NDLI: Performance analysis of cognitive-based radio resource allocation in multi-channel LTE-A networks with M2M/H2H coexistence

Content Provider	IET Digital Library
Author	Qahtani, Salman A. Al
Abstract	Efficient radio access strategies are necessary and critical to manage an long-term-evolution (LTE) network system where machine-to-machine (M2M) devices and human-to-human (H2H) users coexist. In this study, the authors propose a cognitive-based access strategy with a priority-based queuing model that is designed for LTE with M2M/H2H coexistence, where the M2M communications have real-time (M2M-RT) and non-real-time (M2M-NRT) traffic. Radio access gives the highest priority to H2H, while M2M-RT has higher priority than M2M-NRT. A continuous-time Markov chain model is developed to evaluate the system performance in terms of service completion rate, blocking and forced termination probabilities, and mean queuing delay of the M2M traffic. In addition, resource utilisation by the M2M traffic is also evaluated. Analytical results reveal that, while protecting the H2H services, the proposed queuing model could increase the capacity of the M2M traffic network while decreasing the blocking probability. Additionally, allowing an interrupted M2M-NRT to be inserted back into its queue can further decrease the forced termination rate. For these reasons, it can be concluded that the proposed model can be used to improve the system performance of multi-channel M2M communication networks.
Starting Page	655
Ending Page	663
Page Count	9
ISSN	17518628
Volume Number	11
e-ISSN	17518636
Issue Number	Issue 5, Mar (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/11/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2016.0469
Journal	IET Communications
Publisher Date	2016-12-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Blocking Probability Cognitive Radio Cognitive-based Radio Access Strategy Continuous-time Markov Chain Model Forced Termination Probability Human-to-human User Long Term Evolution Long-Term-Evolution Network System M2M Traffic M2M-H2H Coexistence Machine-to-machine Device Markov Processes Mobile Radio System Multichannel LTE-A Network Queueing System Queueing Theory Service Completion Rate
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

CTMC modelling for H2H/M2M coexistence in LTE-A/LTE-M networks

Analysis and modelling of power consumption-aware priority-based scheduling for M2M data aggregation over long-term-evolution networks

Enhancement of LTE RACH through extended random access process

CTMC modeling for M2M/H2H coexistence in a NB-IoT Adaptive eNodeB

Performance analysis for uplink NOMA-based cellular network with M2M/H2H co-existence

Analysis of PDCCH Performance for M2M Traffic in LTE

Self-organised dynamic resource allocation scheme using enhanced fractional frequency reuse in long term evolution-advanced relay-based networks

Delay-scheduler coupled throughput-fairness resource allocation algorithm in the long-term evolution wireless networks

Impact of the primary user on the secondary user blocking probability in cognitive radio sensor networks

Performance analysis of cognitive-based radio resource allocation in multi-channel LTE-A networks with M2M/H2H coexistence

Similar Documents

CTMC modelling for H2H/M2M coexistence in LTE-A/LTE-M networks

Analysis and modelling of power consumption-aware priority-based scheduling for M2M data aggregation over long-term-evolution networks

Enhancement of LTE RACH through extended random access process

CTMC modeling for M2M/H2H coexistence in a NB-IoT Adaptive eNodeB

Performance analysis for uplink NOMA-based cellular network with M2M/H2H co-existence

Analysis of PDCCH Performance for M2M Traffic in LTE

Self-organised dynamic resource allocation scheme using enhanced fractional frequency reuse in long term evolution-advanced relay-based networks

Delay-scheduler coupled throughput-fairness resource allocation algorithm in the long-term evolution wireless networks

Impact of the primary user on the secondary user blocking probability in cognitive radio sensor networks

Performance analysis of cognitive-based radio resource allocation in multi-channel LTE-A networks with M2M/H2H coexistence