Machine-to-machine communication with long-term evolution with reduced device energy consumption

2013 ◽  
Vol 24 (4) ◽  
pp. 413-426 ◽  
Author(s):  
Tuomas Tirronen ◽  
Anna Larmo ◽  
Joachim Sachs ◽  
Bengt Lindoff ◽  
Niclas Wiberg
Keyword(s):  
Energy Consumption ◽  
Long Term Evolution ◽  
Machine To Machine ◽  
Term Evolution ◽  
Machine To Machine Communication ◽  
Machine Communication

scholarly journals Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

2018 ◽  
Vol 7 (3) ◽  
pp. 27 ◽  
Author(s):  
Nargis Khan ◽  
Jelena Mišić ◽  
Vojislav Mišić
Keyword(s):  
Smart City ◽  
Overlay Network ◽  
Long Term Evolution ◽  
City Development ◽  
Machine To Machine ◽  
Crowd Sensing ◽  
Term Evolution ◽  
Trade Offs ◽  
Access Channel

Long-Term Evolution (LTE) and its improvement, Long-Term Evolution-Advanced (LTE-A), are attractive choices for Machine-to-Machine (M2M) communication due to their ubiquitous coverage and high bandwidth. However, the focus of LTE design was high performance connection-based communications between human-operated devices (also known as human-to-human, or H2H traffic), which was initially established over the Physical Random Access Channel (PRACH). On the other hand, M2M traffic is mostly based on contention-based transmission of short messages and does not need connection establishment. As a result, M2M traffic transmitted over LTE PRACH has to use the inefficient four-way handshake and compete for resources with H2H traffic. When a large number of M2M devices attempts to access the PRACH, an outage condition may occur; furthermore, traffic prioritization is regulated only through age-based power ramping, which drives the network even faster towards the outage condition. In this article, we describe an overlay network that allows a massive number of M2M devices to coexist with H2H traffic and access the network without going through the full LTE handshake. The overlay network is patterned after IEEE 802.15.6 to support multiple priority classes of M2M traffic. We analyse the performance of the joint M2M and H2H system and investigate the trade-offs needed to keep satisfactory performance and reliability for M2M traffic in the presence of H2H traffic of known intensity. Our results confirm the validity of this approach for applications in crowd sensing, monitoring and others utilized in smart city development.

Supporting machine-to-machine communications in long-term evolution networks

2015 ◽  
pp. 109-129 ◽  
Author(s):  
A. Laya ◽  
K. Wang ◽  
L. Alonso ◽  
J. Alonso-Zarate ◽  
J. Markendahl
Keyword(s):  
Long Term Evolution ◽  
Machine To Machine ◽  
Term Evolution

PERFORMANCE ANALYSIS OF THE ENERGY CONSUMPTION OF THE SCHEDULING ALGORITHMS IN LONG TERM EVOLUTION LTE (LONG TERM EVOLUTION) NETWORKS

2016 ◽  
Vol 78 (10-4) ◽  
Author(s):  
Nurulanis Mohd Yusoff ◽  
Darmawaty Mohd Ali ◽  
Ku Siti Syahidah Ku Mohd Noh
Keyword(s):  
Global Warming ◽  
Energy Consumption ◽  
Communication Systems ◽  
Scheduling Algorithms ◽  
Long Term Evolution ◽  
Proportional Fair ◽  
Downlink Transmission ◽  
Term Evolution ◽  
The Impact

Energy efficiency has become an important feature in communication systems due to the problem of global warming and lack of energy resources. The impact on global warming caused by wireless communication industries has been gradually increasing, so it is obvious that developing the green communication is significant. In particular, energy consumption in the base stations and downlink transmission are the major areas where significant conservation can be achieved. Thus, the objective of this study is to investigate the performance of the packet scheduling algorithms in the downlink transmission and the energy consumption for video and Voice over IP (VoIP) applications in Long Term Evolution (LTE) systems. In this work, four different scheduling algorithms were analysed namely the Channel and Quality of Service Aware Proportional Fair (CQA_PF), CQA Frequency Fading (CQA_Ff), Priority Set Scheduler Proportional Fair (PSS_PF), and PSS Carrier Over Interference to Average (PSS_CoItA) based on the performance metrics of throughput, delay, energy consumption ratio (ECR) and fairness. The results showed that the CQA algorithm for both methods (CQA_PF and CQA_Ff) outperformed the other algorithms since it has the highest throughput with an increase of up to 25%. Meanwhile, for delay and ECR, the CQA scheduler was the lowest of up to 20% as compared to the PSS scheduler. Thus, it can be concluded that CQA is the most energy efficient algorithm to schedule the video and VoIP applications.

scholarly journals Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5337 ◽  
Author(s):  
Hajer Ben Rekhissa ◽  
Cecile Belleudy ◽  
Philippe Bessaguet
Keyword(s):  
Energy Consumption ◽  
Long Term Evolution ◽  
M2m Communication ◽  
Maximum Expansion ◽  
High Data ◽  
Channel Quality ◽  
M2m Communications ◽  
Term Evolution ◽  
Energy Efficient Resource Allocation

Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more flexibility. However, M2M communication over LTE/LTE-A networks faces some challenges. One of these challenges is the management of resource radios especially on the uplink. LTE schedulers should be able to meet the needs of M2M devices, such as power management and the support of large number of devices, in addition to handling both human-to-human (H2H) and M2M communications. Motivated by the fundamental requirement of extending the battery lives of M2M devices and managing an LTE network system, including both M2M devices and H2H users, in this paper, two channel-aware scheduling algorithms on the uplink are proposed. Both of them consider the coexistence of H2H and M2M communications and aim to reduce energy consumption in M2M devices. The first algorithm, called FDPS-carrier-by-carrier modified (CBC-M), takes into account channel quality and power consumption while allocating radio resources. Our second algorithm, recursive maximum expansion modified (RME-M), offers a balance between delay requirement and energy consumption. Depending on the system requirements, RME-M considers both channel quality and system deadlines in an adjustable manner according to M2M devices needs. Simulation results show that the proposed schedulers outperform the round-robin scheduler in terms of energy efficiency and have better cell spectral efficiency.

scholarly journals Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

2021 ◽  
Author(s):  
Nargis Khan ◽  
Jelena Mišić ◽  
Vojislav B. Mišić
Keyword(s):  
Smart City ◽  
Overlay Network ◽  
Long Term Evolution ◽  
City Development ◽  
Machine To Machine ◽  
Crowd Sensing ◽  
Term Evolution ◽  
Trade Offs ◽  
Access Channel

Long-Term Evolution (LTE) and its improvement, Long-Term Evolution-Advanced (LTE-A), are attractive choices for Machine-to-Machine (M2M) communication due to their ubiquitous coverage and high bandwidth. However, the focus of LTE design was high performance connection-based communications between human-operated devices (also known as human-to-human, or H2H traffic), which was initially established over the Physical Random Access Channel (PRACH). On the other hand, M2M traffic is mostly based on contention-based transmission of short messages and does not need connection establishment. As a result, M2M traffic transmitted over LTE PRACH has to use the inefficient four-way handshake and compete for resources with H2H traffic. When a large number of M2M devices attempts to access the PRACH, an outage condition may occur; furthermore, traffic prioritization is regulated only through age-based power ramping, which drives the network even faster towards the outage condition. In this article, we describe an overlay network that allows a massive number of M2M devices to coexist with H2H traffic and access the network without going through the full LTE handshake. The overlay network is patterned after IEEE 802.15.6 to support multiple priority classes of M2M traffic. We analyse the performance of the joint M2M and H2H system and investigate the trade-offs needed to keep satisfactory performance and reliability for M2M traffic in the presence of H2H traffic of known intensity. Our results confirm the validity of this approach for applications in crowd sensing, monitoring and others utilized in smart city development.

scholarly journals Realization of LTE physical layer baseband processing architecture for narrowband IOT

2018 ◽  
Vol 7 (2.31) ◽  
pp. 56
Author(s):  
S Syed Ameer Abbas ◽  
M Venisubha ◽  
S Siva Gayathri ◽  
S J. Thiruvengadam
Keyword(s):  
Long Term Evolution ◽  
Smart Devices ◽  
Battery Life ◽  
Term Evolution ◽  
Data Rates ◽  
Massive Number ◽  
Machine Communication ◽  
3Gpp Long Term Evolution ◽  
Resource Elements

The 3GPP Long Term Evolution represents the major innovation in cellular technology. NB-IoT is the 3GPP standard for machine to machine communication finalized within LTE Release13. NB-IoT technology occupies frequency band of 180 kHz bandwidth which corresponds to one resource block in LTE transmission. The Long Term Evolution (LTE) supports higher data rates, higher bandwidth, Low latency, good Quality of Service whereas objective of Narrow Band Internet of Things (NB - IOT) is to achieve extended coverage, to support massive number of smart devices and have multi - year long battery life. So the main focus is linking LTE with IOT. The objective of this paper proposes transmitter architecture of PUCCH (Physical Uplink Control Channel) and PUSCH(Physical uplink Shared Channel) in SISO and SIMO configurations for physical uplink channels of LTE. The physical uplink  and downlink channel processing involves scrambling, modulation, layer mapping, transform precoding, and resource element mapping at the transmitter and the receiver block to have demapping from the resource elements and detection of data. At present, the data for on-off control has been worked and the whole framework has been simulated using Modelsim and implemented in Spartan 6.

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