FPGA Design of an Efficient EEG Signal Transmission Through 5G Wireless Network Using Optimized Pilot Based Channel Estimation: A Telemedicine Application

Kumar, K. B. Santhosh; Sujatha, B.

doi:10.1007/s11277-021-09305-2

Cited by 7 publications

(4 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pilot-based techniques have been widely used for estimating the communication channel characteristics between the sending node and the gateway [13], [14]. In [13], where the focus of the paper is on exploring the potential utilization of optical wireless channels in WBANs, both the sending node and the gateway periodically exchange pilot symbols.…”

Section: Related Work a Channel Prediction Modelsmentioning

confidence: 99%

“…This facilitates channel estimation at the gateway to obtain channel characteristics accurately for the sensor-gateway link. Notably, an optimal pilot-based channel estimation technique is proposed in [14] specifically for EEG signal transmission, aiming to mitigate channel-induced decoding errors at the receiver. However, it is important to acknowledge that pilot symbols necessitate the allocation of a dedicated portion of the available bandwidth or time resources for transmission, which might be less desirable in WBANs characterized by highly time-varying channels.…”

Section: Related Work a Channel Prediction Modelsmentioning

confidence: 99%

“…Using this loop, the components in the higher step are available at the beginning of each step. In each step represented by τ , there is another loop (line [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] where the probability of transition from each channel state k ∈ {1, . .…”

Section: Efficient Calculation Of Channel Transition Probabilities Us...mentioning

confidence: 99%

See 2 more Smart Citations

Power-Adaptive Communication With Channel-Aware Transmission Scheduling in WBANs

Arghavani,

Zhang,

Huang

et al. 2024

IEEE Internet Things J.

View full text Add to dashboard Cite

Radio links in Wireless Body Area Networks (WBANs) are highly subject to short and long-term attenuation due to the unstable network topology and frequent body blockage. This instability makes it challenging to achieve reliable and energy-efficient communication, but on the other hand, provides a great potential for the sending nodes to dynamically schedule the transmissions at the time with the best-expected channel quality. Motivated by this, we propose IGE (Improved Gilbert-Elliott Markov chain model), a memory-efficient Markov chain model to monitor channel fluctuations and provide a long-term channel prediction. We then design ATPS (Adaptive Transmission Power Selection), a deadline-constrained channel scheduling scheme that enables a sending node to buffer the packets when the channel is bad and schedule them to be transmitted when the channel is expected to be good within a deadline. ATPS can self-learn the pattern of channel changes without imposing a significant computation or memory overhead on the sending node. We evaluate the performance of ATPS through experiments using TelosB motes under different scenarios with different body postures and packet rates. We further compare ATPS with several state-of-the-art schemes including the optimal scheduling policy in which the optimal transmission time for each packet is calculated based on the collected RSSI (Received Signal Strength Indicator) samples in an off-line manner. The experimental results reveal that ATPS performs almost as efficiently as the optimal scheme in high-date-rate scenarios and has a similar trend on power level usage.

show abstract

Section: Related Work a Channel Prediction Modelsmentioning

confidence: 99%

Section: Related Work a Channel Prediction Modelsmentioning

confidence: 99%

Section: Efficient Calculation Of Channel Transition Probabilities Us...mentioning

confidence: 99%

See 1 more Smart Citation

Power-Adaptive Communication With Channel-Aware Transmission Scheduling in WBANs

Arghavani,

Zhang,

Huang

et al. 2024

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…The expansion in mobile phone usage and other personal communication gadgets for data and voice transmission worldwide has added to the strain on the wireless broadband communication infrastructure [10]. These systems have become the subject of more intensive investigation both in academic and industrial sectors as a result of this high bandwidth rate [11], less BER, and low delay [12], which are accomplished by wireless applications for data and voice given the enormous volume of traffic in the wireless communication medium for data communication [13].…”

Section: Introductionmentioning

confidence: 99%

A Novel Intelligent Channel Estimation Strategy for the 5G Wireless Communication Systems

Lakshmi

Vijayalakshmi

Naveena

2023

Wireless Pers Commun

View full text Add to dashboard Cite

Nowadays, the Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) is an important method used in wireless communications, especially in 5G cellular communications. As in a wireless network, the input signals pass through a channel, and the input signal undergoes phase shift, attenuation, and interference. So, the password from the user side and the received signals are not the same. Thus, an effective channel estimator is essential to make cellular communication better. Hence, a novel hybrid technique called Chimp-based CatBoost channel estimation (CbCBCE) was proposed. This technique is the combination of the Chimp optimization algorithm and CatBoost algorithm. The channel parameters are estimated and then reduced using the Chimp optimization algorithm. Finally, the proposed model is validated with the case study. Then, the result of the proposed model was estimated, and it was compared with other existing techniques. It is observed that the outcome of the proposed design is more compared with the other conventional methods. The presented model is executed in the MATLAB platform, and it is proved that the proposed model has high throughput, high energy efficiency, less BER, and a high data transfer rate.

show abstract

Biosignal encryption algorithm based on Ushio chaotic map for e-health

Murillo-Escobar

Quintana-Ibarra

Cruz-Hernández

et al. 2022

Multimed Tools Appl

View full text Add to dashboard Cite

FPGA Design of an Efficient EEG Signal Transmission Through 5G Wireless Network Using Optimized Pilot Based Channel Estimation: A Telemedicine Application

Cited by 7 publications

References 34 publications

Power-Adaptive Communication With Channel-Aware Transmission Scheduling in WBANs

Power-Adaptive Communication With Channel-Aware Transmission Scheduling in WBANs

A Novel Intelligent Channel Estimation Strategy for the 5G Wireless Communication Systems

Biosignal encryption algorithm based on Ushio chaotic map for e-health

Contact Info

Product

Resources

About