• ETRI Journal
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• v.45 no.5
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• pp.874-886
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• 2023

A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.691-708
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• 2010

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.17-29
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• 1999

This paper presents a high level synthesis method targeting low power consumption for data-dominated CMOS circuits (e.g., DSP). The high level synthesis is divided into three basic tasks: scheduling, resource and register allocation. For lower power scheduling, we increase the possibility of reusing an input operand of functional units. For a scheduled data flow graph, a compatibility graph for register and resource allocation is formed, and then a special weighted network is then constructed from the compatibility graph and the minimum cost flow algorithm is performed on the network to obtain the minimum power consumption data path assignment. The formulated problem is then solved optimally in polynomial time. This method reduces both the switching activity and the capacitance in synthesized data path. Experimental results show 15% power reduction in benchmark circuits.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.826-832
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• 2015

In wireless networks, it is important to guarantee the energy efficiency and receiver fairness for satisfying service provider and customer at the same time. In this paper, we propose a resource allocation algorithm which improves energy efficiency as well as receiver fairness based on optimization techniques. In the proposed algorithm, subchannel and power are allocated to receivers iteratively in the consideration of channel state information, amount of dissipated power, and receiver rate, in order to improve energy efficiency and receiver fairness. Through simulation, we show the effectiveness and superiority of the proposed algorithm in terms of energy efficiency and receiver fairness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.152-167
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• 2016

This paper investigates the simultaneous wireless information and power transfer (SWIPT) for two-hop orthogonal frequency division multiplexing (OFDM) decode-and-forward (DF) relay network, where a relay harvests energy from radio frequency signals transmitted by a source and then uses the harvested energy to assist information transmission from the source to its destination. The power splitting receiver is considered at the relay. To explore the performance limit of such a SWIPT-enabled system, a resource allocation (RA) optimization problem is formulated to maximize the achievable information rate of the system, where the power allocation, the subcarrier pairing and the power splitting factor are jointly optimized. As the problem is non-convex and there is no known solution method, we first decompose it into two separate subproblems and then design an efficient RA algorithm. Simulation results demonstrate that our proposed algorithm can achieve the maximum achievable rate of the system and also show that to achieve a better system performance, the relay node should be deployed near the source in the SWIPT-enabled two-hop OFDM DF relay system, which is very different from that in conventional non-SWIPT system where the relay should be deployed at the midpoint of the line between the source and the destination.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3529-3550
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• 2016

In heterogeneous networks (HetNets), energy saving is vital for a sustainable network development. Many techniques, such as spectrum allocation, network planning, etc., are used to improve the network energy efficiency (EE). In this paper, micro BSs utilizing cell range expansion (CRE) and spectrum allocation are considered in multi-channel heterogeneous networks to improve EE. Hotspot region is assumed to be covered by micro BSs which can ensure that the hotspot capacity is greater than the average demand of hotspot users. The expressions of network energy efficiency are derived under shared, orthogonal and hybrid subchannel allocation schemes, respectively. Particle swarm optimization (PSO) algorithm is used to solve the optimal ratio of subchannel allocation in orthogonal and hybrid schemes. Based on the results of the optimal analysis, we propose three service control strategies on the basis of large-scale user behaviors, i.e., adjust micro cell rang expansion (AmCRE), adjust micro BSs density (AmBD) and adjust micro BSs transmit power (AmBTP). Both theoretical and simulation results show that using shared subchannel allocation scheme in AmBD strategies can obtain maximal EE with a very small area ratio. Using orthogonal subchannel allocation scheme in AmCRE strategies can obtain maximal EE when area ratio is larger. Using hybrid subchannel allocation scheme in AmCRE strategies can obtain maximal EE when area ratio is large enough. No matter which service control strategy is used, orthogonal spectrum scheme can obtain the maximal hotspot user rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2949-2963
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• 2019

A novel distributed compress-and-forward (CF) system based on multi-relay network is presented. In this system, as the direct link between the source and destination is invalid due to some reasons, such as the limited power, special working environment, or even economic factors, relays are employed to receive analog signals and carry on distributed compressed encoding. Subsequently, the digital signals are transmitted to the destination via wireless channel. Moreover, a theoretical analysis for the system is provided by utilizing the Chief Executive Officer (CEO) theory and Shannon channel capacity theory, and the rate-distortion function as well as the connection between the transmission rate and the channel capacity are constructed. In addition, an optimal signal-to-noise ratio (SNR) -based power allocation method is proposed to maximize the quantization SNR under the limited total power. Simulation result shows that the proposed CF system outperforms the amplify-and-forward (AF) system versus the SNR performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1517-1524
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• 2022

In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.67-71
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• 2015

In this Paper, we proposed optimization of system performance, power splitting protocols applied to relay in the cooperative communication undergo co-channel interference. When relay adjust power distribution factors undergo co-channel interference, it is possible to optimize and maximize the channel capacity of the receiver. Because of energy haversting, interfence transfer to new power source. If finding the optimal power levels, to solve inability in system, and to increase the efficiency of the network. Finally, performance of the proposed protocol is analyzed in terms of outage probability, capacity of system.

• ETRI Journal
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• v.35 no.3
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• pp.550-553
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• 2013

Due to limited spectrum resources and differences in link loads, network congestion is one of the key issues in cognitive radio wireless mesh networks. In this letter, a congestion avoidance model with power control, channel allocation, and routing under the signal-to-interference-and-noise ratio is presented. As a contribution, a nested optimization scheme combined with a genetic algorithm and linear programming solver is proposed. Extensive simulation results are presented to demonstrate the effectiveness of our algorithm.