scholarly journals A Baseband Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM Signals

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1101
Author(s):  
Felipe A. P. de Figueiredo ◽  
Ruben Mennes ◽  
Irfan Jabandžić ◽  
Xianjun Jiao ◽  
Ingrid Moerman
Keyword(s):  
Radio Frequency ◽  
Mobile Networks ◽  
Spectral Efficiency ◽  
Base Stations ◽  
Traffic Load ◽  
Front End ◽  
Rf Front End ◽  
Radio Access ◽  
Wireless Spectrum ◽  
Arbitrary Frequency

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

scholarly journals A Base-Band Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM signals

2019 ◽  
Author(s):  
Felipe Augusto Pereira de Figueiredo ◽  
Ruben Mennes ◽  
Irfan Jabandzic ◽  
Xianjun Jiao ◽  
Ingrid Moerman
Keyword(s):  
Mobile Networks ◽  
Spectral Efficiency ◽  
Traffic Load ◽  
Spectrum Access ◽  
Physical Layers ◽  
Wireless Spectrum ◽  
Arbitrary Frequency ◽  
Limited Spectrum ◽  
Base Band ◽  
Ofdm Signals

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the actual one. This situation calls for novel ways to increase spectral efficiency. Therefore in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front-ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, $i.e.$, the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum-bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

scholarly journals Optimal User Association Strategy for Large-Scale IoT Sensor Networks with Mobility on Cloud RANs

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4415 ◽  
Author(s):  
Taewoon Kim ◽  
Chanjun Chun ◽  
Wooyeol Choi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Mobile Internet ◽  
Base Stations ◽  
Traffic Load ◽  
User Association ◽  
Network Simulator ◽  
Traffic Loads ◽  
Association Strategy ◽  
Radio Access

In networking systems such as cloud radio access networks (C-RAN) where users receive the connection and data service from short-range, light-weight base stations (BSs), users’ mobility has a significant impact on their association with BSs. Although communicating with the closest BS may yield the most desirable channel conditions, such strategy can lead to certain BSs being over-populated while leaving remaining BSs under-utilized. In addition, mobile users may encounter frequent handovers, which imposes a non-negligible burden on BSs and users. To reduce the handover overhead while balancing the traffic loads between BSs, we propose an optimal user association strategy for a large-scale mobile Internet of Things (IoT) network operating on C-RAN. We begin with formulating an optimal user association scheme focusing only on the task of load balancing. Thereafter, we revise the formulation such that the number of handovers is minimized while keeping BSs well-balanced in terms of the traffic load. To evaluate the performance of the proposed scheme, we implement a discrete-time network simulator. The evaluation results show that the proposed optimal user association strategy can significantly reduce the number of handovers, while outperforming conventional association schemes in terms of load balancing.

scholarly journals Enhanced Transmit-Antenna Selection Schemes for Multiuser Massive MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Byung-Jin Lee ◽  
Sang-Lim Ju ◽  
Nam-il Kim ◽  
Kyung-Seok Kim
Keyword(s):  
Computational Complexity ◽  
Radio Frequency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Base Station ◽  
Base Stations ◽  
Transmit Antenna Selection ◽  
Selection Scheme

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.

scholarly journals Problems of constructing broadband radio access systems of mobile radio communication

2019 ◽  
Vol 2019 (2) ◽  
pp. 24-30
Author(s):  
Василий Типаков ◽  
Vasily Sergeevich Tipakov ◽  
Тимур Яковлев ◽  
Timur Aleksandrovich Yakovlev
Keyword(s):  
Cellular Networks ◽  
Mobile Networks ◽  
Mobile Communications ◽  
Current Trend ◽  
Mobile Radio ◽  
Base Stations ◽  
Radio Communication ◽  
Radio Access ◽  
Broadband Radio ◽  
Internal Network

The article is focused on the problem of degrading the signals of broadband 3G / 4G mobile radio access systems in places of subscribers clustering and in so-called “dead zones”. The analysis of the actual principles of building mobile networks has been carried out, the main disadvantages of the approaches to the development of cellular networks have been identified. The current trend of building macro cells in the urban environment has lost its effectiveness due to the increasing frequencies used; it has to be replaced by a fundamentally new way of planning mobile networks. A new principle of providing access to mobile communications “from inside to outside” is proposed, which takes into account the needs of a large number of subscribers in the premises. It is based on setting the maximum number of internal base stations fully meeting the needs of internal network users. Such a distinction will positively affect all subscribers and improve the experience from using the high-quality services of the mobile operators, which will result in increasing the economic performance

Galileo E5 Signal Acquisition and Tracking Based on a Wide-Band Customized Universal Peripheral N210 Platform

2013 ◽  
Vol 765-767 ◽  
pp. 2686-2690
Author(s):  
Ning Yan Guo ◽  
Yan Zhao ◽  
Tian Xing Chu
Keyword(s):  
Radio Frequency ◽  
Wide Band ◽  
High Accuracy ◽  
Signal Acquisition ◽  
Multipath Mitigation ◽  
Front End ◽  
Rf Front End ◽  
Galileo E5

GNSS navigation has its own advantages which make researchers focus on how to effectively receive and process GNSS signals. This typically needs to utilize flexible specialized radio frequency front-ends, and we need to investigate novel software solutions. Due to the good performance of the Galileo E5 signal, the study of its acquisition, tracking and multipath mitigation has become increasingly significant. This paper has developed a customized 100MHz wide-band GNSS front-end. Three wide-band datasets of Galileo E5 signal were collected for case study. Final acquisition and tracking results of Galileo E5a signal successfully verified this customized RF front-end usability. It offers great potential for further studying the multi-constellation GNSS compatibility and interoperability to achieve high accuracy and continuity of GNSS navigation.

scholarly journals Dynamic handoff policy for RAN slicing by exploiting deep reinforcement learning

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yuansheng Wu ◽  
Guanqun Zhao ◽  
Dadong Ni ◽  
Junyi Du
Keyword(s):  
Reinforcement Learning ◽  
Mobile Networks ◽  
Resource Constraints ◽  
Base Stations ◽  
Service Needs ◽  
Network Slicing ◽  
Logical Connection ◽  
Radio Access ◽  
Markov Decision ◽  
Underlying Network

AbstractIt has been widely acknowledged that network slicing is a key architectural technology to accommodate diversified services for the next generation network (5G). By partitioning the underlying network into multiple dedicated logical networks, 5G can support a variety of extreme business service needs. As network slicing is implemented in radio access networks (RAN), user handoff becomes much more complicated than that in traditional mobile networks. As both physical resource constraints of base stations and logical connection constraints of network slices should be considered in handoff decision, an intelligent handoff policy becomes imperative. In this paper, we model the handoff in RAN slicing as a Markov decision process and resort to deep reinforcement learning to pursue long-term performance improvement in terms of user quality of service and network throughput. The effectiveness of our proposed handoff policy is validated via simulation experiments.

scholarly journals Dynamic Handoff Policy for RAN Slicing by Exploiting Deep Reinforcement Learning

2021 ◽  
Author(s):  
Yuansheng Wu ◽  
Guanqun Zhao ◽  
Dadong Ni ◽  
Junyi Du
Keyword(s):  
Reinforcement Learning ◽  
Mobile Networks ◽  
Resource Constraints ◽  
Base Stations ◽  
Service Needs ◽  
Network Slicing ◽  
Logical Connection ◽  
Radio Access ◽  
Markov Decision ◽  
Underlying Network

Abstract It has been widely acknowledged that network slicing is a key architectural technology to accommodate diversified services for the next generation network (5G). By partitioning the underlying network into multiple dedicated logical networks, 5G can support a variety of extreme business service needs. As network slicing is implemented in radio access networks (RAN), user handoff becomes much more complicated than that in traditional mobile networks. As both physical resource constraints of base stations (BSs) and logical connection constraints of network slices should be considered in handoff decision, an intelligent handoff policy becomes imperative. In this paper, we model the handoff in RAN slicing as a Markov decision process (MDP) and resort to deep reinforcement learning to pursue long-term performance improvement in terms of user quality of Service (QoS) and network throughput. The effectiveness of our proposed handoff policy is validated via simulation experiments.

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