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  1. (Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi-NCR Campus, Ghaziabad, Uttar Pradesh, India {vinothkm, vinodkur1}

Free space optical (FSO), Multiple input multiple output (MIMO), Atmospheric attenuation

1. Introduction

Hybrid fiber and free-space optical (FSO) communication systems are essential in fifth and sixth-generation systems to expand internet services and manage traffic. FSO communication can be integrated with fiber networks as a key to addressing the challenge of fiber channel implementation up to the last mile [1]. The main advantage of FSO systems is an unlicensed optical spectrum with terahertz (THz) frequencies.

In an FSO system, the signal transmitted to a receiver is focused by a telescope at the receiver, and the received data are estimated by a photodetector, an optical band-pass filter, and detection circuits [2]. Weather attenuation losses in an FSO communication system are significant factors during implementation, particularly because of atmospheric conditions such as haze, rain, fog, dust, snow, and smoke [3,4]. Unlike radio frequency, FSO links suffer the highest attenuation in fog and the most negligible attenuation in the presence of rain. Hybrid and mixed RF/FSO systems have been analyzed in applications between two nodes [4]. Both technologies were deployed together in a hybrid system for various hops.

Hybrid fiber-optical and free-space optical (FO-FSO) communication systems could be a promising solution in future internet services due to the ever-increasing requirements for efficient high speed, high bandwidth, and cost-effective systems. FO-FSO is mainly considered for inter-building connections to avoid bending losses in fiber and reach the last mile. The optical signal propagates through fiber and a wireless-communication FSO channel using an optical carrier to carry the information from the transmitter.

Many types of research on fiber channels are being proposed and analyzed. Various challenges are encountered in the case of fiber materials [5,6] and wireless channels. Examples are bending loss, signal dispersion while transmitting an optical signal through a fiber channel, geometric loss, weather attenuation, background noise, misalignment errors, and atmospheric turbulence due to wireless transmission before the receiver receives the signal.

Section 2 of this research paper discusses related works, section 3 discusses system design and estimation of attenuation values for various weather conditions. Mathematical calculations are covered in section 4, and section 5 shows the results. Furthermore, system observations are discussed in detail.

2. Related Work

Various studies have been published on optical wired and wireless networks connections. The concept of transmitting a signal over an FO-FSO system is that optical signals are modulated by radio frequency signals and transmitted over fiber and FSO channels. Haze attenuation effects on a ``radio over free-space optical'' (RoFSO) transmission system have been presented for Kuala Lumpur International Airport, Sepang (a town in Malaysia). Air pollution index records from between October 2015 and 2017 have been considered for analysis [7].

Techniques to generate 30-300 GHz (millimeter wave) frequency signals to transmit data via fiber and the FSO channel are demonstrated [8]. Phase modulator (PM) and Mach-Zehnder modulator (MZM) based techniques of generating mm-wave are investigated where 5G technology started using high bands such as millimeter-wave leading to the high data rate. The authors analytically quantified the impact of fiber nonlinearities on the performance of mmWave access networks with radio over fiber (RoF) fronthaul [9].

Delhi’s climate was inspected under conditions of heavy to minimum rain, haze, and clear sky, and an FSO connection was inspected for attenuation and the connection length margin under various climatic conditions [10]. The scintillation effects on the performance of FSO links are analyzed [11]. Three optical transmission windows have been evaluated for multiple weather conditions in a worst-case scenario [12]. However, there was no analysis of techniques that reduce the signal loss caused by atmospheric turbulence.

A closed-form mathematical equation was derived to realize the reduced signal loss caused by atmospheric turbulence, but the realization had restrictions in the range of communication [13]. An iterative optimization technique was studied for signal attenuation due to geographical causes and weather conditions [14]. This technique was analyzed for an FSO link, and the performance was observed to increase the visibility distance and reduce BER. Digital modulation techniques such as amplitude shift keying (ASK) and phase-shift keying (PSK) were implemented on an FSO link, and the results were compared for various types of atmospheric turbulence to improve signal transmission [15]. There has been some limitation in incrementing both data rate and transmission link. So it is required to optimize the system to fulfill multimedia requests for new-generation systems.

Several researchers have improved the performance of limited-distance signal transmission in optical communication links with reduced signal loss. However, there is a shortage of research on FSO links to increase transmission distance without attenuation due to weather conditions. There is a limitation in backhaul networks in fiber optic transmission systems and physical connection across networks between buildings, and the last mile reach has yet to be rectified. The integration of fiber and FSO provides a unique solution to the last-mile communication link implementation. However, the challenges in signal attenuation by atmospheric turbulence and FSO channel estimation should be considered while implementing the FO-FSO communication link.

This paper investigates the performance of an FO-FSO system to reach the last mile. The multi- FSO channel technique was analyzed to overcome atmospheric attenuation. FSO channel used in this model is the Gamma-Gamma turbulence model. An RF-modulated light intensity model was analyzed for single, dual, and four FSO channels in terms of BER, quality factor (Q-factor), and the eye diagram. Better receiver sensitivity and a clear eye diagram were observed for four FSO channels than two FSO channels. Attenuation was calculated for the weather conditions of Delhi. The results show that the proposed method fulfills the bandwidth demand for communication over the last mile and increases the distance of the link with minimum BER. Furthermore, simulated results of the power penalty show the method’s capacity to overcome the effects of Delhi’s fog-weather conditions.

3. System Design

The internal and external parameters in FSO systems listed in Table 1 were considered to examine the performance related to the design of FSO shown in Fig. 1 and the environment where the system was implemented [3]. A radio signal modulates the optical signal in the FO-FSO communication system and is transmitted across a fiber channel, which works as a coupler between the modulator and the FSO channel [11]. A pseudo-random bit-sequence generator (PRBS) is employed to send information. A non-return to zero (NRZ) pulse generator converts bit sequences into an electric signal.

An external Mach-Zehnder modulator imposes the information from the NRZ pulse generator on the optical signal generated by a light source. A photodetector is placed at the receiver to convert the optical signal into an electrical signal, followed by a low pass filter. The system design is shown in Fig. 2 for single, dual, and four FSO channels. It consists of blocks of a transmitter, a link channel, and a receiver. System parameters used for simulation are listed in Table 2.

Fig. 1. Free-space optical (FSO) system.
Fig. 2. Block diagram of hybrid fiber-optical and free-space optical (FO-FSO) communication system.
Table 1 Internal and external parameters in the FSO system.

Internal parameters

(related to design)

External parameters (related to the environment)

Wavelength and

Optical - power


Transmission bandwidth

Atmospheric attenuation

Divergence angle


Optical loss resting on the

transmit side

Deployment distance

Receiver - sensitivity and

Receive lens diameter

Window loss

Bit error rate (BER),

Receiver field of view

Pointing loss

Table 2 Various parameters used in the FO-FSO system.

System Parameters

PRBS generator


CW Laser wavelength and power

1550nm, 15dBm

Modulator extinction ratio


Fiber Channel

Single Mode (SMF)

FSO Channel model

Gamma-Gamma Model

FSO Transmitter aperture size


FSO Receiver aperture size


Weather conditions

Haze, Thin fog, Thick fog

Optical amplifier

5m each

Photodetector, Responsivity

PIN Photodiode, 1 A/W

3.1 Transmitter

The optically modulated signal is sent into the fiber channel from the transmitter. A continuous-wave (CW) laser set at 1550-nm wavelength is suitable for the FO-FSO communication system and results in less attenuation when compared to 1310 nm [10]. A PRBS generator generates a bit sequence at a bit rate of 10 Gbps, which is converted into an electrical pulse by an NRZ generator. Signals from the CW laser and NRZ generator are applied to the MZM, which modulates the light signal according to the instantaneous values of the information signal.

3.2 Fiber and FSO Channel

The FO-FSO communication system includes two channels. The modulated optical signal is in a radio frequency range and is transmitted from MZM over single-mode fiber (SMF). An erbium-doped fiber amplifier (EDFA) of 5-m length is connected with the fiber channel line and performs amplification because the signals need strengthening to enhance the signal power. The fiber channel is connected to the FSO channel for wireless transmission of the optical signal.

The transmission medium in the FSO system is atmospheric air. Various weather conditions affect the FSO communication system's performance. Both fiber and FSO channels have advantages and some limitations in propagating information signals. The optical fiber link is susceptible to RF interference and has an extensive range of bandwidth capacity. Lightwave propagation over glass fiber results in less attenuation than wireless transmission [3]. The light signal transmitted over the FSO channel is attenuated by different atmospheric conditions, such as haze, fog, rain, and dust, and the geometric losses lead to further attenuation [11].

3.3 FSO Channel Model

Atmospheric channel models such as the gamma-gamma turbulence model, rician fading, and rayleigh model represent the environment and its meteorological conditions. The Gamma-Gamma turbulence model is utilized in this work for FSO link. The Gamma-Gamma turbulence model employs two random gamma variables that differ significantly and represent weak to strong atmospheric turbulence. A mathematical representation of the gamma-gamma distribution model is given in Eq. (1). Its probability distribution function is expressed as [16,17]

$ f_{I}\left(I_{mn}\right)=~ \frac{2\left(\alpha \beta \right)^{\frac{\alpha +\beta }{2}}}{\Gamma \left(\alpha \right)\Gamma \left(\beta \right)}I_{mn}^{\frac{\alpha +\beta }{2}-1}K_{\alpha -\beta }\left(2\sqrt{\alpha \beta I_{mn}}\right) $

where $\Gamma \left(*\right)$ is Gamma function, $K_{v}\left(*\right)$ is the ${v}^{\mathrm{th}}$order modified Bessel function of the second kind, parameters $\alpha $ and $\beta $ both are calculated based on atmospheric conditions using the following expressions [18],

$\alpha =~ \left[\exp \left(\frac{0.49\chi ^{2}}{\left(1+0.18d^{2}+0.56\chi ^{\frac{12}{5}}\right)^{\frac{7}{6}}}\right)-1\right]^{-1}$,
$ \beta =~ \left[\exp \left(\frac{0.51\chi ^{2}\left(1+0.69\chi ^{\frac{12}{5}}\right)^{\frac{-5}{6}}}{\left(1+0.9d^{2}+0.62d^{2}\chi ^{\frac{12}{5}}\right)^{\frac{7}{6}}}\right)-1\right]^{-1} $

where$~ \chi ^{2}$ = 0.5$C_{n}^{2}k^{7/6}L^{11/6}$, $d=~ \left(\frac{kD^{2}}{4L}\right)^{1/2}$, k = 2${\pi}$/$~ \lambda $. ${D}$ - diameter of the receiver lens aperture, L - link distance in meters, $C_{n}^{2}$ is an altitude-dependent index of refractive structure parameter varying from 10$^{-13}$m$^{\mathrm{-2/3}}$ to 10$^{-17}$m$^{\mathrm{-2/3}}$ as strong to weak turbulence, respectively.

3.4 Receiver

A PIN (P-type, Intrinsic, N-type semiconductor) photodetector is used to detect the optical signal and then pass it via a low-pass Bessel filter with a cutoff frequency range that removes high-frequency components and filters noise from the signal. A BER analyzer was used to examine the performance of the least BER values. The International Telecommunication Union (ITU) declares a minimum BER range of less than 10$^{-9}$ must be maintained [19].

4. Estimation of FSO System Parameters and Atmospheric Attenuations

Based on the recommendation provided by ITU-R P.1814 [19], propagation-prediction methods to plan terrestrial FSO systems were followed. The methods include procedures for estimating attenuation in clear-air, fog, rain, and snow. Weather attenuation calculated under various visibility ranges using Eq. (8) is listed in Table 3. This proposed FO-FSO system is analyzed for whether attenuation loss in different atmospheric conditions.

Table 3 Visibility range in Delhi weather condition and calculated attenuation values.






Visibility in km










(1550 nm)









Weather condition




4.1 Atmospheric Attenuation

Atmospheric attenuation is the process where some or all of the electromagnetic wave (EM) energy is lost when propagating through the atmosphere [14]. In this manner, air causes signal loss in an FSO connection in different ways, such as absorption, scattering, and scintillation. The atmospheric attenuation can be described by Beer's Law [20]:

$ \tau \left(\lambda ,L\right)=\frac{P_{R}}{P_{T}}=e^{-\left(\gamma \left(\lambda \right)L\right)} $


L - Transmitter and receiver distance in km

$\lambda $ - Wavelength

${P}_{R}$ - Optical-power received at distance L

${P}_{T}$ - Optical power at the source

In general, the specific atmospheric attenuation $\gamma $ can be expressed as [3]:

$ \gamma _{atm}=~ \gamma _{\textit{clear}\_ air}+\gamma _{\textit{excess}} $


$\gamma _{\textit{clear}\_ air}$ - Specific attenuation in clear air

$\gamma _{\textit{excess}}$ - Specific attenuation results from the occasional presence of fog, mist, haze, drizzle, rain, snow, hail, etc.

In clear air conditions, attenuation happens because of absorption by gaseous molecules. The interaction between photons and atoms [21] (H$_{2}$, N$_{2}$, H$_{2}$O, CO$_{2}$, O$_{2}$) drives the absorption of the incident photons and raises the temperature. The type of gas molecules and their concentration are used to find out the absorption coefficient. $\gamma _{\textit{clear}\_ air}$ is negligible when selecting the laser's wavelengths to fall inside atmospheric transmission windows.

The FSO system is generally processed with wavelengths near 690 nm, 780 nm, 850 nm, and 1550 nm. In the FSO channel, the excess particles such as haze, fog, mist, drizzle, rain, and snow are causes of extra attenuation, $\gamma _{\textit{excess}}$. These excess particles mainly cause scattering (angular redistribution of the incident flux), reducing the flux propagation in the actual path.

A mathematical representation of attenuation coefficient $\gamma (\lambda )$ is given as [22]:

$ \gamma \left(\lambda \right)=~ \beta _{m}\left(\lambda \right)+\beta _{a}\left(\lambda \right)+\alpha _{m}\left(\lambda \right)+\alpha _{a}\left(\lambda \right) $

where $\gamma (\lambda )$ is derived from four individual parameters as a function of wavelength.

$\beta _{m}$ - Molecular scattering coefficient

$\beta _{a}$ - Aerosol scattering coefficient

$\alpha _{m}$ - Molecular absorption coefficient

$\alpha _{a}$ - Aerosol absorption coefficient.

4.2 Absorption and Scattering

The wavelengths used in FSO systems are 690 nm, 790~nm, 850 nm, and 1550 nm and are located in transmission windows since molecular absorptions are insignificant, and they can be negligible when taking into account the way that these elements are exceptionally minor in this spectrum region [22,23]. Scattering is the redirection of light to propagate along a path resulting in a reduction in expected light intensity [24]. Molecular or Rayleigh scattering [25] is a source of degradation in the electromagnetic radiation in a communication link. It is known that molecular, scattering, and aerosol absorption are insignificant, so the attenuation coefficient from Eq. (4) can be approximated by aerosol scattering:

$ \gamma \left(\lambda \right)\cong ~ \beta _{a}\left(\lambda \right) $

4.3 Visibility

Visibility can be straightforwardly characterized as the natural eye’s ability to see the contrast between a white and dark boundary. The visibility range is the space in kms or miles at which a big dark object can be seen against the horizon sky in daytime [26]. Because the atmosphere has complex shape and is multidirectional, meeting the terms in the hypothesis of Mie scattering to air particles is exceptionally complicated, so the attenuation of a signal owing to distribution is utilized depending on a detailed empirical equation [27,28]. The observational model is expressed as:

$ \gamma \left(\lambda \right)\cong ~ \beta _{a}\left(\lambda \right)=~ \frac{3.912}{V}\left(\frac{\lambda }{550}\right)^{-q\left(v\right)} $

q(v) - The particle size distribution coefficient.

Visibility (V in km) has been studied by Koschmieder law, visibility model established 90 years ago, Middleton (1947) and Duntley (1948a) [29,30]:

$ V=\frac{3.912}{\gamma _{550nm}} $

Also, the attenuation prediction formula has been studied using [10,31]:

$ \gamma \left(\lambda \right)=~ \frac{17}{V}\left(\frac{\lambda }{550}\right)^{-q\left(v\right)} $

V - Meteorological visibility: a path beyond which transmittance goes down to a value$\varepsilon $.

q (v) is the particle size distribution coefficient in Eq. (6), and (8) can be expressed with the help of some models. To calculate the FSO link budget, the Kruse model is commonly used.

$ \begin{equation*} q\left(v\right)=\left\{\begin{array}{ll} 1.6 & if\,\,V>50km\\ 1.3 & if6km<V<50km\\ 0.585V^{1/3} & if\,\,V<6km \end{array}\right. \end{equation*} $

The particle size distribution coefficient q in dense fog was estimated using the model above for visibility less than 6 km as $0.585\mathrm{V}^{1/3}$ and the value of visibility, V<1 km, was proposed by Kim model [32] as:

$$ q(v)=\left\{\begin{array}{cc} 1.6 & \text { if } V>50 \mathrm{~km} \\ 1.3 & \text { if } 6 \mathrm{~km}<V<50 \mathrm{~km} \\ 0.16 V+0.34 & \text { if } 1 \mathrm{~km}<V<6 \mathrm{~km} \\ V-0.5 & \text { if } 0.5 \mathrm{~km}<V<1 \mathrm{~km} \\ 0 & \text { if } V<0.5 \mathrm{~km} \end{array}\right. $$

For tropical regions where fog attenuation is not be taken into account, only haze attenuation is be measured. The Kruse model [31] is acceptable in this case because we are not required to consider visibility of less than 1 km. The value for severe haze defined by the International Visibility Code is around 2.5 km of visibility. Table 3 displays International Visibility Codes for Delhi atmospheric condition [33], and calculated attenuation values using Eq. (8) are listed.

5. Results and Discussion

Tables 4-7 show attenuation values for atmospheric conditions such as haze, thin fog, thick fog, and heavy fog based on visibility level. BER is calculated as [21]:

Bit error rate (BER) = $\frac{\text{Number}\,\,\mathrm{of}\,\,\text{errors}}{\mathrm{The}\,\,\text{total}\,\,\text{number}\,\,\mathrm{of}\,\,\text{bits}\,\,\text{received}}$

Fog is the dominating atmospheric condition in more significant attenuation in FSO systems. Attenuation also depends on rain, low clouds, dust, snow, and combinations of each. Different shapes of eye diagrams with BER values were obtained for various attenuation channels. Wide-open and precise eye diagrams for multiple FSO channels were obtained for respective attenuation values.

The FO-FSO system was checked for three different FSO transmission channels at different atmospheric attenuation values: 4 dB/km for haze conditions, 9 dB/km for thin fog, 16 dB/km for thick fog, and 22 dB/km for heavy fog conditions. Fig. 3 shows eye diagrams and quality factors for haze conditions for single, dual, and four-channel FSO communication systems with a 3.5-km distance. In haze conditions, the attenuation factor is taken as 4dB/km.

Fig. 3. HAZE conditions, attenuation 4dB/km, 3.5-km distance.

Figs. 4-6 are eye diagrams from simulated results with attenuation of 9 dB/km, 16 dB/km, and 22 dB/km for thin, thick, and heavy fog; single, dual, and four channels; and 3.5 km, 2.2 km, and 1.7 km, respectively. The quality factor decreases when increasing the atmospheric attenuation and the range of the FSO link. An additional channel reduces error and increases the Q-factor. Variations in Q-factor are listed in Tables 4-7.

Hybrid FO-FSO systems with single and dual channels were simulated to calculate the power penalty and verify the system's feasibility. Initially, the single-channel FSO of 1.5 km was simulated without fiber connected to the system considering 0- dB/km attenuation as a back-to-back reference model. Secondly, the attenuation for heavy fog conditions of 22 dB/km was used for simulation, and the bit error rate was observed. It is possible to achieve error-free operation for a minimum power penalty while adding a fiber channel before the FSO channel. A fiber channel with a 15-km length and 0.2 dB/km has been simulated along with single and dual FSO channels, which achieved reasonable error-free operation and a good quality factor with minimal power penalty.

The signal output degrades as the atmospheric attenuation, FSO channel range, and optical fiber length increase. Fig. 7 shows the variations in bit error rate for 1*1, 2*2, and 4*4 FSO channels with 22-dB/km attenuation. Improvement in received bits is observed as the number of channels increases for the wireless optical medium. The Achieved FSO link range of the proposed system has been compared with a few existing works, and the comparison is listed in Table 8.

The power penalty value increases as the lengths of both channels and attenuations increase, as shown in Fig. 8 between received power and various lengths of FSO channels with attenuations of haze, fog conditions. Also, Fig. 9 shows that the power penalty significantly increases after 0.8 km in all cases. For the current bit rate of 10 Gbps, this system can deliver effective transmission up to 0.8 km, and there is minimal power penalty for increased lengths. The analysis shows that more than one FSO channel in the FO-FSO system leads to the capacity to overcome the effects of Delhi’s fog weather conditions with an increment of the distance of the link, minimal bit error rate, and minimal power penalty.

Fig. 4. Thin fog conditions, attenuation 9 dB/km, 3.5-km distance.
Fig. 5. Thick fog conditions, attenuation 16 dB/km, 2.2-km distance.
Fig. 6. Heavy fog conditions, attenuation 22 dB/km, 1.7-km distance.
Fig. 7. Min. log of BER versus MIMO FSO Channel range.
Fig. 8. Total power (dBm) versus single FSO channel range with various attenuations.
Fig. 9. Total power (dBm) versus MIMO FSO channel range with various attenuations.
Table 4 Haze conditions, visibility 2km, bit rate - 10 Gb/sec.

Single FSO channel

Dual FSO channels

Four FSO channels

Range (km)

Attenuation (dB/km)

Quality factor

Bit error rate

Quality factor

Bit error rate

Quality factor

Bit error rate

































Table 5 Thin fog conditions, visibility 1km, bit rate - 10 Gb/sec.

Single FSO channel

Dual FSO channels

Four FSO channels

Range (km)

Attenuation (dB/km)

Quality factor

Bit error rate

Quality factor

Bit error rate

Quality factor

Bit error rate

































Table 6 Thick fog conditions, visibility 0.7km, bit rate - 10 Gb/sec.

Single FSO channel

Dual FSO channels

Four FSO channels

Range (km)

Attenuation (dB/km)

Quality factor

Bit error rate

Quality factor

Bit error rate

Quality factor

Bit error rate

























Table 7 Heavy fog conditions, visibility 0.4km, bit rate - 10 Gb/sec.

Single FSO channel

Dual FSO channels

Four FSO channels

Range (km)

Attenuation (dB/km)

Quality factor

Bit error rate

Quality factor

Bit error rate

Quality factor

Bit error rate

























Table 8 Performance comparison of the proposed system with previous works.


Transmission method

Data rate

FSO Channel range and attenuation

Ref [1]

Hybrid Fiber- FSO


0.5km, 0.2 dB/km

Ref [2]

Mode division multiplexing (MDM) - FSO


3km, 0.2 dB/km

650m, 2.62 dB/km

Ref [12]

FSO link


0.5km, 70 dB/km

Proposed system

Hybrid Fiber- FSO


3.5km, 4dB/km

2km, 9dB/km

1km, 22dB/km

6. Conclusion

This work investigated an FO-FSO system with 1*1, 2*2, and 4*4 FSO channels under various atmospheric conditions based on visibility levels. Attenuation in the haze, thin fog, thick fog, and heavy fog have been analyzed for all FSO channels. The results show that the signal performance experiences degradation as attenuation increases (i.e., reduction in Q-factor and increase BER as the channel's length and power penalty grow). But increasing the channel count leads to better signal transmission over free space. The effects of communication parameters on different atmospheric conditions for free-space transmission were shown by simulation of FSO channels. Based on the observations, the multi-channel FSO design integrated with fiber optic communication could become a promising solution for cutting-edge optical communication networks due to its improved performance in information transmission up to the last mile.



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M. Vinoth Kumar

M. Vinoth Kumar is currently pursuing his Ph.D. degree at the Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi-NCR Campus, India. He received his M.Tech. VLSI design and Embedded Systems from B. S. Abdur Rahman University, Chennai, Tamil Nadu, India, in 2013 and B.E. Electronics and Instrumentation Engineering from Anna University, Tamil Nadu, India, in 2009. His research interests are optical fiber communication networks, free-space optical communication systems, photonics, and radio-over-fiber.

Vinod Kumar

Vinod Kumar earned his M. Tech and a Ph.D. degree in Electronics Engineering from the Indian Institute of Technology, BHU, Varanasi, India, in 2008 and 2015. He has more than 15 years of experience in teaching, research, and administration. He is currently working as an Associate Professor at SRM IST Delhi-NCR Campus, Ghaziabad (U.P.). His areas of interest include MOS Sensors, WSN, GaN HEMT, Radio over Fiber, etc. He has published more than 40 research papers in international journals and conferences like IEEE Sensors, IEEE Transactions, JAP, Elsevier, Springer, etc.