Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Gurugopinath, Sanjeev"'
In this paper, we present a survey on the utility of machine learning (ML) algorithms for applications in cognitive radio networks (CRN). We start with a high-level overview of some of the major challenges in CRNs, and mention the ML architectures an
Externí odkaz:
http://arxiv.org/abs/2106.10413
Autor:
Gurugopinath, Sanjeev, Muhaidat, Sami, Kishore, Rajaleksmi, Sofotasios, Paschalis C., Bouanani, Faissal El, Yanikomeroglu, Halim
Non-orthogonal multiple access (NOMA) is a technology enabler for the fifth generation and beyond networks, which has shown a great flexibility such that it can be readily integrated with other wireless technologies. In this paper, we investigate the
Externí odkaz:
http://arxiv.org/abs/2105.11186
In this paper, we derive the information theoretic performance bounds on communication data rates and errors in parameter estimation, for a joint radar and communication (JRC) system. We assume that targets are semi-passive, i.e. they use active comp
Externí odkaz:
http://arxiv.org/abs/2103.11184
Autor:
Bariah, Lina, Muhaidat, Sami, Sofotasios, Paschalis C., Gurugopinath, Sanjeev, Hamouda, Walaa, Yanikomeroglu, Halim
In this letter, we investigate the performance of non-orthogonal multiple access (NOMA), under the assumption of generalized Gaussian noise (GGN), over Rayleigh fading channels. Specifically, we consider a NOMA system with $L$ users, each of which is
Externí odkaz:
http://arxiv.org/abs/2005.04891
Autor:
Gurugopinath, Sanjeev, Muhaidat, Sami, Al-Hammadi, Yousof, Sofotasios, Paschalis C., Dobre, Octavia A.
The proliferation of connected vehicles along with the high demand for rich multimedia services constitute key challenges for the emerging 5G-enabled vehicular networks. These challenges include, but are not limited to, high spectral efficiency and l
Externí odkaz:
http://arxiv.org/abs/2001.06959
The increasing demand for rich multimedia services and the emergence of the Internet-of-Things (IoT) pose challenging requirements for the next generation vehicular networks. Such challenges are largely related to high spectral efficiency and low lat
Externí odkaz:
http://arxiv.org/abs/1906.06025
Autor:
Kishore, Rajalekshmi, Gurugopinath, Sanjeev, Muhaidat, Sami, Sofotasios, Paschalis C., Dianati, Mehrdad, Al-Dhahir, Naofal
In this paper, we investigate the energy efficiency of conventional collaborative compressive sensing (CCCS) scheme, focusing on balancing the tradeoff between energy efficiency and detection accuracy in cognitive radio environment. In particular, we
Externí odkaz:
http://arxiv.org/abs/1903.00945
Autor:
Kishore, Rajalekshmi, Gurugopinath, Sanjeev, Muhaidat, Sami, Sofotasios, Paschalis C., Dobre, Octavia A., Al-Dhahir, Naofal
In this paper, we investigate the performance of conventional cooperative sensing (CCS) and superior selective reporting (SSR)-based cooperative sensing in an energy harvesting-enabled heterogeneous cognitive radio network (HCRN). In particular, we d
Externí odkaz:
http://arxiv.org/abs/1902.00373
Autor:
Kishore, Rajalekshmi, Gurugopinath, Sanjeev, Sofotasios, Paschalis C., Muhaidat, Sami, Al-Dhahir, Naofal
In the present contribution, we propose a novel opportunistic ambient backscatter communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) networks. This framework considers opportunistic spectrum sensing integrated with AB
Externí odkaz:
http://arxiv.org/abs/1902.00332
Publikováno v:
In Digital Signal Processing November 2022 131
