The Impact of Spectrum Sharing Strategies on the E2E Performance of Machine Type Communication

2017 ◽  
Author(s):  
M. Bassi ◽  
C. Lima ◽  
A. Ferreira
2021 ◽  
Author(s):  
Parampreet Sidhu

With the advent of new wireless technologies, it is expected that the use of Machine-Type Communication (MTC) will significantly increase in next generation wireless networks. Wireless communication networks are considered to support MTC due to their availability and existing infrastructures. As these networks are designed and optimized in a way that they fit best for Human Type Communication (HTC), there is a need of an efficient radio re- source management (RRM) to accommodate MTC traffic without affecting the regular HTC traffic in the network. In this thesis, a continuous-time Markov chain (CTMC) model-based RRM scheme is proposed to analyze the impact of MTC traffic on HTC traffic in wireless communication networks, in terms of blocking probability and channel utilization. Numerical results are provided, demonstrating the effectiveness of the proposed RRM scheme in providing the quality of service (QoS) isolation between HTC and MTC traffic.


Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8064
Author(s):  
Binod Kharel ◽  
Onel Luis Alcaraz López ◽  
Hirley Alves ◽  
Matti Latva-aho

This paper focuses on edge-enabled cloud radio access network architecture to achieve ultra-reliable communication, a crucial enabler for supporting mission-critical machine-type communication networks. We propose coordinated multi-point transmission schemes taking advantage of diversity mechanisms in interference-limited downlink cellular networks. The network scenario comprises spatially distributed multiple remote radio heads (RRHs) that may cooperate through silencing, or by using more elaborated diversity strategies such as maximum ratio transmission or transmit antenna selection to serve user equipment in the ultra-reliable operation regime. We derive an exact closed-form expression for the outage probabilities and expected values of signal-to-interference ratio for silencing, transmit antenna selection and maximum ratio transmission schemes. We formulate rate control and energy efficiency under reliability constraints to test the performance and resource usage of the proposed schemes. Furthermore, we study the impact on average system sum throughput with throughput-reliability trade-off under cooperative communication. Extensive numerical analysis shows the feasibility of ultra-reliable communication by implementing diversity schemes with RRHs cooperation.


2021 ◽  
Author(s):  
Parampreet Sidhu

With the advent of new wireless technologies, it is expected that the use of Machine-Type Communication (MTC) will significantly increase in next generation wireless networks. Wireless communication networks are considered to support MTC due to their availability and existing infrastructures. As these networks are designed and optimized in a way that they fit best for Human Type Communication (HTC), there is a need of an efficient radio re- source management (RRM) to accommodate MTC traffic without affecting the regular HTC traffic in the network. In this thesis, a continuous-time Markov chain (CTMC) model-based RRM scheme is proposed to analyze the impact of MTC traffic on HTC traffic in wireless communication networks, in terms of blocking probability and channel utilization. Numerical results are provided, demonstrating the effectiveness of the proposed RRM scheme in providing the quality of service (QoS) isolation between HTC and MTC traffic.


2019 ◽  
Author(s):  
Marcela Gomez ◽  
Martin B. H. Weiss ◽  
Seongmin Park ◽  
Prashabnt Krishnamurthy

Author(s):  
Xu Chen ◽  
Zhiyong Feng ◽  
Zhiqing Wei ◽  
Ping Zhang ◽  
Xin Yuan

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7336
Author(s):  
Mincheol Paik ◽  
Haneul Ko

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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