Apurba Adhikary 교수

The impending sixth-generation wireless communication networks are anticipated to guarantee mass connectivity, high integration, and lower power consumption for generating the required beamforming. To achieve these goals, an artificial intelligence (AI) framework is proposed by utilizing holographic MIMO-assisted integrated sensing, localization, and communication. The proposed AI framework ensures lower power consumption to activate the minimum number of grids from the holographic grid array fo

The forth-coming 6G wireless communication systems are required to meet the increasing demand for network connectivity that requires power savings for generating effective beamforming. Therefore, joint sensing and communication framework is proposed with the coexistence between holographic MIMO (HMIMO) and Intelligent Omni-Surface (IOS) which ensures the extension of the coverage area resulting in lower power consumption for beamforming. An optimization problem is formulated maximizing the utili

Sixth-generation wireless networks are required to satisfy the ever-increasing demands of diverse applications to guarantee power savings, energy efficiency (EE), and mass connectivity. To accomplish these goals, in this article, an artificial intelligence (AI)-based holographic MIMO (HMIMO)-empowered cell-free (CF) network is proposed while leveraging integrated sensing and communication (ISAC). The proposed AI-based framework allocates the desired power for beamforming by activating the requir

The growing global populations, particularly in major cities, have created new problems, notably in terms of public safety regulation and optimization. As a result, in this paper, a strategy is provided for predicting crime occurrences in a city based on historical events and demographic observation. In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. Thus, a complete analysis of four distinct sorts of crimes, such a

The future sixth-generation (6G) wireless communication networks are expected to provide massive connectivity with lower power requirements for generating the desired beamforming. Therefore, holographic MIMO assisted integrated sensing and communication framework is proposed that ensures lower power requirements to activate the minimum number of grids from the holographic grid array (HGA) for the effective beamforming. An optimization problem is formulated that maximizes the signal to noise-inte

본 논문은 홀로그램 기술을 이용하여 다양한 형태의 사용자를 위한 사용자 지향 통신 리소스 할당을 수행하는 단일 셀 대규모 다중 입력 다중 출력(mMIMO) 시스템을 제안한다. 본 논문에서는 목표지향 사용자에게 서비스를 제공하기 위한 빔 포밍의 저전력 요구 사항을 확인하기 위해 홀로그램 그리드 어레이(HGA)에서 활성 그리드의 수를 최소화할 수 있는 기술을 제안한다. 이를 위해 신호 대 간섭 잡음 비율(SINR)을 최대화하여 문제를 공식화하였다. 이는 효과적인 빔포밍 및 총 전력 규칙을 생성하여 자원 할당을 최대화한다. 또한, 홀로그램 mMIMO 시스템은 더 적은 전력으로 다양한 사용자들의 장비에 서비스를 동시에 제공할 수 있다. 인공지능(AI) 기반 솔루션을 고안하기 위해 전력 제약을 최소화한 그리드 활성화 결정을 위한 순차 신경망 모델을 개발하였다. 시뮬레이션 및 성능 평가 결과에서 전력이 효율적으로 할당되고 0.01의 낮은 RMSE 점수로 효과적인 빔이 형성됨을 보여주었다.

The coming 6G wireless communication system requires an intelligent networking system with higher network capacity. Therefore, we consider an intelligent omni surface (IOS)-assisted cell-free massive MIMO (ICFMM) system that extends the network coverage by providing services on both sides of the IOS with minimized power. The base stations and IOSs cooperatively serve the users in the ICFMM system and require a smaller number of IOS compared to the intelligent reflecting surfaces. An optimization

The upcoming 6G wireless communication networks are anticipated to offer extensive mobile connectivity, faster data services with reduced power consumption, and seamless integration among different technologies for providing effective beamforming. To accomplish these aims, a transfer learning empowered AI framework is proposed to allocate the power for serving the users under the coverage areas of the corresponding holographic MIMOs (HMIMOs) by activating the required number of grids from the re

The 6G wireless communication networks need an intelligent networking system to meet the ever-increasing de-mands of various applications and mobile devices to ensure power savings, energy efficiency (EE), high integration of devices, and mass connection. To achieve these aims, an artificial intelligence (AI)-based holographic MIMO (HMIMO)-aided cell-free (CF) network is suggested to allocate desired power for beamforming by activating the required number of grids from the serving HMIMOs for ser

Our study proposes a technique to enhance light extraction efficiency of light emitting diodes (LEDs) by incorporating various micro-/nanolens arrays (MNLAs) on the substrate layer, which in turn increases the external quantum efficiency (EQE) of the LEDs. To simulate the LEDs, we utilized the finite difference time domain method. To achieve a white LED, we inserted a thin layer of NiO at the interface between the n-type ZnO and the p-type GaN. The basic n-ZnO/NiO/p-GaN heterojunction-based LED

<p>The impending sixth-generation wireless communication networks are anticipated to guarantee mass connectivity, high integration, and lower power consumption for generating the required beamforming. To achieve these goals, an artificial intelligence (AI) framework is proposed by utilizing holographic MIMO-assisted integrated sensing, localization, and communication. The proposed AI framework ensures lower power consumption to activate the minimum number of grids from the holographic grid

Aims: This paper presents a Gigabit Passive Optical Networks (GPON) model which includes a power budget analysis, availability analysis and signal performance analysis of the system.
 Study Design: A Gigabit Passive Optical Networks (GPON) model.
 Place and Duration of Study: Department of Electronics and Communication Engineering, Khulna University, Khulna-9208, Bangladesh, between June 2017 and February 2018.
 Methodology: The system performance is presented through various para