Evaluation of Channel Coding Techniques for Massive Machine-Type Communication in 5G Cellular Network

2020 ◽  
Author(s):  
Muhammad Huseen Khan ◽  
Gongxuan Zhang
Keyword(s):  
Channel Coding ◽  
Cellular Network ◽  
Machine Type ◽  
Machine Type Communication

scholarly journals Performance Analysis of Wireless Information Surveillance in Machine-Type Communication at Finite Blocklength Regime

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3031
Author(s):  
Dong ◽  
Li ◽  
Yan
Keyword(s):  
Channel Coding ◽  
High Signal ◽  
Machine Type ◽  
Pervasive Sensing ◽  
Security Challenges ◽  
Machine Type Communications ◽  
Communication Devices ◽  
Machine Type Communication ◽  
And Control ◽  
The Internet Of Things

The Internet of Things (IoT) will feature pervasive sensing and control capabilities via the massive deployment of machine-type communication devices in order to greatly improve daily life. However, machine-type communications can be illegally used (e.g., by criminals or terrorists) which is difficult to monitor, and thus presents new security challenges. The information exchanged in machine-type communications is usually transmitted in short packets. Thus, this paper investigates a legitimate surveillance system via proactive eavesdropping at finite blocklength regime. Under the finite blocklength regime, we analyze the channel coding rate of the eavesdropping link and the suspicious link. We find that the legitimate monitor can still eavesdrop the information sent by the suspicious transmitter as the blocklength decreases, even when the eavesdropping is failed under the Shannon capacity regime. Moreover, we define a metric called the effective eavesdropping rate and study the monotonicity. From the analysis of monotonicity, the existence of a maximum effective eavesdropping rate for a moderate or even high signal-to-noise (SNR) is verified. Finally, numerical results are provided and discussed. In the simulation, we also find that the maximum effective eavesdropping rate slowly increases with the blocklength.

scholarly journals A Device Performance and Data Analytics Concept for Smartphones’ IoT Services and Machine-Type Communication in Cellular Networks

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 593 ◽  
Author(s):  
Kingsley A. Ogudo ◽  
Dahj Muwawa Jean Nestor ◽  
Osamah Ibrahim Khalaf ◽  
Hamed Daei Kasmaei
Keyword(s):  
Cellular Network ◽  
New Technologies ◽  
Service Providers ◽  
Mobile Network ◽  
Device Performance ◽  
Data Traffic ◽  
Machine Type ◽  
Wide Range ◽  
Machine Type Communication ◽  
Video Sensors

With the advancement of new technologies, the number of connected devices, the amount of data generated, and the need to build an intelligently connected network of things to improve and enrich the human ecosystem open new doors to modifications and adaptations of current cellular network infrastructures. While more focus is given to low power wide area (LPWA) applications and devices, a significant challenge is the definition of Internet of Things (IoT) use cases and the value generation of applications on already existing IoT devices. Smartphones and related devices are currently manufactured with a wide range of smart sensors such as accelerometers, video sensors, compasses, gyros, proximity sensors, fingerprint sensors, temperature sensors, and biometric sensors used for various purposes. Many of these sensors can be automatically expanded to monitor a user’s daily activities (e.g., fitness workouts), locations, movements, and real-time body temperatures. Mobile network operators (MNOs) play a substantial role in providing IoT communications platforms, as they manage traffic flow in the network. In this paper, we discuss the global concept of IoT and machine-type communication (MTC), and we conduct device performance analytics based on data traffic collected from a cellular network. The experiment equips service providers with a model and framework to monitor device performance in a network.

scholarly journals Autonomous and adaptive congestion control for machine-type communication in cellular network

2019 ◽  
Vol 15 (4) ◽  
pp. 155014771984186
Author(s):  
Qi Pan ◽  
Xiangming Wen ◽  
Zhaoming Lu ◽  
Wenpeng Jing ◽  
Haijun Zhang
Keyword(s):  
Congestion Control ◽  
Cellular Network ◽  
Machine Type ◽  
Machine Type Communication ◽  
Adaptive Congestion Control

Code-Division OFDM Joint Communication and Sensing System for 6G Machine-type Communication

2021 ◽  
pp. 1-1
Author(s):  
Xu Chen ◽  
Zhiyong Feng ◽  
Zhiqing Wei ◽  
Ping Zhang ◽  
Xin Yuan
Keyword(s):  
Machine Type ◽  
Sensing System ◽  
Machine Type Communication

scholarly journals Distributed Group Location Update Algorithm for Massive Machine Type Communication

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7336
Author(s):  
Mincheol Paik ◽  
Haneul Ko
Keyword(s):  
Outage Probability ◽  
Stochastic Game ◽  
Location Update ◽  
Response Dynamics ◽  
Small Energy ◽  
Machine Type ◽  
Best Response ◽  
Machine Type Communication ◽  
Iot Devices ◽  
The Individual

Frequent location updates of individual Internet of Things (IoT) devices can cause several problems (e.g., signaling overhead in networks and energy depletion of IoT devices) in massive machine type communication (mMTC) systems. To alleviate these problems, we design a distributed group location update algorithm (DGLU) in which geographically proximate IoT devices determine whether to conduct the location update in a distributed manner. To maximize the accuracy of the locations of IoT devices while maintaining a sufficiently small energy outage probability, we formulate a constrained stochastic game model. We then introduce a best response dynamics-based algorithm to obtain a multi-policy constrained Nash equilibrium. From the evaluation results, it is demonstrated that DGLU can achieve an accuracy of location information that is comparable with that of the individual location update scheme, with a sufficiently small energy outage probability.

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