• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.7A
• /
• pp.660-668
• /
• 2010

In energy resource constrained networks, the network lifetime can be enhanced by optimally allocating energy resource among users based on the available channel state information and the residual energy information at each node. In this paper, we propose the relay selection scheme and power allocation scheme to maximize the network lifetime in wireless relay networks with capacity constraint. The computer simulation results show that the proposed scheme increase the network lifetime in comparison to the conventional schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.794-815
• /
• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.9
• /
• pp.3008-3028
• /
• 2022

In this paper, we investigate traffic scheduling for a delay-sensitive multi-hop relay network, and aim to minimize the priority-based end-to-end delay of different data packet via joint relay selection, subcarrier assignment, and power allocation. We first derive the priority-based end-to-end delay based on queueing theory, and then propose a two-step method to decompose the original optimization problem into two sub-problems. For the joint subcarrier assignment and power control problem, we utilize an efficient particle swarm optimization method to solve it. For the relay selection problem, we prove its convexity and use the standard Lagrange method to deal with it. The joint relay selection, subcarriers assignment and transmission power allocation problem for each hop can also be solved by an exhaustive search over a finite set defined by the relay sensor set and available subcarrier set. Simulation results show that both the proposed routing scheme and the resource allocation scheme can reduce the average end-to-end delay.

• Journal of Satellite, Information and Communications
• /
• v.12 no.2
• /
• pp.46-50
• /
• 2017

In this paper, we propose an artificial intelligence based spectrum allocation scheme for power line communication system. The frequency band of the transmitted signal can be adjusted through the spectrum allocation technique, thereby avoiding interference. This improves the performance of the transmission signal and the spectral efficiency. Through the simulation results, we show that the proposed spectrum allocation technique improves the spectral efficiency and improve the communication performance.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.9A
• /
• pp.729-736
• /
• 2005

In this paper, we introduce a new approach for the design of uplink sub-channel allocation and power control in the High-speed Portable Internet system that is based on OmMAnDD scheme. In OFDMA system, because the number of allocated sub-channel in mobile station varies from one to the whole sub-channel as in base station while mobile station's transmit power is lower than that of base station, full loading range(FLR) constraint occurs where whole sub-channel can be used and the conventional open-loop power control scheme can not be used beyond FLR. We propose a new scheme that limits the maximum sub-channel allocation number and uses power concentration gain(PCG) depending on location of mobile station, which is based on ranging in OfDMA system. Simulation results show that the proposed scheme extends the uplink coverage to the entire cell service coverage area, provides solutions for optimum utilization of radio resource and enables open-loop power control beyond FLR without extra hardware complexity.

• ETRI Journal
• /
• v.36 no.3
• /
• pp.506-509
• /
• 2014

This paper studies the energy efficiency power allocation for cognitive radio networks based on uplink orthogonal frequency-division multiplexing. The power allocation problem is intended to minimize the maximum energy efficiency measured by "Joule per bit" metric, under total power constraint and robust aggregate mutual interference power constraint. However, the above problem is non-convex. To make it solvable, an equivalent convex optimization problem is derived that can be solved by general fractional programming. Then, a robust energy efficiency power allocation scheme is presented. Simulation results corroborate the effectiveness of the proposed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2243-2257
• /
• 2019

A heterogeneous cellular network (HCN) is useful to increase the spectral and energy efficiency of wireless networks and to reduce the traffic load from the macro cell. The performance of the secondary user equipment (SUE) is affected by interference from the eNodeB (eNB) in a macro cell. To decrease the interference between the macro cell and the small cell, allocating resources properly is essential to an HCN. This study considers the scenario of a software-defined heterogeneous cellular network and performs the resource allocation process. First, we show the system model of HCN and formulate the optimization problem. The optimization problem is a complex process including power and frequency resource allocation, which imposes an extremely high complexity to the HCN. Therefore, a hierarchical resource allocation scheme is proposed, which including subchannel selection and a particle swarm optimization (PSO)-based power allocation algorithm. Simulation results show that the proposed hierarchical scheme is effective in improving the system capacity and energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.4923-4939
• /
• 2019

In this paper, a secure transmission scheme based on the artificial noise is proposed for D2D communications underlaying the full-duplex cellular network, and a secure power allocation scheme to maximize the overall secrecy rate of both the cellular user and D2D transmitter node is presented. Firstly, the full-duplex base station transmits the artificial noise to guarantee the secure communications when it receives signals of cellular uplinks. Under this secure framework, it is found that improving the transmission power of the cellular user or the D2D transmitter node will degrade the secrecy rate of the other, although will improve itself secrecy rate obviously. Hence, a secure power allocation scheme to maximize the overall secrecy rate is presented subject to the security requirement of the cellular user. However, the original power optimization problem is non-convex. To efficiently solve it, we recast the original problem into a convex program problem by utilizing the proper relaxation and the successive convex approximation algorithm. Simulation results evaluate the effectiveness of the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.5
• /
• pp.1286-1302
• /
• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• Journal of Electrical Engineering and Technology
• /
• v.4 no.3
• /
• pp.337-345
• /
• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.