently invented and applied to a general case of a blind MIMO-OFDM system [28]. The possible improvements to Stone's BSS was theoretically discussed [25] and a PDF-matched modiication was introduced [24] before the well-clariied probabilistic with extensive analysis on variety range of multimedia data [28]. This paper describes and analyses a blind MIMO-OFDM IoUT network based on PS-BSS.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Underwater IoT Network by Blind MIMO OFDM Transceiver Based on Probabilistic Stone’s Blind Source Separation

Khosravy

Gupta

Dey

et al. 2022

ACM Trans. Sen. Netw.

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Telecommunications systems with Multi-Input Multi-Output (MIMO) structure using Orthogonal Frequency Division Modulation (OFDM) has a great potential of efficient application to a network of Internet of Things (IoT) of a high data rate. When the IoT network is amongst the underwater sensory devices known as the Internet of Underwater Things (IoUT), the electromagnetic wave can not play the role of baseband signal due to rapid fall off inside the water. Thus, Acoustic OFDM is a reliable replacement for conventional OFDM inside the water. A blind structure for MIMO acoustic OFDM using Independent Component Analysis (ICA) brings even further advantages in data rate and energy consumption by avoiding the required pilot and preamble data. This research work presents a blind MIMO Acoustic OFDM blind transceiver for IoUT based on Probabilistic Stone’s Blind Source Separation (PS-BSS). The proposed technique has multiple times lower complexity compared to the ICA-based technique while maintaining a comparable efficiency. As observed in the results carried out one hundred Monte Carlo runs of transmission random data bits, over a highly sparse channel that is the common case of an underwater environment the proposed PS-BSS-based technique dominates the ICA-based one, and as the sparseness of the channel decreases its efficiency is comparable to ICA-based technique. Thus in the case of a high sparse channel, the proposed technique is superior in both aspects of efficiency and complexity while over lower sparseness due to its comparative efficiency it can be hired as an optimum technique fulfilling a fair trade-off between efficiency and complexity.

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Section: Ps-bss Based Mimo Acoustic Ofdm Iout Networkmentioning

confidence: 99%

“…For the details of PS-BSS, see Ref. [28]. Table 3 presents the notations used in description of the PS-BSS.…”

Section: Ps-bss Ps-bss Is An Extension Of Stone's Bssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Underwater IoT Network by Blind MIMO OFDM Transceiver Based on Probabilistic Stone’s Blind Source Separation

Khosravy

Gupta

Dey

et al. 2022

ACM Trans. Sen. Netw.

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show abstract

“…Metaheuristic methods are in favour for solving high complicated optimization problems [1,2], and have been used in a wide range of industrial applications from electrocardiogram pre-processing [3] and renewable energies [4] to optimum structure design of artificial intelligence for lightweight end-devices [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Study of Crossover Operators in Genetic Algorithms

Singh

Gupta

2021

Springer Tracts in Nature-Inspired Computing

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“…Today, automation is called the third industrial revolution [2] wherein we currently live and experience its impact on people's life. However, the forth revolutionary phenomenon approaching us by novel information and communication trends in which IoT is the sharp edge of this development [3][4][5][6]. As IoT technologies pass through their development and gradual implementation, their efficiency is subject to improvement via different approaches.…”

Section: Introductionmentioning

confidence: 99%