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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 4  |  Issue : 1  |  Page : 7-15

Ultra-wideband transceiver model for wireless body area network applications


1 Department of Electrical Engineering, AL-Hikma University, Baghdad, Iraq
2 Department of Electrical Engineering, University of Nairobi, Nairobi, Kenya

Date of Submission14-Nov-2018
Date of Acceptance15-Dec-2018
Date of Web Publication20-Feb-2019

Correspondence Address:
Dr. Mohanad Abdulhamid
AL-Hikma University, Baghdad
Iraq
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijas.ijas_16_18

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  Abstract 


The major constraints in the design of wireless body area network (WBAN) can be attributed to the battery autonomy, need for high data rate services, and low interference from the devices operating within the industrial, scientific, and medical (ISM) bands. To meet the demand for high data rate services and low power spectral density to avoid ISM band interference, an ultra-wideband (UWB) system-based technology has been proposed. This study focuses on the design and demonstration of an UWB modem to be used in the WBAN applications and the evaluation of its performance in near-real-world scenarios affected by additive white Gaussian noise interference. The modem is tested with different values of signal-to-noise ratio (SNR). Results show that the performance of the modem degrades as the value of SNR decreases.

Keywords: Bit error rate, ultra-wideband transceiver, wireless body area network


How to cite this article:
Abdulhamid M, Sewe OB. Ultra-wideband transceiver model for wireless body area network applications. Imam J Appl Sci 2019;4:7-15

How to cite this URL:
Abdulhamid M, Sewe OB. Ultra-wideband transceiver model for wireless body area network applications. Imam J Appl Sci [serial online] 2019 [cited 2019 May 19];4:7-15. Available from: http://www.e-ijas.org/text.asp?2019/4/1/7/252591




  Introduction Top


The advancement in technology can also be seen in the miniaturization of electronic devices, sensors, battery, and wireless communication, which have led to the development of wireless body area network (WBAN). WBAN in simple terminology can be described as a network around the body which consists of smart miniaturized devices that are able to sense, process, and communicate.[1]

Typical body area network kits consist of battery, sensor, signal processor, and a transceiver (modem).[1] A modem is a device that modulates an analog signal, encodes it then transmits it; at the same time, the modem receives the signal, decodes it, and demodulates it. The main objective of a transceiver is to produce a signal that can be transmitted easily and then decode it to produce the original signal.

The applications of WBAN include health-care applications, military applications, lifestyle and sports, and monitoring of persons operating in harsh or hostile environments.

Health-care applications are typically associated with low data rates needed to communicate vital data about human health, for example, heart rate, brain activity, blood pressure, muscle activity, blood sugar level, body temperature, levels of oxygen in the blood, and motion, and the BAN allows reliable monitoring and data transfer for patients without interfering with their mobility.[1],[2],[3]

In the military applications, a battle dress uniform is integrated with a BAN that connects devices such as life-support sensors, cameras, and health monitoring global positioning system. These devices relay real-time information. Future advancements will include missile detection sensors, and this will indeed revolutionize warfare.[1],[2],[3]

Lifestyle and sports are revolutionized since new services such as wearable entertainment systems, navigation support in the car or while walking, museum or city guide, heart rate and performance monitoring in sports using muscle activity sensors are made possible by the BAN technology.

In monitoring of persons operating in harsh or hostile environments, there are professions or jobs that require the integration of BAN, for example, miners and firefighters to monitor their health and also improve the general working conditions.

Because of the rather simple hardware realizations and the energy efficiency, ultra-wideband (UWB) communication has become one promising technology for the use in WBAN. UWB technology provides the high rate of data transmission due to its relatively large bandwidth of transmission. UWB spans a frequency range of 3.1GHz to 10.6 GHz with a transmission bandwidth of more than 20% of its center frequency, i.e., more than 500 MHz. Based on this transmission bandwidth, it can be seen that the white Gaussian channel capacity of a UWB system is large for a given signal-to-noise ratio (SNR) according to the Shannon–Hartley law. Some works related to the use of UWB system in WBAN applications are found in literatures.[4],[5],[6],[7]


  Ultra-Wideband Modem Design Top


Since the WBAN sensors have an integrated signal processing chips, the input to the transceiver is in digital form; hence, no need to include source coding as part of the transceiver design. The physical UWB transceiver design simulation which is done in MATLAB Simulink includes:

  1. Random binary generator
  2. Concatenated codes
  3. Quadrature phase-shift keying (QPSK) modulator/demodulator
  4. Orthogonal frequency division multiplexing (OFDM) transceiver
  5. Channel.


Random binary generator

The Bernoulli binary generator is used to generate random binary digits using the Bernoulli distribution. It produces a zero bit (0) with a probability of P and one bit (1) with a probability of 1-p.

In this case, an equiprobable situation is simulated where both “0” and “1” are produced with a probability of 0.5. The output of this generator is frame based having 256 bits per frame at a sampling rate of 1/528 MHz.

Concatenated codes

In wireless communications, burst errors occur due to the reflection of the symbols on large surfaces, for example, buildings, trees, and hills; in addition, random errors also occur due to the thermal noise generated in the electronic circuitry. This calls for a coding scheme with a large codeword length. A serial concatenation of codes is most commonly used for power-limited systems.

In this case, a (48, 32, 8) Reed–Solomon (R-S) code (outer code) with symbols over GF (28) and a (2, 1) convolution code of constraint length 7 were used.

Reed–Solomon coding/decoding

A (48, 32, 8) R-S code over GF (28) was obtained by code shortening scheme of puncturing (zero padding) as shown in [Figure 1] in a MATLAB Simulink model. This code corrects up to eight symbol errors of the 48 symbols.
Figure 1: Reed–Solomon encoder

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Since R-S encoder is a nonbinary coding scheme, the 256-bit frame from the Bernoulli generator is converted to integers using bit to integer converter of 8, resulting into 32 bytes which is the input sequence to the R-S encoder subsystem.

The 32-byte sequence is zero padded to 239 message bytes which is then fed to the integer input R-S encoder. This block adds 16 parity check bytes to give 255 codeword length. Since we are interested in the 48 code words, the zero-padded 255 codewords are passed through a selector to give the 48 code words, and hence, a (48, 32, 8) R-S code is achieved from the (255, 239, 8) R-S code. The 48 bytes is converted back to binary to give 384 bits which is passed through to the convolution encoder.

In the decoder shown in [Figure 2], the 384 bits is converted to bytes, zero padded, and fed to the decoder which decodes the message, i.e., corrects any error introduced during the transmission and removes the parity check bits. The zero-padded 239 message digits from the decoder are passed through a selector to obtain the 32 original message digits which are then converted back to binary.
Figure 2: Reed–Solomon decoder

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Convolution coding/Viterbi decoding

This convolution code has an information rate of ½ and constraint length of 7. It uses the poly2trellis (7, [171 133]) function to create a trellis using the constraint length, code generator (octal), and feedback connection (octal). As can be seen from [Figure 3], output (a, b) = input (x1, x2)
Figure 3: Poly2trellis (7,[171 133]) structure

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Where,

x1= (1111001) = (171)8

x2= (1011011) = (133)8

The Viterbi decoder also uses the same poly2trellis function while decoding the information transmitted. Since the information rate is ½, this implies that for every one bit, two codewords are produced, and hence, the output of the convolution encoder is 768 bits. The Viterbi decoder detects and corrects the random errors and removes the parity check bits, and hence, its output is 384 bits.

Quadrature phase-shift keying modulator/demodulator

The QPSK modulator maps the binary digits from the information sequence into discrete phases of the carrier as shown in [Figure 4].
Figure 4: QPSK constellation mapping

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The 768 message bits are converted to integers and then fed into the QPSK modulator which maps the 384 integers to complex 384 integers. QPSK demodulator performs inverse operation of QPSK modulator.

Orthogonal frequency division multiplexing transceiver

OFDM symbol consists of the data carriers, guard subcarriers, and the cyclic prefix, with time durations as shown in [Figure 5]. In this design, 128 subcarriers are used, with 96 being data carriers, 12 being pilots, and 20 being nulls for guard. A cyclic prefix of 32 subcarriers is appended.
Figure 5: Orthogonal frequency division multiplexing symbol

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The 384 complex integers are rearranged to form 96 × 4 array matrix. The matrix is regrouped as: {1,[2:10], [11:19], [20:28],[29:37],[38:46],[47:50],[51:54], [55:62],[63:70], [71:78],[79:86],[87:96]} to allow the insertion of the pilots. The pilots are inserted at the positions (2, 12, 22, 32, 42, 52, 61, 70, 79, 88, 97, 108).

The guards are then inserted at the beginning and end of the data carriers. The symbol is then passed through the inverse fast Fourier transform to create the orthogonal signals.

A cyclic prefix is appended by rearranging and reordering the sequence as (97:128 1:128). This command repeats the last 32 carriers at the beginning of the OFDM symbol.

The OFDM symbol is then power scaled and transmitted through the additive white Gaussian noise (AWGN) channel. The OFDM transmitter is designed as shown in [Figure 6].
Figure 6: Orthogonal frequency division multiplexing transmitter

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At the OFDM receiver shown in [Figure 7], the received symbol is downscaled, and the cyclic prefix is removed by selecting the message portion. The received message is then transformed by the fast Fourier transform to remove the orthogonality. The guards are then removed and subsequently the pilots. The remaining data stream is then rearranged back to the 384 constellation points and then demodulated using QPSK demodulator.
Figure 7: Orthogonal frequency division multiplexing receiver

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The channel

The type of channel used here is AWGN channel. This channel adds white Gaussian noise to the input signal. The SNRs of 10 dB and 20 dB are simulated, and the results are displayed.

Overall design diagram

The overall design is shown in [Figure 8].
Figure 8: Overall design

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  Simulation Results Top


Results for signal-to-noise ratio = 10 dB

[Figure 9], [Figure 10], [Figure 11], [Figure 12] show the transmitted signal, received signal, error rate calculation, and signal spectrum, respectively, for SNR = 10 dB. It can be seen from [Figure 11] that the error rate calculation is 0.4102. By comparing between transmitted signal [Figure 9] and received signal [Figure 10], it can be concluded that there is some difference between them due to noise effect.
Figure 9: Transmitted signal

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Figure 10: Received signal

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Figure 11: Error rate calculation

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Figure 12: Signal spectrum

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[Figure 13] and [Figure 14] show the eye diagram and time scatter plot for SNR = 10 dB. It seems from the two figures that there is distortion due to noise interference.
Figure 13: Eye diagram

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Figure 14: Time scatter plot

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Results for signal-to-noise ratio = 20 dB

[Figure 15], [Figure 16], [Figure 17], [Figure 18] show the transmitted signal, received signal, error rate calculation, and signal spectrum, respectively, for SNR = 20 dB. From [Figure 17], the error rate calculation is zero due to high SNR. By comparing between transmitted signal and received signal, it can be concluded that the two signals are identical due to error free.
Figure 15: Transmitted signal

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Figure 16: Received signal

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Figure 17: Error rate calculation

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Figure 18: Signal spectrum

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[Figure 19] and [Figure 20] show the eye diagram and time scatter plot for SNR = 20dB. It seems from the two figures that the distortion almost disappears as noise effect vanished.
Figure 19: Eye diagram

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Figure 20: Time scatter plot

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  Result Analysis Top


From the results obtained, the time scatter plots and the eye diagrams show how much is noise interference. The wider the eye, the lower the noise interference. This is further proved by looking at the scatter plots. If the plots are randomly distributed, then the noise power is higher than the signal power. This analysis plus the results show that for a given transmission bandwidth, the system performance improves as the SNR increases. The error calculations done further prove that indeed as the SNR increases, an error-free transmission is possible.


  Conclusion Top


This paper studied both the UWB wireless communication systems and WBAN applications and then designed and demonstrated a modem to be used in those applications. The modem simulation showed that it can achieve an error-free transmission at a lower power spectral density and at a very high data rate.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Crosby G, Ghosh T, Murimi R., Chin C. Wireless body area networks for healthcare: A survey. Int J Ad Hoc Sensor Ubiquitous Comput 2012;3:1-26.  Back to cited text no. 1
    
2.
Samaneh M, Abolhasan M, Lipman J, Smith D, Jamalipour A. Wireless body area networks: A survey. IEEE Commun Surv Tutor 2014;16:1658-86.  Back to cited text no. 2
    
3.
Ragesh G, Baskaran K. An overview of applications, standards and challenges in futuristic wireless body area networks. Int J Comput Sci 2012;9:180-6.  Back to cited text no. 3
    
4.
Abdulhamid M, Ben Sewe O. On the performance of UWB-WBAN modem. Sci Bull Electr Eng Fac (De-Gruyter) 2018;18:48-53.  Back to cited text no. 4
    
5.
Hamza E, Majeed R. MAC Protocol for UWB wireless body area networks. Am Sci Res J Eng Technol Sci 2017;38:169-78.  Back to cited text no. 5
    
6.
Ali M. Low Power FM-UWB Transmitter for Wireless Body Area Networks. Ph.D. Thesis. Egypt: Electronics Research Institute; 2017.  Back to cited text no. 6
    
7.
Ben Sewe O. Ultra-Wideband Modem for Wireless Body Area Network Applications. Graduation Project, Nairobi University, Kenya; 2014.  Back to cited text no. 7
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8], [Figure 9], [Figure 10], [Figure 11], [Figure 12], [Figure 13], [Figure 14], [Figure 15], [Figure 16], [Figure 17], [Figure 18], [Figure 19], [Figure 20]



 

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  In this article
Abstract
Introduction
Ultra-Wideband M...
Simulation Results
Result Analysis
Conclusion
References
Article Figures

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