Intelligent spectral efficiency and energy efficiency enhancement in LTE‐Advanced heterogeneous networks

Tactile internet (TI) has emerged as a new possibility into revolutionizing whole society by involving human beings, communication aspects, and industrial operation. Main purpose of TI is to disseminate perceptual, that is, haptic information to remote industry machines for pouring skills and expertise as if it were actually accomplished by a person in reality. Internet of things is an established tool to serve various smart application development that mainly depends on sensors, actuators, communication technology, and cloud‐based services. Existing studies do not clearly mention the key requirements, architectural standardization and TI enabled functions to transfer haptic information via a suitable communication media. Although 5G has been considered as a valuable core of TI infrastructure, lack of actual implementation and related evidence has raised a dilemma about its effectiveness for industry applications leaving with no direction. In this article, we present architectural and system model‐wise development of tactile internet of things for possible industry application realization. We also present key requirements, functional and optimal aspects of tactile internet of things. Study of potential communication technologies and state‐of‐the‐art study on recent works on TI‐based approaches are paved. Lastly, we present key open challenges and future direction to augment this problem.

Section: Tiot Communications For Industrymentioning

confidence: 99%

Section: Tiot Communications For Industrymentioning

confidence: 99%

A review on tactile IoT: Architecture, requirements, prospects, and future directions

Ray

2021

“…Previous works have addressed the efficient configuration of eICIC parameters. Some works focused solely on the CRE bias, 14‐16 others focused on the ABS ratio, 17‐21,27 while fewer works 22,23,28 aimed at optimizing both parameters simultaneously, like this work.…”

Section: Related Work and Contributionmentioning

confidence: 99%

Online reinforcement learning for adaptive interference coordination

Alcaraz

Ayala‐Romero

Vales‐Alonso

et al. 2020

Heterogeneous networks (HetNets), in which small cells overlay macro cells, are a cost-effective approach to increase the capacity of cellular networks. However, HetNets have raised new issues related to cell association and interference management. In particular, the optimal configuration of interference coordination (IC) parameters is a challenging task because it depends on multiple stochastic processes such as the locations of the users, the traffic demands, or the strength of the received signals. This work proposes a self-optimization algorithm capable of finding the optimal configuration in an operating network. We address the problem using a reinforcement learning (RL) approach, in which the actions are the IC configurations, whose performances are initially unknown. The main difficulty is that, due to the variable network conditions, the performance of each action may change over time. Our proposal is based on two main elements: the sequential exploration of subsets of actions (exploration regions), and an optimal stopping (OS) strategy for deciding when to end current exploration and start a new one. For our algorithm, referred to as local exploration with optimal stopping (LEOS), we provide theoretical bounds on its long-term regret per sample and its convergence time. We compare LEOS to state-of-the-art learning algorithms based on multiarmed bandits and policy gradient RL. Considering different changing rates in the network conditions, our numerical results show that LEOS outperforms the first alternative by 22%, and the second one by 48% in terms of average regret per sample.

“…Therefore, using as much power as possible to maximize spectral efficiency would ultimately reduce the efficiency in using energy resource. To illustrate the SE reduction issue in wireless networks, recent works such as Reference 3 consider that one of the main causes of SE‐EE degradation is the intercellular interference (cochannels); thus, the authors propose an intelligent fuzzy‐based reduced power time‐domain resource partitioning scheme to mitigate the interference level of victim macro users in the feICIC LTE‐HetNets context.The proposed fuzzy feICIC technique is able to control the transmit power of the interfering femto base station while taking into account the throughput of edge macro users and fairness of femto subscribers. As a result, authors sustain that the proposed method improved the overall SE‐EE of the wireless communication system.…”

Section: Introductionmentioning

confidence: 99%

Spectral and energy efficiency tradeoff in optical code division multiple access networks

Martinez

Abrão

2020

A paradigm on the energy efficiency (EE) and spectral efficiency (SE) tradeoff named resource efficiency (RE) exploits the EE‐SE equilibrium, which is formulated as Pareto optimal set based on two objectives balancing power consumption against occupied bandwidth. In optical code division multiple access (OCDMA) networks, the EE‐SE tradeoff is discussed by formulating a multiobjective optimization problem, while solutions are compared by deploying the weighted sum (WS) and ‐Constraint (‐C) scalarization procedures combined with nonlinear programming methods. The generalized RE optimization problem with QoS guarantees for the OCDMA networks is formulated considering that such methods result in the same Pareto boundaries. Theoretical results demonstrate that the obtained numerical optimized solutions are efficient due to the multiobjective characteristics of the optimization problem. Also, considering the numerical tests performed, it is noteworthy that the ‐C procedure found a greater diversity of solutions inside the Pareto front when compared with the WS method.