Enhanced PSO based energy-efficient resource allocation and CQI based MCS selection in LTE-A heterogeneous system

Du, Jianbo; Zhao, Liqiang; Feng, Jie; Xin, Jie; Wang, Yong

doi:10.1109/cc.2016.7781730

Cited by 10 publications

(9 citation statements)

References 2 publications

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“…Generally, the Long Term Evolution‐Advanced (LTE‐A) networks degrade because of its lagging in QoS and energy efficiency. To manage these issues, Du et al 5 made an RB allocation process by combining the genetic algorithm (GA) with the particle swarm optimization (PSO) algorithms. It divided and examined as three subproblems, namely, the Modulation and Coding Scheme (MCS), the RB allocation, and the power distribution.…”

Section: Literature Surveymentioning

confidence: 99%

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Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

Pradeep¹,

Lakshminarasimman

2022

Int J Communication

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Summary The increase in mobile communication has been caused the network traffic problem. For that, phantom cell is used for further spectrum efficiency enhancements. In this paper, improved cat swarm optimization clustering (ICSOC)‐based energy aware load balancing is made for both macro cell and small cell to improve the broadband network efficiency using 5G and beyond wireless networks. Then, Multilevel Feedback Queue with Round Robin (MFQ‐RR) scheduling is used to provide superior channel quality and well improved resource sharing for mobile phones. In this wireless network, the phantom cells provided a feasible and cost‐effective way of refining the network coverage and capacity for both local and wide area networks because of their low cost and easy deployment. This system has highly efficient, cost effective, and flexible that will fulfill the end user expectations, and it enhances the capacity and flexible multi‐RAT access to support the diverse applications. This system performance is evaluated using MATLAB 12 software. From experimental results, it is observed that the throughput and spectral efficiency are increased by 20% and 35%, respectively. As well as the packet delay is reduced to 12% and packet loss ratio is 33% decreased when compared with the existing techniques.

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Section: Literature Surveymentioning

confidence: 99%

“…To attain the alike, the best location of cat (i.e., node) is mutated. The Cauchy mutation operator is described by means of Equations ( 4) and (5).…”

Section: Cauchy Mutation Operatormentioning

confidence: 99%

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

Pradeep¹,

Lakshminarasimman

2022

Int J Communication

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“…The two techniques have been jointly used to enhance the speed of the convergence while finding the optimal solution. A more detailed study by the same authors which follows the same approach was addressed in another study . The proposed study uses the same techniques to solve the radio resource allocation problem in order to maximize the energy efficiency in the system under the quality of service constraints.…”

Section: Related Workmentioning

confidence: 99%

“…A more detailed study by the same authors which follows the same approach was addressed in another study. 7 The proposed study uses the same techniques to solve the radio resource allocation problem in order to maximize the energy efficiency in the system under the quality of service constraints. The problem consisted of three subproblems, namely resource blocks allocation, power distribution, and modulation schemes assignment problem.…”

Section: Related Workmentioning

confidence: 99%

Optimal location management in LTE networks using evolutionary techniques

Aqeeli

Hashim

Haque

et al. 2019

Int J Communication

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Summary Wireless network is considered a vital enabler in the world of information technology, specifically, LTE and LTE advanced networks, which are the latest technologies owing to their fast speed, robustness, and large bandwidth. However, in spite of the aforementioned advancements, signaling overhead poses critical challenges in terms of network availability, especially those caused by location management messages which are related to users’ mobility behavior. This paper seeks to address the problem of signaling overhead caused by the location management messages specifically, tracking area update (TAU) and paging by deploying three evolutionary algorithms, namely particle swarm optimization (PSO), artificial bee colony (ABC), and gravitational search algorithm (GSA). The deployed algorithms guarantee yielding the minimum values of the signaling overhead for TAU, paging, and the battery power consumption of the user. It is shown that ABC‐based algorithm has faster convergence and better signaling overhead when compared with other implemented algorithms. Moreover, the measured relative standard deviation (RSD) value of all algorithms shows low uncertainty of around 1% for the objective function and 3% for the paging, TAU, and power. Hence, the three applied optimization algorithms have proven to be efficient and reliable for solving the problem in a large‐scale environment.

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“…There are few studies focused on the performance of joint MCS and PRBs assignment for the LTE UL. In [9], a downlink (DL) FDPS, together with the MCS assignment algorithm, provide system reliability by the allocation of a lower order MCS to users who have poor channel quality. Nevertheless, the DL FDPS does not comply with the contiguity constraint of a UL FDPS.…”

mentioning

confidence: 99%

A Joint Modulation-Coding Scheme and Resource Allocation in LTE Uplink

Gutierrez

Rangel

Gómez

et al. 2020

ELEKTRON ELEKTROTECH

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In Long Term Evolution (LTE) Resource Allocation Algorithms (RAAs) are an area of work where researchers are seeking to optimize the efficient use of scarce radio resources. The selection of an optimal Modulation and Coding Scheme (MCS) that allows LTE to adapt to channel conditions is a second area of ongoing work. In the wireless part of LTE, these two factors, RAA and MCS selection, are the most critical in optimization. In this paper, the performance of three resource allocation schemes is compared, and a new allocation scheme, Average MCS (AMCS) allocation, is proposed. AMCS is seen to outperform both “Minimum MCS (MMCS)” and “Average Signal to Interference and Noise Ratio MCS (SINR AMCS)” in terms of improvements to LTE Uplink (UL) performance. The three algorithms were implemented in the Vienna LTE-A Uplink Simulator v1.5.

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Enhanced PSO based energy-efficient resource allocation and CQI based MCS selection in LTE-A heterogeneous system

Cited by 10 publications

References 2 publications

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

Optimal location management in LTE networks using evolutionary techniques

A Joint Modulation-Coding Scheme and Resource Allocation in LTE Uplink

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