scholarly journals Investigations of Component Carrier Selection Algorithms in Long Term Evolution-Advanced

2018 ◽  
Vol 10 (1) ◽  
pp. 330
Author(s):  
Huda Adibah Mohd Ramli ◽  
Ani Liza Asnawi ◽  
Farah Nadia Mohd Isa ◽  
Amelia Wong Azman ◽  
Mohamad ‘Ismat Hafizi Mansor
Keyword(s):  
Real Time ◽  
Long Term Evolution ◽  
Data Rate ◽  
System Capacity ◽  
Performance Study ◽  
Current Frequency ◽  
Term Evolution ◽  
Selection Algorithms ◽  
Long Term Evolution Advanced

<p>Given that the demand for real-time multimedia contents that require significantly high data rate are getting of high popularity, a new mobile cellular technology known as Long term Evolution-Advanced (LTE-A) was standardized. The LTE-A is envisaged to support high peak data rate by aggregating more than one Component Carriers (CCs) of the same or different frequency bandwidths. Since the inter-band non-contiguous carrier aggregation is likely to be used due to the current frequency allocation, this paper provides a performance study of a number of CC selection algorithms for use in the inter-band non-contiguous downlink LTE-A. It should be noted that CC selection is of paramount importance in the LTE-A operating in backward compatible mode as the LTE-A contains a mixture of the legacy Long Term Evolution (LTE) users that support packets (re)transmission on a single CC and the LTE-A users that utilize more than one CCs for packets (re)transmission. Simulation results demonstrated the efficacy of the Channel-Throughput Aware (CTA) algorithm for maximizing the system capacity without compromising the required Quality of Service of real-time video users.</p>

scholarly journals A study of packet scheduling algorithms in long term evolution-advanced

2020 ◽  
Vol 18 (1) ◽  
pp. 516
Author(s):  
Mohd Mueen Ul Islam Mattoo ◽  
Huda Adibah Mohd Ramli
Keyword(s):  
Packet Scheduling ◽  
Scheduling Algorithms ◽  
Long Term Evolution ◽  
System Capacity ◽  
Term Evolution ◽  
Lte Advanced ◽  
Radio Resources ◽  
The Impact ◽  
Long Term Evolution Advanced

<span lang="EN-GB">The allocation of radio resources is one of the most critical functions performed by the Radio Resource Management (RRM) mechanisms in the downlink Long Term Evolution – Advanced (LTE-Advanced). Packet scheduling concerns itself with allocation of these radio resources in an intelligent manner such that system throughput/capacity can be maximized whilst the required multimedia Quality of Service (QoS) is met. Majority of the previous studies of packet scheduling algorithms for LTE-Advanced did not take the effect of channel impairments into account. However, in real world the channel impairments cannot be obliterated completely and have a direct impact on the packet scheduling performance. As such, this work studies the impact of channel impairments on packet scheduling performance in a practical downlink LTE-Advanced. The simulation results obtained demonstrate the efficacy of RM2 scheduling algorithm over other scheduling algorithms in maximizing the system capacity and is more robust on the effect of the cellular channel impairments.  </span>

Simulation of Packet Scheduling in Cognitive Long Term Evolution-Advanced

2017 ◽  
Vol 8 (2) ◽  
pp. 533
Author(s):  
Mohamad ‘Ismat Hafizi Mansor ◽  
Huda Adibah Mohd Ramli ◽  
Ani Liza Asnawi ◽  
Farah Nadia Mohd Isa
Keyword(s):  
Real Time ◽  
Packet Scheduling ◽  
Long Term Evolution ◽  
Multimedia Content ◽  
Multimedia Contents ◽  
Term Evolution ◽  
Spectrum Scarcity ◽  
Qos Requirement ◽  
Long Term Evolution Advanced

<p>Real Time (RT) and Non-Real Time (NRT) multimedia content demand on mobile devices are increasing at a high pace. Long Term Evolution-Advanced (LTE-A) is expected to cater these demands. However, LTE-A operates at fixed spectrum which leads to spectrum scarcity. Cognitive Radio (CR) is one the promising technologies that is used to overcome spectrum scarcity and implementation of CR into LTE-A will improve spectrum availability and efficiency of the network. Furthermore, with addition of Packet Scheduling (PS) in the cognitive LTE-A, QoS requirement of the mobile users can be guaranteed. However, the study on the stated is very limited. Thus, this paper models, simulates and evaluates performance of five well-known PS algorithms for supporting the RT and NRT multimedia contents. The simulation results show that Maximum- Largest Weighted Delay First (M-LWDF) is the best candidate for implementation in the cognitive LTE-A.</p>

scholarly journals AN ENHANCED PACKET SCHEDULING ALGORITHM FOR THE DOWNLINK COGNITIVE LONG TERM EVOLUTION-ADVANCED

2020 ◽  
Vol 21 (1) ◽  
pp. 51-60
Author(s):  
Huda Adibah Mohd Ramli ◽  
Mohamad 'Ismat Hafizi Mansor
Keyword(s):  
Real Time ◽  
Packet Scheduling ◽  
Scheduling Algorithm ◽  
Long Term Evolution ◽  
Packet Transmission ◽  
Available Bandwidth ◽  
Term Evolution ◽  
Packet Scheduling Algorithm ◽  
Long Term Evolution Advanced

A packet scheduling algorithm known as Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) is proposed in this paper. It aims to maximize the number of Real Time (RT) and Non Real Time (NRT) users that meet their desired Quality of Service (QoS) in the cognitive Long Term Evolution-Advanced (LTE-A). This cognitive LTE-A allows its Component Carriers (CCs) to be combined with licensed CCs from another system. This enables the LTE-A to further expand the available bandwidth for packet transmission. The EM-LWDF algorithm decides the priority of each user on the basis of the desired QoS of each packet, the urgency of each packet, channel quality and the average throughput. The potential of this algorithm is validated via computer simulation where it is able to simultaneously maximize more users that meet their desired QoS in realistic RT and NRT multimedia of the downlink cognitive LTE-A. ABSTRAK: Algoritma penjadualan paket yang dikenali sebagai Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) dicadangkan dalam kertas ini. Ia bertujuan untuk memaksimumkan bilangan pengguna Real Time (RT) dan Non Real Time (NRT) yang memenuhi Kualiti Perkhidmatan yang dikehendaki (QoS) dalam system kognitif Long Term Evolution-Advanced (LTE-A). Kognitif LTE-A ini membolehkan Carrier Component (CC) untuk digabungkan dengan CC berlesen dari sistem lain. Ini membolehkan LTE-A untuk memperluaskan jalur lebar yang tersedia bagi penghantaran paket. Algoritma EM-LWDF menentukan keutamaan setiap pengguna berdasarkan QoS yang dikehendaki dari setiap paket, kecemasan setiap paket, kualiti saluran dan purata penghantaran. Potensi algoritma ini disahkan melalui simulasi komputer di mana ia dapat memaksimumkan lebih banyak pengguna yang memenuhi QoS yang dikehendaki mereka dalam realistik RT dan NRT multimedia dari downlink sistem kognitif LTE-A.

Urgency-Aware Scheduling Algorithm for Downlink Cognitive Long Term Evolution-Advanced

2019 ◽  
Author(s):  
Huda Adibah Mohd Ramli ◽  
Farah Nadia Mohd Isa ◽  
Ani Liza Asnawi ◽  
Ahmad Zamani Jusoh ◽  
Amelia Wong Azman
Keyword(s):  
Scheduling Algorithm ◽  
Long Term Evolution ◽  
Term Evolution ◽  
Long Term Evolution Advanced

Comparison of multicast/broadcast services in Long Term Evolution Advanced and IEEE 802.16m networks

2012 ◽  
Vol 14 (7) ◽  
pp. 717-728 ◽  
Author(s):  
Jorge Calabuig ◽  
Jose F. Monserrat ◽  
David Martín-Sacristán ◽  
Joan Olmos
Keyword(s):  
Long Term Evolution ◽  
Term Evolution ◽  
Ieee 802.16M ◽  
Long Term Evolution Advanced
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