iBUS: An Integrated Beamformer and Uplink Scheduler for OFDMA Small Cells

Arslan, Mustafa Y.; Sundaresan, Karthikeyan; Krishnamurthy, Srikanth V.; Rangarajan, Sampath

doi:10.1109/tnet.2015.2393356

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…By inversing the (10) and (11), the end point of signal to noise ratios can be computed if the end point packet failure probability of a service provider is as follows:…”

Section: Adaptive Modulation Schemementioning

confidence: 99%

Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Mahesh¹,

Chitnis

2019

IJEECS

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the increased usage of smart phones has led to increase usage an internet based application services. These application requires different quality of service (QoS) and bandwidth requirement. WiMAX is an efficient network to provision high bandwidth connectivity and coverage to end user. To meet QoS requirement the exiting model used adaptive model selection scheme. However, these model induce bandwidth wastage as it does not considers any feedback information for scheduling. This work present an Adaptive Uplink Scheduling (AUS) by optimizing MAC layer using Multi-Objective Genetic Algorithm (MOGA). The MAC scheduler use feedback information from both physical layer and application layer. Further, to meet QoS requirement of application and utilize bandwidth efficiently this paper presented an adaptive modulation selection scheme based on user application requirement using MOGA. Our model provides application level based QoS provisioning for WiMAX network. Experiment are conducted to evaluate performance of AUS over exiting model. The overall result attained shows AUS model attain good performance in term of throughput, successful packet transmission and packet collision.

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“…By inversing the (10) and (11), the end point of signal to noise ratios can be computed if the end point packet failure probability of a service provider is as follows:…”

Section: Adaptive Modulation Schemementioning

confidence: 99%

Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Mahesh¹,

Chitnis

2019

IJEECS

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“…Tables and depict the QoS classes of IEEE 802.16 and QCI of 3GPP LTE‐A standardization, respectively, in terms of priority order . Arslan et al propose an algorithm, which is claimed to be efficient for both discrete and continuous function with a worst‐case guarantee of ½ to determine better transmission rate on LTE‐A networks. As the algorithm is designed to be omnidirectional antenna specific, it could not be fit into the examination of nrtPS and nrtPS especially to fulfill the demand of bandwidth request.…”

Section: Related Workmentioning

confidence: 99%

Analyzing enhanced real‐time uplink scheduling algorithm in 3GPP LTE‐advanced networks using multimedia systems

Deebak

Ever

Al‐Turjman

2018

Trans Emerging Tel Tech

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Third Generation Partnership Project (3GPP) standardizes the Long‐Term Evolution (LTE) to improve the quality of service in modern communication systems using 3GPP LTE‐advanced (LTE‐A) networks. As this technology is converging with modern devices, efficient resource allocation schemes are essential for minimization of the communication delay for the sensitive real‐time devices. To achieve the demands of latest technologies, this paper proposes two novel mechanisms, enhanced real‐time polling system with continuous time–batch Markovian arrival process and proactive resource allocation framework. The objective of the former mechanism is to improvise the service connectivity between the multimedia devices in LTE‐A networks and the latter is to exploit the transmission bits in each user's buffer in addition to the state information of wireless channel. The proposed mechanisms consider the constraints enforced by 3GPP standard in terms of radio resource blocks allocation for LTE‐A networks. In addition, the proposed mechanisms use LTE‐A networks to investigate the Voice over LTE traffic in order to analyze various quality‐of‐service measures, namely, sum throughput, session setup delay, packet delivery ratio, resource utilization ratio, and throughput improvement via real‐time multimedia client‐server systems. The probing results show that the proposed algorithm is superior in comparison to other typical services of IEEE 802.16d/e–based systems as well as LTE‐A system with 7 orthogonal frequency‐division multiplexing symbols over a duration slot 0.5 ms. While the slotted duration is set to 5 ms, the proposed framework effectively utilizes the resource allocation cycle to support the uplink scheduling to outperform at least 38% better throughput performance in comparison with existing mechanisms.

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“…Their distance, in terms of the number of subcarriers between two consecutive pilot symbols, can be chosen without the need to agree with the frequency domain sampling theory. [27][28][29] 2.3 | The signal-to-noise ratio (SNR)…”

Section: The Pilots Locationmentioning

confidence: 99%

Performance evaluation of Wi‐Fi and WiMAX over OFDM physical layer

Rodrigues

Korotaev

et al. 2018

Int J Communication

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Orthogonal frequency division multiplexing (OFDM) is an alternative technology that is constrained to keep up with the increasingly high data transmission rate due to its robustness against selective frequency fading and its resistance to intersymbol interference (ISI). This paper aims to study and optimize its performance, namely, its probability of communication failure and signal-tointerference-plus-noise ratio (SINR) metrics. The mathematical tool used to perform OFDM evaluation and analysis is the Fourier transform and its properties. The obtained results of those equations led to the demonstration of the probability of communication outage and to notice that the cutoff time occurs after the 10th iteration for values of λ less than or equal to 1. It could also be checked that this period is small if λ exceeds 1 by considering the sensitivity factor. Moreover, for the obtained results, in terms of bit error rate (BER) and SINR, the influence of the modulation on the error vector magnitude (EVM) shows the sensitivity factor Ω presents a key role in the transmission chain.

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iBUS: An Integrated Beamformer and Uplink Scheduler for OFDMA Small Cells

Cited by 5 publications

References 27 publications

Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Analyzing enhanced real‐time uplink scheduling algorithm in 3GPP LTE‐advanced networks using multimedia systems

Performance evaluation of Wi‐Fi and WiMAX over OFDM physical layer

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