Yogesh Trivedi

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• Ph D
• Professor (Full) at Nirma University

Wireless communication has revolutionized the evolution of humankind. The rapid growth and development of mobile communication has created an ecosystem better than what has been before. However, issues such as ample energy consumption and resulting carbon emissions, a lack of proper disposal mechanisms for large amounts of electronic waste, and the...

Crop classification from hyperspectral remote sensing images is an effective means to understand the agricultural scenario of the country. Band selection (BS) is a necessary step to reduce the dimensions of the hyperspectral image. We propose a band selection method that takes into account the image quality in terms of a non-reference quality index...

Hyperspectral imaging plays a significant role in crop classification and aims to separate various crop pixels from the imagery. It aids the government in deciding agricultural policies. However, high spectral dimensions in hyperspectral data require high computing power and time. This paper presents a new band selection method based on spectral in...

In this paper, the focus is to obtain performance of a multiple input and single output (MISO) wireless communication system in a real-time scenarios of time division duplex (TDD) and frequency division duplex (FDD). We consider a MISO system equipped with 2N transmit antennas. In the total N pairs of antenna, there is a spatial correlation in each...

In this paper, spectrum sensing for primary user (PU) is considered in additive Laplacian noise. Further, we consider dynamic behaviour of PU, where the transitions of PU in both the null and the alternate hypotheses have been modelled by two state discrete time Markov chain (DTMC). We assume PU signal to be quadrature amplitude modulated (M-QAM) w...

Crop mapping using remote sensing data is essential for predicting crop yield and future requirements. However, it can be accomplished by having full ground truth data corresponding to the samples captured by remote sensors. In a practical scenario, generally, we have limited ground-truth data where available crop samples are less than the number o...

Hyperspectral datasets are widely used in many applications of remote sensing in the fields of agriculture, forestry, weather, urban planning, water study, biodiversity and surface changes. Our focus is agriculture with different perspectives such as classifications of crops, identification of different crop growth stages, fallow land, etc. However...

Visible light communication (VLC) has gained attention due to its ability to provide a high data rate in underwater communication. We consider an underwater VLC (UWVLC) system and vertical propagation through the column of water with L layers (channels) and M relays between the transmitter and the receiver. We consider the real-time adverse effects...

In this paper, cooperative spectrum sensing (CSS) of dynamic primary user (PU) is considered in Laplacian noise environment. The dynamic PU is characterized by its transitions from ON (present) state to OFF (absent) state and vice-versa. It means, during the entire sensing duration, the PU appears or disappears intermittently. We assume that each c...

A real time scenario of dynamic primary user (PU) is considered in additive Laplacian noise. Two transitions or status changes of PU in the fixed sensing time are considered. The last status change point (LSCP) is estimated with maximum likelihood estimation by using dynamic programming. We consider Cumulative Sum (CuSum) based weighted samples for...

Spatial Modulation (SM) is a technology that incorporates digital modulation and coding with multiple antennas to achieve high data rates along with improved energy efficiency. Quadrature spatial modulation (QSM), which extends the transmitted signals to in‐phase and quadrature domains, has recently been proposed to improve spectral efficiency (SE)...

In this paper, spectrum sensing techniques with dynamic primary user (PU) are considered in the environment of Laplacian noise. It means the PU may not be present or absent during the whole sensing time. However, PU arrives or departs randomly in the sensing time interval. We consider three different detection schemes such as energy detection, abso...

The inhomogeneous environment due to variation of temperature and salt causes turbulence in the ocean. The strength of turbulence changes with ocean depth. In this paper, we study the performance of underwater visible light communication (UWVLC) system for different depths. We derive novel closed-form analytical expressions for the outage probabili...

A real time scenario of dynamic primary user (PU) is considered in additive Laplacian noise. Two transitions or status changes of PU in the fixed sensing time are considered. The last status change point (LSCP) is estimated with maximum likelihood estimation (MLE) by using dynamic programming. We consider Cumulative Sum (CuSum) based weighted sampl...

Pure endmember extraction from the hyperspectral image is a very essential step in target detection, classification and unmixing applications. Using the concept of convex geometry, a novel algorithm for endmember extraction is proposed in this paper. The algorithm uses convex polygon maximization to determine a convex set that gives maximum convex...

In this paper, the performance of cooperative spectrum sensing (CSS) with absolute value cumulation detection (AVCD) based improved energy detector (IED) in additive Laplacian noise environment is proposed. Each cognitive radio (CR) uses improved AVCD (i-AVCD) as a test statistic. Decision from each CR is then forwarded to the fusion center (FC) wh...

Spectral unmixing is an important problem for remotely sensed hyperspectral data exploitation. Automatic spectral unmixing can be viewed as a three-stage problem, where the first stage is subspace identification, the next one is endmember extraction, and the final one is abundance estimation. In this sequence, endmember extraction is the most chall...

In this paper, we consider Mt×M system (Mt > M), where Mt and M are the numbers of antennas at the transmitter and receiver, respectively. We select M out of Mt transmit antennas using two different antenna selection schemes. In scheme 1, we select the subset of M antennas out of total \((\begin{array}{l}{M_{t}} \\{M}\end{array})\) subsets. In the...

In this paper, a single input multiple output system is considered with L receive antennas and the underlying channels are assumed to be time varying with temporal correlation coefficient a and spatially correlated with correlation coefficient \(\rho \). Further, the channel is assumed to be identically distributed using Rayleigh fading channels an...

Anovel point-to-point symbol detection algorithm in multiple input multiple output (MIMO) system is proposed. This algorithm is an augmentation of two popular algorithms, namely, vertical Bell laboratories layered space-time (VBLAST) and maximum a posteriori probability (MAP). Here, layers are distinguished or ordered based on the a posteriori prob...

In this paper, a novel non-parametric spectrum sensing scheme in cognitive radio (CR) is proposed based on robust Goodness of Fit (GoF) test. The proposed scheme uses likelihood ratio statistics (LRS-\(G^2\)), from which goodness of fit test is derived. The test is applied assuming different types of primary user (PU) signals such as static or cons...

Antenna selection in multiple antenna systems is used as there is no loss of diversity gain. However, in a practical scenario, there is a spatial correlation between adjacent antennas. In this paper, a multiple input single output (MISO) system is considered with L transmit antennas. At the transmitter, the antennas are divided into N = L over 2 gr...

In cognitive radio, spectrum sensing is a challenging task. In this paper, a spectrum sensing method based on censored observations is proposed. We call it as Censored Anderson Darling (CAD) sensing. We present the performance of the CAD sensing method with receiver operating characteristics (ROC) in fading channels using simulations. It is observe...

A novel goodness-of-fit-based non-parametric spectrum sensing scheme in a non-Gaussian noise environment, modelled by Middleton class A distribution, is proposed. The sampling distribution of the proposed test statistic is derived and the detection performance is shown using Monte Carlo simulations. Results are presented and it is concluded that th...

Non-parametric sensing algorithms are preferred in cognitive radio. In this paper, spectrum sensing method based on censored observations is proposed. We evaluate the performance of Censored Anderson-Darling (CAD) sensing method in time-varying and flat-fading channel using Monte Carlo simulations. We have shown the performance of the CAD sensing i...

We consider orthogonal frequency division multiplexing (OFDM) in a multiple input single output (MISO) system. In the presence of spatially uncorrelated time-varying frequency selective channel, we use subcarrier by subcarrier antenna selection using delayed feedback. We derive closed-form expressions for the pdf of the received SNR and BER for MQA...

We consider a sub-optimum joint transmitreceive antenna selection (JTRAS) scheme in multiple input multiple output (MIMO) systems equipped with N transmit and two receive antennas. At the transmitter, we keep one antenna as fixed and select the best among the remaining N − 1 antennas. After selecting two transmit antennas for each of the receive an...

In this paper, we consider Alamouti Transmit Diversity (ATD) system in spatially independent and slowly time varying Rayleigh flat fading channels. The channel is modeled by second order autoregressive (AR2) processes such that it will remain constant for a pair of two consecutive symbols and vary with one pair to another. We consider a frame of N+...

In this paper, we consider MISO systems with N transmit antennas and assume slowly time-varying channel. We select two out of N antennas and use Alamouti transmit diversity. At the receiver, we use zero-forcing detector and obtain expression of BER as a function of correlation (ρ) between two consecutive channel coefficients. We have also discussed...

The authors consider a multiple input single output (MISO) system in which both transmit beamforming and antenna selection (AS) are implemented using delayed channel state information (CSI) at the transmitter (CSIT). The performance of the system has been analysed for three different AS schemes wherein two out of N antennas are selected at the tran...

In this paper, we propose a simple technique for the reduction of high Peak to Average Power Ratio (PAPR), based on Clipping and Differential Scaling, in Orthogonal Frequency Division Multiplexing (OFDM) systems. In this technique, the amplitude of complex OFDM signal is clipped and then scaled in such a way so that the PAPR is reduced without caus...

We analyze a sub-optimum transmit antenna selection (TAS) scheme in multiple input single output (MISO) systems equipped with I transmit antennas. We keep one antenna fixed and select the best among the remaining N - 1 antennas. We assume spatially independent flat fading channel with perfect channel state information (CSI) at receiver and an ideal...

We consider a Multiple Input Single Output (MISO) system equipped with L_t transmit antennas in spatially uncorrelated Rayleigh fading channels. We consider a sub-optimum Antenna Selection (AS) scheme, wherein all the L_t antennas are divided into two groups with L₁ and L₂ antennas such that L₁+L...