2022
Ioannis D Bougas; Maria S Papadopoulou; Achilles D Boursianis; Panagiotis Sarigiannidis; Spyridon Nikolaidis; Sotirios. K Goudos
Rectifier circuit design for 5G energy harvesting applications Conference
2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2022, ISBN: 978-1-6654-6717-9.
Abstract | BibTeX | Tags: 5G, impedance matching network, power conversion efficiency, radio frequency energy harvesting, rectifier, voltage doubler, voltage multiplier, wireless power transfer | Links:
@conference{9837524,
title = {Rectifier circuit design for 5G energy harvesting applications},
author = {Ioannis D Bougas and Maria S Papadopoulou and Achilles D Boursianis and Panagiotis Sarigiannidis and Spyridon Nikolaidis and Sotirios. K Goudos},
url = {https://www.researchgate.net/publication/362327796_Rectifier_circuit_design_for_5G_energy_harvesting_applications},
doi = {10.1109/MOCAST54814.2022.9837524},
isbn = {978-1-6654-6717-9},
year = {2022},
date = {2022-06-08},
booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)},
pages = {1-4},
abstract = {The need for electronic devices usage has risen significantly over the years. This has in turn generated greater demands for electricity and in addition for green energy sources. These include Radio-Frequency (RF) energy harvesting. In this concept we design a rectifier circuit for RF to DC conversion suitable for operation at sub-6 GHz 5G bands. Such a circuit can be used to supply low-power electronic devices. The proposed rectifier works at the frequency band FR1 of 5G cellular network and more specifically at 3.5 GHz. The most important problem in the RF energy harvesters is low system efficiency, something that limits the popularity of the power harvest. The proposed design is found to be highly efficient in its current form. Numerical results show that the system in a single-tone signal provides maximum power conversion efficiency equal to 42.5% when the load of the circuit is 1.1 KΩ and the input power reaches 9 dBm. The presented rectifier circuit performs better or equally with similar designs in the literature.},
keywords = {5G, impedance matching network, power conversion efficiency, radio frequency energy harvesting, rectifier, voltage doubler, voltage multiplier, wireless power transfer},
pubstate = {published},
tppubtype = {conference}
}
The need for electronic devices usage has risen significantly over the years. This has in turn generated greater demands for electricity and in addition for green energy sources. These include Radio-Frequency (RF) energy harvesting. In this concept we design a rectifier circuit for RF to DC conversion suitable for operation at sub-6 GHz 5G bands. Such a circuit can be used to supply low-power electronic devices. The proposed rectifier works at the frequency band FR1 of 5G cellular network and more specifically at 3.5 GHz. The most important problem in the RF energy harvesters is low system efficiency, something that limits the popularity of the power harvest. The proposed design is found to be highly efficient in its current form. Numerical results show that the system in a single-tone signal provides maximum power conversion efficiency equal to 42.5% when the load of the circuit is 1.1 KΩ and the input power reaches 9 dBm. The presented rectifier circuit performs better or equally with similar designs in the literature.
2019
D. Pliatsios; P. Sarigiannidis; I.D. Moscholios; A. Tsiakalos
Cost-efficient Remote Radio Head Deployment in 5G Networks Under Minimum Capacity Requirements Conference
2019.
Abstract | BibTeX | Tags: 5G, Cloud Radio Access Network (C-RAN), cost optimization, small cell deployment, traffic demand | Links:
@conference{Pliatsios2019,
title = {Cost-efficient Remote Radio Head Deployment in 5G Networks Under Minimum Capacity Requirements},
author = { D. Pliatsios and P. Sarigiannidis and I.D. Moscholios and A. Tsiakalos},
url = {https://www.researchgate.net/publication/338597444_Cost-efficient_Remote_Radio_Head_Deployment_in_5G_Networks_Under_Minimum_Capacity_Requirements},
doi = {10.1109/PACET48583.2019.8956245},
year = {2019},
date = {2019-01-01},
journal = {5th Panhellenic Conference on Electronics and Telecommunications, PACET 2019},
abstract = {Dense small cell deployment is an effective way to address the increasing requirements of the emerging Fifth Generation mobile networks. The Cloud Radio Access Network (C-RAN) is an emerging concept that can achieve very dense small cell deployment. In ultra-dense C-RAN architectures with numerous Remote Radio Heads (RRHs), the minimization of the deployment cost is a critical issue in the radio network planning phase. In this paper, we propose a low complexity algorithm that minimizes the required number of small cells, while ensuring user satisfaction in terms of network capacity. The algorithm is based on the successive elimination of RRHs, and it simultaneously solves the minimization and the optimal deployment problems. The evaluation results indicate that the proposed algorithm can efficiently solve the aforementioned problems. © 2019 IEEE.},
keywords = {5G, Cloud Radio Access Network (C-RAN), cost optimization, small cell deployment, traffic demand},
pubstate = {published},
tppubtype = {conference}
}
Dense small cell deployment is an effective way to address the increasing requirements of the emerging Fifth Generation mobile networks. The Cloud Radio Access Network (C-RAN) is an emerging concept that can achieve very dense small cell deployment. In ultra-dense C-RAN architectures with numerous Remote Radio Heads (RRHs), the minimization of the deployment cost is a critical issue in the radio network planning phase. In this paper, we propose a low complexity algorithm that minimizes the required number of small cells, while ensuring user satisfaction in terms of network capacity. The algorithm is based on the successive elimination of RRHs, and it simultaneously solves the minimization and the optimal deployment problems. The evaluation results indicate that the proposed algorithm can efficiently solve the aforementioned problems. © 2019 IEEE.
S.K. Goudos; M. Deruyck; D. Plets; L. Martens; K.E. Psannis; P. Sarigiannidis; W. Joseph
A Novel Design Approach for 5G Massive MIMO and NB-IoT Green Networks Using a Hybrid Jaya-Differential Evolution Algorithm Journal Article
In: IEEE Access, vol. 7, pp. 105687-105700, 2019.
Abstract | BibTeX | Tags: 4G, 5G, evolutionary algorithms, green networks, hybrid networks, Massive MIMO, NB-IoT, network design, network planning, power consumption | Links:
@article{Goudos2019105687,
title = {A Novel Design Approach for 5G Massive MIMO and NB-IoT Green Networks Using a Hybrid Jaya-Differential Evolution Algorithm},
author = { S.K. Goudos and M. Deruyck and D. Plets and L. Martens and K.E. Psannis and P. Sarigiannidis and W. Joseph},
url = {https://www.researchgate.net/publication/334778653_A_Novel_Design_Approach_for_5G_Massive_MIMO_and_NB-IoT_Green_Networks_Using_a_Hybrid_Jaya-Differential_Evolution_Algorithm},
doi = {10.1109/ACCESS.2019.2932042},
year = {2019},
date = {2019-01-01},
journal = {IEEE Access},
volume = {7},
pages = {105687-105700},
abstract = {Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user for 4th Generation (4G) and 5th Generation (5G) Massive MIMO network configurations. Moreover, we present and address the problem of designing green LTE networks with the Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. In this context, we apply emerging evolutionary algorithms in the context of green network design. We investigate three different cases to show the performance of the new proposed algorithm, namely the 4G, 5G Massive MIMO, and the NB-IoT technologies. More specifically, we investigate the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, the self-adaptive differential evolution jDE algorithm, and other hybrid algorithms. We introduce a new hybrid algorithm named Jaya-jDE that uses concepts from both Jaya and jDE algorithms in an effective way. The results show that 5G Massive MIMO networks require about 50% less power consumption than the 4G ones, and the NB-IoT in-band deployment requires about 10% less power than guard-band deployment. Moreover, Jaya-jDE emerges as the best algorithm based on the results. © 2013 IEEE.},
keywords = {4G, 5G, evolutionary algorithms, green networks, hybrid networks, Massive MIMO, NB-IoT, network design, network planning, power consumption},
pubstate = {published},
tppubtype = {article}
}
Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user for 4th Generation (4G) and 5th Generation (5G) Massive MIMO network configurations. Moreover, we present and address the problem of designing green LTE networks with the Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. In this context, we apply emerging evolutionary algorithms in the context of green network design. We investigate three different cases to show the performance of the new proposed algorithm, namely the 4G, 5G Massive MIMO, and the NB-IoT technologies. More specifically, we investigate the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, the self-adaptive differential evolution jDE algorithm, and other hybrid algorithms. We introduce a new hybrid algorithm named Jaya-jDE that uses concepts from both Jaya and jDE algorithms in an effective way. The results show that 5G Massive MIMO networks require about 50% less power consumption than the 4G ones, and the NB-IoT in-band deployment requires about 10% less power than guard-band deployment. Moreover, Jaya-jDE emerges as the best algorithm based on the results. © 2013 IEEE.
D. Pliatsios; P. Sarigiannidis
Resource allocation combining heuristic matching and particle swarm optimization approaches: The case of Downlink Non-Orthogonal Multiple Access Journal Article
In: Information (Switzerland), vol. 10, no. 11, 2019.
Abstract | BibTeX | Tags: 5G, Heuristic optimization, Non-orthogonal multiple access, Resource allocation | Links:
@article{Pliatsios2019d,
title = {Resource allocation combining heuristic matching and particle swarm optimization approaches: The case of Downlink Non-Orthogonal Multiple Access},
author = { D. Pliatsios and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/336928272_Resource_Allocation_Combining_Heuristic_Matching_and_Particle_Swarm_Optimization_Approaches_The_Case_of_Downlink_Non-Orthogonal_Multiple_Access},
doi = {10.3390/info10110336},
year = {2019},
date = {2019-01-01},
journal = {Information (Switzerland)},
volume = {10},
number = {11},
abstract = {The ever-increasing requirement of massive connectivity, due to the rapid deployment of internet of things (IoT) devices, in the emerging 5th generation (5G) mobile networks commands for even higher utilization of the available spectrum. Non-orthogonal multiple access (NOMA) is a promising solution that can effectively accommodate a higher number of users, resulting in increased spectrum utilization. In this work, we aim to maximize the total throughput of a NOMA system, while maintaining a good level of fairness among the users. We propose a three-step method where the first step matches the users to the channels using a heuristic matching algorithm, while the second step utilizes the particle swarm optimization algorithm to allocate the power to each channel. In the third step, the power allocated to each channel is further distributed to the multiplexed users based on their respective channel gains. Based on extensive performance simulations, the proposed method offers notable improvement, e.g., 15% in terms of system throughput and 55% in terms of user fairness. © 2019 by the authors.},
keywords = {5G, Heuristic optimization, Non-orthogonal multiple access, Resource allocation},
pubstate = {published},
tppubtype = {article}
}
The ever-increasing requirement of massive connectivity, due to the rapid deployment of internet of things (IoT) devices, in the emerging 5th generation (5G) mobile networks commands for even higher utilization of the available spectrum. Non-orthogonal multiple access (NOMA) is a promising solution that can effectively accommodate a higher number of users, resulting in increased spectrum utilization. In this work, we aim to maximize the total throughput of a NOMA system, while maintaining a good level of fairness among the users. We propose a three-step method where the first step matches the users to the channels using a heuristic matching algorithm, while the second step utilizes the particle swarm optimization algorithm to allocate the power to each channel. In the third step, the power allocated to each channel is further distributed to the multiplexed users based on their respective channel gains. Based on extensive performance simulations, the proposed method offers notable improvement, e.g., 15% in terms of system throughput and 55% in terms of user fairness. © 2019 by the authors.
2018
D. Pliatsios; P. Sarigiannidis; S. Goudos; G.K. Karagiannidis
Realizing 5G vision through Cloud RAN: technologies, challenges, and trends Journal Article
In: Eurasip Journal on Wireless Communications and Networking, vol. 2018, no. 1, 2018.
Abstract | BibTeX | Tags: 5G, Cloud Radio Access Network, Common Public Radio Interface, Network function virtualization, Software-defined networking | Links:
@article{Pliatsios2018,
title = {Realizing 5G vision through Cloud RAN: technologies, challenges, and trends},
author = { D. Pliatsios and P. Sarigiannidis and S. Goudos and G.K. Karagiannidis},
url = {https://www.researchgate.net/publication/325181057_Realizing_5G_vision_through_Cloud_RAN_technologies_challenges_and_trends},
doi = {10.1186/s13638-018-1142-1},
year = {2018},
date = {2018-01-01},
journal = {Eurasip Journal on Wireless Communications and Networking},
volume = {2018},
number = {1},
abstract = {Achieving the fifth-generation (5G) vision will introduce new technology innovations and substantial changes in delivering cutting-edge applications and services in current mobile and cellular networks. The Cloud Radio Access Network (C-RAN) concept emerged as one of the most compelling architectures to meet the requirements of the 5G vision. In essence, C-RAN provides an advanced mobile network architecture which can leverage challenging features such as network resource slicing, statistical multiplexing, energy efficiency, and high capacity. The realization of C-RAN is achieved by innovative technologies such as the software-defined networking (SDN) and the network function virtualization (NFV). While SDN technology brings the separation of the control and data planes in the playground, supporting thus advanced traffic engineering techniques such as load balancing, the NFV concept offers high flexibility by allowing network resource sharing in a dynamic way. Although SDN and NFV have many advantages, a number of challenges have to be addressed before the commercial deployment of 5G implementation. In addition, C-RAN introduces a new layer in the mobile network, denoted as the fronthaul, which is adopted from the recent research efforts in the fiber-wireless (Fi-Wi) paradigm. As the fronthaul defines a link between a baseband unit (BBU) and a remote radio unit (RRU), various technologies can be used for this purpose such as optical fibers and millimeter-wave (mm-wave) radios. In this way, several challenges are highlighted which depend on the technology used. In the light of the aforementioned remarks, this paper compiles a list of challenges and open issues of the emerging technologies that realize the C-RAN concept. Moreover, comparative insights between the current and future state of the C-RAN concept are discussed. Trends and advances of those technologies are also examined towards shedding light on the proliferation of 5G through the C-RAN concept. © 2018, The Author(s).},
keywords = {5G, Cloud Radio Access Network, Common Public Radio Interface, Network function virtualization, Software-defined networking},
pubstate = {published},
tppubtype = {article}
}
Achieving the fifth-generation (5G) vision will introduce new technology innovations and substantial changes in delivering cutting-edge applications and services in current mobile and cellular networks. The Cloud Radio Access Network (C-RAN) concept emerged as one of the most compelling architectures to meet the requirements of the 5G vision. In essence, C-RAN provides an advanced mobile network architecture which can leverage challenging features such as network resource slicing, statistical multiplexing, energy efficiency, and high capacity. The realization of C-RAN is achieved by innovative technologies such as the software-defined networking (SDN) and the network function virtualization (NFV). While SDN technology brings the separation of the control and data planes in the playground, supporting thus advanced traffic engineering techniques such as load balancing, the NFV concept offers high flexibility by allowing network resource sharing in a dynamic way. Although SDN and NFV have many advantages, a number of challenges have to be addressed before the commercial deployment of 5G implementation. In addition, C-RAN introduces a new layer in the mobile network, denoted as the fronthaul, which is adopted from the recent research efforts in the fiber-wireless (Fi-Wi) paradigm. As the fronthaul defines a link between a baseband unit (BBU) and a remote radio unit (RRU), various technologies can be used for this purpose such as optical fibers and millimeter-wave (mm-wave) radios. In this way, several challenges are highlighted which depend on the technology used. In the light of the aforementioned remarks, this paper compiles a list of challenges and open issues of the emerging technologies that realize the C-RAN concept. Moreover, comparative insights between the current and future state of the C-RAN concept are discussed. Trends and advances of those technologies are also examined towards shedding light on the proliferation of 5G through the C-RAN concept. © 2018, The Author(s).
Address
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Contact Information
tel: +30 2461 056527
Email: ithaca@uowm.gr
