2,325 research outputs found
Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services
This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book
NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks
With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)
A Study on Techniques/Algorithms used for Detection and Prevention of Security Attacks in Cognitive Radio Networks
In this paper a detailed survey is carried out on the taxonomy of Security Issues, Advances on Security Threats and Countermeasures ,A Cross-Layer Attack, Security Status and Challenges for Cognitive Radio Networks, also a detailed survey on several Algorithms/Techniques used to detect and prevent SSDF(Spectrum Sensing Data Falsification) attack a type of DOS (Denial of Service) attack and several other  Network layer attacks in Cognitive Radio Network or Cognitive Radio Wireless Sensor Node Networks(WSNN’s) to analyze the advantages and disadvantages of those existing algorithms/techniques
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN
The number of IoT devices is predicted to reach 125 billion by 2023. The
growth of IoT devices will intensify the collisions between devices, degrading
communication performance. Selecting appropriate transmission parameters, such
as channel and spreading factor (SF), can effectively reduce the collisions
between long-range (LoRa) devices. However, most of the schemes proposed in the
current literature are not easy to implement on an IoT device with limited
computational complexity and memory. To solve this issue, we propose a
lightweight transmission-parameter selection scheme, i.e., a joint channel and
SF selection scheme using reinforcement learning for low-power wide area
networking (LoRaWAN). In the proposed scheme, appropriate transmission
parameters can be selected by simple four arithmetic operations using only
Acknowledge (ACK) information. Additionally, we theoretically analyze the
computational complexity and memory requirement of our proposed scheme, which
verified that our proposed scheme could select transmission parameters with
extremely low computational complexity and memory requirement. Moreover, a
large number of experiments were implemented on the LoRa devices in the real
world to evaluate the effectiveness of our proposed scheme. The experimental
results demonstrate the following main phenomena. (1) Compared to other
lightweight transmission-parameter selection schemes, collisions between LoRa
devices can be efficiently avoided by our proposed scheme in LoRaWAN
irrespective of changes in the available channels. (2) The frame success rate
(FSR) can be improved by selecting access channels and using SFs as opposed to
only selecting access channels. (3) Since interference exists between adjacent
channels, FSR and fairness can be improved by increasing the interval of
adjacent available channels.Comment: 14 pages, 12 figures, 8 tables. This work has been submitted to the
IEEE for possible publication. Copyright may be transferred without notice,
after which this version may no longer be accessibl
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