arXiv subjects

Sanjeev Sharma

Publications and source records attributed to Sanjeev Sharma.

At least 19 recordsLinked to original sources

arXiv2026

Tertiary-Mode STAR-RIS for Secure NOMA: Integrating Transmission, Reflection, and Jamming

This paper investigates the physical layer security of a non-orthogonal multiple access (NOMA) system assisted by a tertiary-mode simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS), which can perform transmission, reflection, and jamming simultaneously. The system comprises a base station (BS) serving two users located on opposite sides of the STAR-RIS, assuming perfect channel state information (CSI) at the transmitter. To enhance secrecy performance, a subset of STAR-RIS elements is adaptively configured for jamming. A penalty-based alternating optimization algorithm is developed to jointly optimize the BS's active beamforming and the STAR-RIS's passive beamforming and mode selection. Simulation results demonstrate that the proposed design substantially improves the achievable sum rate and secrecy performance compared to conventional RIS-assisted and no-RIS benchmarks, highlighting the potential of tertiary-mode STAR-RIS for secure and efficient next-generation wireless communications.

eess.SP↗

arXiv2025

Comprehensive Review of Deep Unfolding Techniques for Next-Generation Wireless Communication Systems

The application of machine learning in wireless communications has been extensively explored, with deep unfolding emerging as a powerful model-based technique. Deep unfolding enhances interpretability by transforming complex iterative algorithms into structured layers of deep neural networks (DNNs). This approach seamlessly integrates domain knowledge with deep learning (DL), leveraging the strengths of both methods to simplify complex signal processing tasks in communication systems. To provide a solid foundation, we first present a brief overview of DL and deep unfolding. We then explore the applications of deep unfolding in key areas, including signal detection, channel estimation, beamforming design, decoding for error-correcting codes, sensing and communication, power allocation, and security. Each section focuses on a specific task, highlighting its significance in emerging 6G technologies and reviewing recent advancements in deep unfolding-based solutions. Finally, we discuss the challenges associated with developing deep unfolding techniques and propose potential improvements to enhance their applicability across diverse wireless communication scenarios.

eess.SP↗

arXiv2025

Hybrid Rate-Splitting and Sparse Code Multiple Access (RS-SCMA): Design and Performance

This paper proposes, for the first time, a hybrid multiple access framework that integrates the principles of rate-splitting (RS) and sparse code multiple access (SCMA) in an SISO downlink scenario. The proposed scheme, termed RS-SCMA, unifies the powerful interference management capability of rate-splitting multiple access (RSMA) with the near-optimal multiuser detection of SCMA. A key feature of RS-SCMA is a tunable splitting factor $\alpha$, which governs the allocation between the generic $M$-ary modulated common messages and SCMA-encoded private messages. This enables dynamic control over the fundamental trade-off between system sum-rate, bit error rate (BER), and the overloading factor. We develop novel transmitter and receiver architectures based on soft successive interference cancellation (SIC), incorporating message passing algorithm (MPA) detection and soft-symbol reconstruction. Furthermore, a unified analytical expression for the achievable sum-rate is derived as a function of the splitting factor $\alpha$. The performance of the proposed RS-SCMA system is evaluated in terms of both BER and sum-rate. Simulation results confirm the superiority of RS-SCMA over conventional SCMA and multi-carrier RSMA, demonstrating its scalability and robustness even in the presence of channel estimation errors.

eess.SP↗

arXiv2024

IRS-Assisted OTFS: Beamforming Design and Signal Detection

Intelligent reflecting surface (IRS) technology has become a crucial enabler for creating cost effective, innovative, and adaptable wireless communication environments. This study investigates an IRS-assisted orthogonal time frequency space (OTFS) modulation that facilitates communication between users and the base station (BS). The users attainable downlink rate can be boosted by collaboratively improving the reflection coefficient (RC) matrix at the IRS and beamforming matrix at the BS. Then, in the IRS-aided OTFS network, the problem of cooperative precoding at BS and IRS to improve the network throughput is framed. The precoding design problem is non-convex and highly complicated; an alternate optimization (AO) approach is proposed to solve this. Specifically, an approach based on strongest tap maximization (STM) and fractional programming is proposed. It solves RC matrix (at IRS) and beamforming matrix (at BS) alternatively. Moreover, an efficient signal detector for IRS-aided OTFS communication systems using the alternating direction method of multipliers (ADMM) is proposed. Finally, to estimate the cascaded MIMO channel, using a parallel factor tensor model that separates the IRS-User and BS-IRS MIMO channels, respectively is suggested. Simulation results show that the proposed method significantly enhances the system capacity and bit error rate (BER) performance compared to conventional OTFS.

eess.SP↗

arXiv2023

Sparse Code Multiple Access (SCMA) Technique

Next-generation wireless networks require higher spectral efficiency and lower latency to meet the demands of various upcoming applications. Recently, non-orthogonal multiple access (NOMA) schemes are introduced in the literature for 5G and beyond. Various forms of NOMA are considered like power domain, code domain, pattern division multiple access, etc. to enhance the spectral efficiency of wireless networks. In this chapter, we introduce the code domain-based sparse code multiple access (SCMA) NOMA scheme to enhance the spectral efficiency of a wireless network. The design and detection of an SCMA system are analyzed in this chapter. Also, the method for codebooks design and its impact on system performance are highlighted. A hybrid multiple access scheme is also introduced using both code-domain and power-domain NOMA. Furthermore, simulation results are included to show the impact of various SCMA system parameters.ext-generation wireless networks require higher spectral efficiency and lower latency to meet the demands of various upcoming applications. Recently, non-orthogonal multiple access (NOMA) schemes are introduced in the literature for 5G and beyond. Various forms of NOMA are considered like power domain, code domain, pattern division multiple access, etc. to enhance the spectral efficiency of wireless networks. In this chapter, we introduce the code domainbased sparse code multiple access (SCMA) NOMA scheme to enhance the spectral efficiency of a wireless network. The design and detection of an SCMA system are analyzed in this chapter. Also, the method for codebooks design and its impact on system performance are highlighted. A hybrid multiple access scheme is also introduced using both code-domain and power-domain NOMA. Furthermore, simulation results are included to show the impact of various SCMA system parameters.

eess.SP↗

arXiv2023

ADMM-based Detector for Large-scale MIMO Code-domain NOMA Systems

Large-scale multi-input multi-output (MIMO) code domain non-orthogonal multiple access (CD-NOMA) techniques are one of the potential candidates to address the next-generation wireless needs such as massive connectivity, and high reliability. This work focuses on two primary CD-NOMA techniques: sparse-code multiple access (SCMA) and dense-code multiple access (DCMA). One of the primary challenges in implementing MIMO-CD-NOMA systems is designing the optimal detector with affordable computation cost and complexity. This paper proposes an iterative linear detector based on the alternating direction method of multipliers (ADMM). First, the maximum likelihood (ML) detection problem is converted into a sharing optimization problem. The set constraint in the ML detection problem is relaxed into the box constraint sharing problem. An alternative variable is introduced via the penalty term, which compensates for the loss incurred by the constraint relaxation. The system models, i.e., the relation between the input signal and the received signal, are reformulated so that the proposed sharing optimization problem can be readily applied. The ADMM is a robust algorithm to solve the sharing problem in a distributed manner. The proposed detector leverages the distributive nature to reduce per-iteration cost and time. An ADMM-based linear detector is designed for three MIMO-CD-NOMA systems: single input multi output CD-NOMA (SIMO-CD-NOMA), spatial multiplexing CD-NOMA (SMX-CD-NOMA), and spatial modulated CD-NOMA (SM-CD-NOMA). The impact of various system parameters and ADMM parameters on computational complexity and symbol error rate (SER) has been thoroughly examined through extensive Monte Carlo simulations.

cs.IT↗

arXiv2023

QCQP-Tunneling: Ellipsoidal Constrained Agent Navigation

This paper presents a convex-QCQP based novel path planning algorithm named ellipsoidal constrained agent navigation (ECAN), for a challenging problem of online path planning in completely unknown and unseen continuous environments. ECAN plans path for the agent by making a tunnel of overlapping ellipsoids, in an online fashion, through the environment. Convex constraints in the ellipsoid-formation step circumvent collision with the obstacles. The problem of online-tunneling is solved as a convex-QCQP. This paper assumes no constraints on shape of the agent and the obstacles. However, to make the approach clearer, this paper first introduces the framework for a point-mass agent with point-size obstacles. After explaining the underlying principle in drawing an ellipsoid tunnel, the framework is extended to the agent and obstacles having finite area (2d space) and finite-volume (3d-space).

cs.RO↗

arXiv2021

Convolutional Sparse Coding based Channel Estimation for OTFS-SCMA in Uplink

Orthogonal time frequency space (OTFS) has emerged as the most sought-after modulation technique in a high mobility scenario. Sparse code multiple access (SCMA) is an attractive code-domain non-orthogonal multiple access (NOMA) technique. Recently a code-domain NOMA approach for OTFS, named OTFS-SCMA, is proposed. OTFS-SCMA is a promising framework that meets the demands of high mobility and massive connectivity. This paper presents a channel estimation technique based on the convolutional sparse coding (CSC) approach for OTFS-SCMA in the uplink. The channel estimation task is formulated as a CSC problem following a careful rearrangement of the OTFS input-output relation. We use an embedded pilot-aided sparse-pilot structure that enjoys the features of both OTFS and SCMA. The existing channel estimation techniques for OTFS in multi-user scenarios for uplink demand extremely high overhead for pilot and guard symbols, proportional to the number of users. The proposed method maintains a minimal overhead equivalent to a single user without compromising on the estimation error. The results show that the proposed channel estimation algorithm is very efficient in bit error rate (BER), normalized mean square error (NMSE), and spectral efficiency (SE).

eess.SP↗

arXiv2021

Design of SCMA Codebooks Using Differential Evolution

Non-orthogonal multiple access (NOMA) is a promising technology which meets the demands of massive connectivity in future wireless networks. Sparse code multiple access (SCMA) is a popular code-domain NOMA technique. The effectiveness of SCMA comes from: (1) the multi-dimensional sparse codebooks offering high shaping gain and (2) sophisticated multi-user detection based on message passing algorithm (MPA). The codebooks of the users play the main role in determining the performance of SCMA system. This paper presents a framework to design the codebooks by taking into account the entire system including the SCMA encoder and the MPA-based detector. The symbol-error rate (SER) is considered as the design criterion which needs to be minimized. Differential evolution (DE) is used to carry out the minimization of the SER over the codebooks. The simulation results are presented for various channel models.

cs.IT↗

arXiv2020

Hybrid NOMA for Future Radio Access: Design, Potentials and Limitations

Next-generation internet of things (IoT) applications need trillions of low-powered wireless mobile devices to connect with each other having ultra-reliability and low-latency. Non-orthogonal multiple access (NOMA) is a promising technology to address massive connectivity for 5G and beyond by accommodating several users within the same orthogonal resource block. Therefore, this article explores hybrid NOMA (HNOMA) for massive multiple access in the uplink scenarios due to its higher spectral efficiency. The HNOMA includes both power domain and code domain NOMA method due to diverse channel conditions in practice. We highlight that polar coded based data transmission can achieve higher reliability and lower latency in HNOMA-based wireless networks. Further, at the base station (BS), channel state information (CSI) of each link is not perfectly available or very complex to estimate due to non-orthogonal links. Therefore, we analyze and review the performance of uplink based system involving HNOMA transmission in the presence of imperfect CSI. Furthermore, we summarize some key technical challenges as well as their potential solutions in futuristic IoT applications using HNOMA transmission. Finally, we offer some design guidelines for HNOMA-based systems using deep learning approach to implement adaptive and efficient wireless networks.

eess.SP↗

arXiv2020

Performance of Intelligent Reconfigurable Surface-Based Wireless Communications Using QAM Signaling

Intelligent reconfigurable surface (IRS) is being seen as a promising technology for 6G wireless networks. The IRS can reconfigure the wireless propagation environment, which results in significant performance improvement of wireless communications. In this paper, we analyze the performance of bandwidth-efficient quadrature amplitude modulation (QAM) techniques for IRS-assisted wireless communications over Rayleigh fading channels. New closed-form expressions of the generic average symbol error rate (ASER) for rectangular QAM, square QAM and cross QAM schemes are derived. Moreover, simplified expressions of the ASER for low signal-to-noise-ratio (SNR) and high SNR regions are also presented, which are useful to provide insights analytically. We comprehensively analyze the impact of modulation parameters and the number of IRS elements employed. We also verify our theoretical results through simulations. Our results demonstrate that employing IRS significantly enhances the ASER performance in comparison to additive white Gaussian noise channel at a low SNR regime. Thus, IRS-assisted wireless communications can be a promising candidate for various low powered communication applications such as internet-of-things (IoT).

cs.IT↗

arXiv2020

Design of Puncturing for Length-Compatible Polar Codes Using Differential Evolution

This paper presents a puncturing technique to design length-compatible polar codes. The punctured bits are identified with the help of differential evolution (DE). A DE-based optimization framework is developed where the sum of the bit-error-rate (BER) values of the information bits is minimized. We identify a set of bits which can be avoided for puncturing in the case of additive white Gaussian noise (AWGN) channels. This reduces the size of the candidate puncturing patterns. Simulation results confirm the superiority of the proposed technique over other state-of-the-art puncturing methods.

cs.IT↗

arXiv2020

OTFS-NOMA based on SCMA

Orthogonal Time Frequency Space (OTFS) is a $\text{2-D}$ modulation technique that has the potential to overcome the challenges faced by orthogonal frequency division multiplexing (OFDM) in high Doppler environments. The performance of OTFS in a multi-user scenario with orthogonal multiple access (OMA) techniques has been impressive. Due to the requirement of massive connectivity in 5G and beyond, it is immensely essential to devise and examine the OTFS system with the existing Non-orthogonal Multiple Access (NOMA) techniques. In this paper, we propose a multi-user OTFS system based on a code-domain NOMA technique called Sparse Code Multiple Access (SCMA). This system is referred to as the OTFS-SCMA model. The framework for OTFS-SCMA is designed for both downlink and uplink. First, the sparse SCMA codewords are strategically placed on the delay-Doppler plane such that the overall overloading factor of the OTFS-SCMA system is equal to that of the underlying basic SCMA system. The receiver in downlink performs the detection in two sequential phases: first, the conventional OTFS detection using the method of linear minimum mean square error (LMMSE), and then the conventional SCMA detection. For uplink, we propose a single-phase detector based on message-passing algorithm (MPA) to detect the multiple users' symbols. The performance of the proposed OTFS-SCMA system is validated through extensive simulations both in downlink and uplink. We consider delay-Doppler planes of different parameters and various SCMA systems of overloading factor up to 200$\%$. The performance of OTFS-SCMA is compared with those of existing OTFS-OMA techniques. The comprehensive investigation demonstrates the usefulness of OTFS-SCMA in future wireless communication standards.

cs.IT↗

arXiv2019

Non-orthogonal Multiple Access as an Enabler for Massive Connectivity for 5G and Beyond Networks

Two of the most challenging goals to be achieved in the fifth generation (5G) and beyond communication are massive connectivity and higher capacity. The use of traditional orthogonal multiple access techniques limits the number of users that can be served using the available resources due to orthogonality constraint. Moreover, the available resources may not be utilized effectively by the alloted users thereby resulting in inefficiency and user unfairness. This imposes a severe drawback in cases where the number of users to be served are high, like in the 5G networks. Hence, introducing non-orthogonality to the multiple access scheme is advocated as a supreme methodology to serve multiple users simultaneously, thereby enhancing the connectivity. In scenarios with massive number of users, non-orthogonal multiple access scheme increases the number of active connections by superimposing the signal of multi-users on a same resource block, thereby also utilizing the available resources efficiently.

eess.SP↗

arXiv2019

An End-to-end Framework for Unconstrained Monocular 3D Hand Pose Estimation

This work addresses the challenging problem of unconstrained 3D hand pose estimation using monocular RGB images. Most of the existing approaches assume some prior knowledge of hand (such as hand locations and side information) is available for 3D hand pose estimation. This restricts their use in unconstrained environments. We, therefore, present an end-to-end framework that robustly predicts hand prior information and accurately infers 3D hand pose by learning ConvNet models while only using keypoint annotations. To achieve robustness, the proposed framework uses a novel keypoint-based method to simultaneously predict hand regions and side labels, unlike existing methods that suffer from background color confusion caused by using segmentation or detection-based technology. Moreover, inspired by the biological structure of the human hand, we introduce two geometric constraints directly into the 3D coordinates prediction that further improves its performance in a weakly-supervised training. Experimental results show that our proposed framework not only performs robustly on unconstrained setting, but also outperforms the state-of-art methods on standard benchmark datasets.

cs.CV↗

arXiv2017

Autonomous Waypoint Generation with Safety Guarantees: On-Line Motion Planning in Unknown Environments

On-line motion planning in unknown environments is a challenging problem as it requires (i) ensuring collision avoidance and (ii) minimizing the motion time, while continuously predicting where to go next. Previous approaches to on-line motion planning assume that a rough map of the environment is available, thereby simplifying the problem. This paper presents a reactive on-line motion planner, Robust Autonomous Waypoint generation (RAW), for mobile robots navigating in unknown and unstructured environments. RAW generates a locally maximal ellipsoid around the robot, using semi-definite programming, such that the surrounding obstacles lie outside the ellipsoid. A reinforcement learning agent then generates a local waypoint in the robot's field of view, inside the ellipsoid. The robot navigates to the waypoint and the process iterates until it reaches the goal. By following the waypoints the robot navigates through a sequence of overlapping ellipsoids, and avoids collision. Robot's safety is guaranteed theoretically and the claims are validated through rigorous numerical experiments in four different experimental setups. Near-optimality is shown empirically by comparing RAW trajectories with the global optimal trajectories.

cs.RO↗

arXiv2017

Sparse Impulse Noise Minimization in UWB Communication using Signal Characteristics

In many applications, ultra-wide band (UWB) system experiences impulse noise due to surrounding physical noise sources. Therefore, a conventional receiver (correlator or matched filter) designed for additive Gaussian noise system is not optimum for an impulse noise affected communication channel. In this paper, we propose a new robust receiver design that utilizes the received UWB signal cluster sparsity to mitigate impulse noise. Further, multipath channel diversity enhances the signal-to-noise ratio, as compared to the single path after impulse noise removal in the proposed receiver design. The proposed receiver is analyzed in time hopping binary phase shift keying UWB system and is compared with popular blanking non-linearity based receiver in Bernoulli-Gaussian impulse noise over both single and multipath IEEE 802.15.4a channels. Unlike existing designs, the proposed receiver does not require any training sequence. The proposed receiver is observed to be robust with improved bit error rate performance as compared to a blanking receiver in the presence of impulse noise.

cs.IT↗

arXiv2013

A Comparative Study of Histogram Equalization Based Image Enhancement Techniques for Brightness Preservation and Contrast Enhancement

Histogram Equalization is a contrast enhancement technique in the image processing which uses the histogram of image. However histogram equalization is not the best method for contrast enhancement because the mean brightness of the output image is significantly different from the input image. There are several extensions of histogram equalization has been proposed to overcome the brightness preservation challenge. Contrast enhancement using brightness preserving bi-histogram equalization (BBHE) and Dualistic sub image histogram equalization (DSIHE) which divides the image histogram into two parts based on the input mean and median respectively then equalizes each sub histogram independently. This paper provides review of different popular histogram equalization techniques and experimental study based on the absolute mean brightness error (AMBE), peak signal to noise ratio (PSNR), Structure similarity index (SSI) and Entropy.

cs.CV↗