arXiv subjects

Devendra Singh Gurjar

Publications and source records attributed to Devendra Singh Gurjar.

5 recordsLinked to original sources

arXiv2025

Radiance Field Delta Video Compression in Edge-Enabled Vehicular Metaverse

Connected and autonomous vehicles (CAVs) offload computationally intensive tasks to multi-access edge computing (MEC) servers via vehicle-to-infrastructure (V2I) communication, enabling applications within the vehicular metaverse, which transforms physical environment into the digital space enabling advanced analysis or predictive modeling. A core challenge is physical-to-virtual (P2V) synchronization through digital twins (DTs), reliant on MEC networks and ultra-reliable low-latency communication (URLLC). To address this, we introduce radiance field (RF) delta video compression (RFDVC), which uses RF-encoder and RF-decoder architecture using distributed RFs as DTs storing photorealistic 3D urban scenes in compressed form. This method extracts differences between CAV-frame capturing actual traffic and RF-frame capturing empty scene from the same camera pose in batches encoded and transmitted over the MEC network. Experiments show data savings up to 71% against H.264 codec and 44% against H.265 codec under different conditions as lighting changes, and rain. RFDVC also demonstrates resilience to transmission errors, significantly outperforming the standard codec in non-rainy conditions with up to a +0.26 structural similarity index measure (SSIM) improvement over H.264 codec, and maintaining a +0.18 SSIM improvement even in challenging rainy conditions, both measured at a block error rate (BLER) of 0.25.

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arXiv2021

Low-Complexity Interference Cancellation Algorithms for Detection in Media-based Modulated Uplink Massive-MIMO Systems

Media-based modulation (MBM) is a novel modulation technique that can improve the spectral efficiency of the existing wireless systems. In MBM, multiple radio frequency (RF) mirrors are placed near the transmit antenna(s) and are switched ON/OFF to create different channel fade realizations. In such systems, additional information is conveyed through the ON/OFF status of RF mirrors along with conventional modulation symbols. A challenging task at the receiver is to detect the transmitted information symbols and extract the additional information from the channel fade realization used for transmission. In this paper, we consider a massive MIMO (mMIMO) system where each user relies on MBM for transmitting information to the base station, and investigate the problem of symbol detection at the base station. First, we propose a mirror activation pattern (MAP) selection based modified iterative sequential detection algorithm. With the proposed algorithm, the most favorable MAP is selected, followed by the detection of symbol corresponding to the selected MAP. Each solution is subjected to the reliability check before getting the update. Next, we introduce a $K$ favorable MAP search based iterative interference cancellation (KMAP-IIC) algorithm. In particular, a selection rule is introduced in KMAP-IIC for deciding the set of favorable MAPs over which iterative interference cancellation is performed, followed by a greedy update scheme for detecting the MBM symbols corresponding to each user. Simulation results show that the proposed detection algorithms exhibit superior performance-complexity trade-off over the existing detection techniques in MBM-mMIMO systems.

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arXiv2021

Performance Analysis and Optimization of Bidirectional Overlay Cognitive Radio Networks with Hybrid-SWIPT

This paper considers a cooperative cognitive radio network with two primary users (PUs) and two secondary users (SUs) that enables two-way communications of primary and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information and power transfer (SWIPT). With the considered network, SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs. The overall bidirectional end-to-end transmission takes place in four phases, which include both energy harvesting (EH) and information transfer. A non-linear energy harvester with a hybrid SWIPT scheme is adopted in which both power-splitting and time-switching EH techniques are used. The SUs aid in relay cooperation by performing an amplify-and-forward operation, whereas selection combining technique is adopted at the PUs to extract the intended signal from multiple received signals broadcasted by the SUs. Accurate outage probability expressions for the primary and secondary links are derived under the Nakagami-$m$ fading environment. Further, the system behavior is analyzed with respect to achievable system throughput and energy efficiency. Since the performance of the considered system is strongly affected by the spectrum sharing factor and hybrid SWIPT parameters, particle swarm optimization is implemented to optimize the system parameters so as to maximize the system throughput and energy efficiency. Simulation results are provided to corroborate the performance analysis and give useful insights into the system behavior concerning various system/channel parameters.

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arXiv2020

Wireless Information and Power Transfer for IoT Applications in Overlay Cognitive Radio Networks

This paper proposes and investigates an overlay spectrum sharing system in conjunction with the simultaneous wireless information and power transfer (SWIPT) to enable communications for the Internet of Things (IoT) applications. Considered is a cooperative cognitive radio network, where two IoT devices (IoDs) exchange their information and also provide relay assistance to a pair of primary users (PUs). Different from most existing works, in this paper, both IoDs can harvest energy from the radio-frequency (RF) signals received from the PUs. By utilizing the harvested energy, they provide relay cooperation to PUs and realize their own communications. For harvesting energy, a time-switching (TS) based approach is adopted at both IoDs. With the proposed scheme, one round of bidirectional information exchange for both primary and IoT systems is performed in four phases, i.e., one energy harvesting (EH) phase and three information processing (IP) phases. Both IoDs rely on the decode-and-forward operation to facilitate relaying, whereas the PUs employ selection combining (SC) technique. For investigating the performance of the considered network, this paper first provides exact expressions of user outage probability (OP) for the primary and IoT systems under Nakagami-m fading. Then, by utilizing the expressions of user OP, the system throughput and energy efficiency are quantified together with the average end-to-end transmission time. Numerical and simulation results are provided to give useful insights into the system behavior and to highlight the impact of various system/channel parameters.

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arXiv2020

Performance of Wireless Powered Cognitive Radio Sensor Networks With Nonlinear Energy Harvester

This letter analyzes the performance of simultaneous wireless information-and-power transfer (SWIPT) in an overlay cognitive radio network (CRN) under Nakagami-$m$ fading. A pair of secondary users (SUs) is considered in which one SU facilitates relay cooperation for communications between two primary users (PUs). In return, SUs make use of primary users' signals for energy harvesting (EH) and realize their own communications. In such a network, end-to-end bidirectional communications between the two PUs and unidirectional information exchange between the SUs can be performed in three phases. A power splitting (PS) based approach is adopted for enabling SWIPT. The relaying SU applies an amplify-and-forward (AF) protocol to broadcast primary and secondary signals, whereas the PUs perform selection combining to access the active direct link. Accurate expressions of the outage probability (OP) and throughput are derived for the primary system by considering a nonlinear energy harvester at the relaying SU under Nakagami-m fading

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